{ "servers": [ { "id": "agentndx", "name": "AgentNDX", "description": "A network registry for the agentic web. Search, browse, and query MCP servers, A2A agents, and x402-enabled services.", "category": "data", "endpoint": "https://agentndx.ai/mcp", "homepage_url": "https://agentndx.ai", "github_url": "https://github.com/agentndx/agentndx-web", "x402": true, "x402_price": "$0.005", "verified": true, "protocols": [ "MCP", "x402" ], "transport": "http", "auth": "x402", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "directory", "registry", "mcp", "search", "discovery" ], "use_cases": [ "Search for MCP servers by capability or category", "Discover x402-enabled payment services for agents", "List all available tool categories and their counts" ], "health": "active" }, { "id": "playwright-mcp", "name": "Playwright MCP", "description": "Browser automation and web scraping via Playwright. Navigate, click, fill forms, take screenshots, and extract structured data from any website.", "category": "web", "endpoint": "npx @playwright/mcp", "homepage_url": "https://playwright.dev", "github_url": "https://github.com/microsoft/playwright-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @playwright/mcp", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "browser", "automation", "scraping", "screenshots", "forms" ], "use_cases": [ "Automate browser interactions for web agents", "Extract structured data from dynamic websites", "Run end-to-end tests or browser-based workflows" ], "related_ids": [ "firecrawl-mcp" ], "health": "active" }, { "id": "firecrawl-mcp", "name": "Firecrawl MCP", "description": "Web scraping and crawling with LLM-ready output. Scrape, crawl, map, and extract structured data from any URL. Returns clean markdown.", "category": "web", "endpoint": "npx firecrawl-mcp", "homepage_url": "https://firecrawl.dev", "github_url": "https://github.com/mendableai/firecrawl-mcp-server", "schema_url": "https://firecrawl.dev/schema", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx firecrawl-mcp", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "scraping", "crawling", "markdown", "extraction", "web" ], "use_cases": [ "Extract clean markdown from any webpage for LLM consumption", "Crawl entire sites and build structured data sets", "Map site structure before targeted scraping" ], "related_ids": [ "playwright-mcp" ], "health": "active" }, { "id": "github-mcp", "name": "GitHub MCP", "description": "Full GitHub API access via MCP. Create issues, PRs, manage repos, read code, run searches, and interact with the GitHub ecosystem.", "category": "code", "endpoint": "npx @modelcontextprotocol/server-github", "homepage_url": "https://github.com", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/github", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @modelcontextprotocol/server-github", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "github", "git", "repositories", "issues", "pull-requests" ], "use_cases": [ "Create and manage GitHub issues and PRs from agents", "Search code across repositories", "Automate release workflows" ], "related_ids": [ "filesystem-mcp" ], "health": "active" }, { "id": "filesystem-mcp", "name": "Filesystem MCP", "description": "Local filesystem access for agents. Read, write, search, and manipulate files and directories with configurable path permissions.", "category": "data", "endpoint": "npx @modelcontextprotocol/server-filesystem", "homepage_url": "https://modelcontextprotocol.io", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @modelcontextprotocol/server-filesystem /path/to/dir", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "files", "filesystem", "read", "write", "local" ], "use_cases": [ "Read and write local files from agent workflows", "Search files by name or content pattern", "Manage project directories and assets" ], "related_ids": [ "github-mcp" ], "health": "active" }, { "id": "brave-search-mcp", "name": "Brave Search MCP", "description": "Web and local search via Brave Search API. Privacy-respecting search with real-time results, news, and image search capabilities.", "category": "web", "endpoint": "npx @modelcontextprotocol/server-brave-search", "homepage_url": "https://search.brave.com", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/brave-search", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @modelcontextprotocol/server-brave-search", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "search", "web-search", "brave", "news", "privacy" ], "use_cases": [ "Real-time web search for agents needing current information", "News search for market intelligence workflows", "Image and video search for content pipelines" ], "related_ids": [ "firecrawl-mcp" ], "health": "active" }, { "id": "postgres-mcp", "name": "PostgreSQL MCP", "description": "Read-only PostgreSQL access via MCP. Query databases, inspect schemas, and retrieve structured data. Safe — no write operations.", "category": "data", "endpoint": "npx @modelcontextprotocol/server-postgres", "homepage_url": "https://postgresql.org", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/postgres", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @modelcontextprotocol/server-postgres postgresql://user:pass@host/db", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "database", "postgresql", "sql", "read-only", "schema" ], "use_cases": [ "Query production databases safely from agent workflows", "Inspect table schemas for data pipeline agents", "Answer natural language questions against structured data" ], "related_ids": [ "filesystem-mcp" ], "health": "active" }, { "id": "slack-mcp", "name": "Slack MCP", "description": "Slack workspace integration for agents. Read messages, post to channels, manage threads, and search workspace history.", "category": "communication", "endpoint": "npx @modelcontextprotocol/server-slack", "homepage_url": "https://slack.com", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/slack", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @modelcontextprotocol/server-slack", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "slack", "messaging", "notifications", "team", "communication" ], "use_cases": [ "Post agent results and reports to Slack channels", "Monitor channel activity and trigger workflows", "Search message history for context retrieval" ], "related_ids": [], "health": "active" }, { "id": "context7-mcp", "name": "Context7 MCP", "description": "Live library documentation fetcher for LLMs. Resolves library names to current API docs, preventing hallucinations on outdated APIs.", "category": "ai", "endpoint": "npx @upstash/context7-mcp", "homepage_url": "https://context7.com", "github_url": "https://github.com/upstash/context7", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @upstash/context7-mcp", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "documentation", "libraries", "llm", "context", "api-docs" ], "use_cases": [ "Fetch current library docs during code generation", "Prevent LLM hallucinations on deprecated APIs", "Resolve package names to versioned documentation" ], "related_ids": [ "github-mcp" ], "health": "active" }, { "id": "stripe-agent-toolkit", "name": "Stripe Agent Toolkit", "description": "Stripe payment operations via MCP. Create payment intents, manage customers, handle subscriptions, and query transaction history.", "category": "payments", "endpoint": "npx @stripe/agent-toolkit", "homepage_url": "https://stripe.com/docs/agents", "github_url": "https://github.com/stripe/agent-toolkit", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @stripe/agent-toolkit", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "stripe", "payments", "billing", "subscriptions", "fintech" ], "use_cases": [ "Automate payment collection from agent workflows", "Query customer billing history for support agents", "Create and manage subscription plans programmatically" ], "related_ids": [], "health": "active" }, { "id": "memory-mcp", "name": "Memory MCP", "description": "Persistent memory for AI agents using a knowledge graph. Store, retrieve, and reason over facts, entities, and relationships across sessions.", "category": "data", "endpoint": "npx @modelcontextprotocol/server-memory", "homepage_url": "https://modelcontextprotocol.io", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/memory", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @modelcontextprotocol/server-memory", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "memory", "knowledge-graph", "persistence", "entities", "agent-memory" ], "use_cases": [ "Persist facts and context across agent sessions", "Build and query a knowledge graph of entities and relationships", "Give agents long-term memory without a database" ], "health": "active" }, { "id": "exa-mcp", "name": "Exa MCP", "description": "Semantic and neural web search via Exa. Find exactly what you mean, not just keyword matches. Ideal for research agents that need high-quality results.", "category": "web", "endpoint": "npx exa-mcp", "homepage_url": "https://exa.ai", "github_url": "https://github.com/exa-labs/exa-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx exa-mcp", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "search", "semantic", "neural", "research", "web" ], "use_cases": [ "Semantic search for research and fact-finding agents", "Find recent content on any topic with high relevance", "Neural search that understands intent, not just keywords" ], "health": "active" }, { "id": "notion-mcp", "name": "Notion MCP", "description": "Full Notion workspace access for agents. Read, create, and update pages, databases, and blocks. Connect agents to your team knowledge base.", "category": "productivity", "endpoint": "npx @notionhq/notion-mcp", "homepage_url": "https://notion.so", "github_url": "https://github.com/makenotion/notion-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @notionhq/notion-mcp", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "notion", "productivity", "docs", "database", "knowledge-base" ], "use_cases": [ "Read and write Notion pages and databases from agent workflows", "Sync task and project data between agents and Notion", "Build agents that update documentation automatically" ], "health": "active" }, { "id": "linear-mcp", "name": "Linear MCP", "description": "Official Linear MCP server. Create and manage issues, projects, teams, and cycles in Linear's issue tracking system from agent workflows.", "category": "productivity", "endpoint": "npx -y @linear/mcp-server", "homepage_url": "https://linear.app", "github_url": "https://github.com/linear/linear-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @linear/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "linear", "issues", "project-management", "sprints", "engineering" ], "use_cases": [ "Create Linear issues automatically from Sentry errors or Datadog alerts", "Query and update sprint cycles and project status from agent pipelines", "Triage and assign issues as part of autonomous engineering workflow automation" ], "related_ids": [ "jira-mcp", "github-mcp" ], "health": "active" }, { "id": "cloudflare-mcp", "name": "Cloudflare MCP", "description": "Manage Cloudflare infrastructure from agents. Deploy Workers, manage DNS records, query analytics, and interact with the full Cloudflare API.", "category": "infrastructure", "endpoint": "npx @cloudflare/mcp-server-cloudflare", "homepage_url": "https://cloudflare.com", "github_url": "https://github.com/cloudflare/mcp-server-cloudflare", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @cloudflare/mcp-server-cloudflare", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "cloudflare", "workers", "dns", "infrastructure", "deployment" ], "use_cases": [ "Deploy and manage Cloudflare Workers from agent pipelines", "Query DNS records and zone analytics", "Automate infrastructure changes via agent workflows" ], "health": "active" }, { "id": "sentry-mcp", "name": "Sentry MCP", "description": "Official Sentry MCP server. Access error events, issues, stack traces, and performance data from Sentry for automated debugging and triage workflows.", "category": "code", "endpoint": "npx -y @sentry/mcp-server-sentry", "homepage_url": "https://sentry.io", "github_url": "https://github.com/getsentry/sentry-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @sentry/mcp-server-sentry", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "sentry", "errors", "debugging", "monitoring", "stack-traces" ], "use_cases": [ "Fetch recent Sentry errors and stack traces for autonomous debugging agents", "Triage and assign issues in Sentry from agent-driven incident response workflows", "Monitor error rates and regressions in CI/CD agent pipelines" ], "related_ids": [ "datadog-mcp", "grafana-mcp" ], "health": "active" }, { "id": "fetch-mcp", "name": "Fetch MCP", "description": "HTTP fetch and web content extraction for agents. Retrieve any URL as markdown, HTML, or raw text. Essential for agents that need to read the web.", "category": "web", "endpoint": "npx @modelcontextprotocol/server-fetch", "homepage_url": "https://modelcontextprotocol.io", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/fetch", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @modelcontextprotocol/server-fetch", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "fetch", "http", "web", "scraping", "content" ], "use_cases": [ "Fetch any URL as clean markdown for agent consumption", "Read documentation, articles, and web content", "Lightweight alternative to full browser automation" ], "health": "active" }, { "id": "sequential-thinking-mcp", "name": "Sequential Thinking MCP", "description": "Structured multi-step reasoning for complex problems. Enables agents to break tasks into explicit thought chains, revise reasoning, and build toward solutions methodically.", "category": "ai", "endpoint": "npx @modelcontextprotocol/server-sequential-thinking", "homepage_url": "https://modelcontextprotocol.io", "github_url": "https://github.com/modelcontextprotocol/servers/tree/main/src/sequentialthinking", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @modelcontextprotocol/server-sequential-thinking", "added": "2026-04-09", "updated": "2026-04-09", "tags": [ "reasoning", "thinking", "chain-of-thought", "planning", "problem-solving" ], "use_cases": [ "Break complex tasks into explicit reasoning steps", "Build agent workflows that self-correct mid-task", "Structured problem solving with revisable thought chains" ], "health": "active" }, { "id": "supabase-mcp", "name": "Supabase MCP", "description": "Official Supabase MCP server. Query and manage Postgres databases, auth, storage, and realtime subscriptions directly from agent workflows.", "category": "data", "endpoint": "npx -y @supabase/mcp-server-supabase", "homepage_url": "https://supabase.com", "github_url": "https://github.com/supabase-community/supabase-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @supabase/mcp-server-supabase", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "supabase", "postgres", "database", "auth", "realtime", "storage" ], "use_cases": [ "Run SQL queries and manage Supabase Postgres tables from agent workflows", "Read and write to Supabase Storage buckets during automated tasks", "Trigger Supabase realtime events or Edge Functions from an agent" ], "related_ids": [ "neon-mcp", "planetscale-mcp" ], "health": "active" }, { "id": "google-maps-mcp", "name": "Google Maps MCP", "description": "Official MCP server for the Google Maps Platform API, providing geocoding, directions, places search, and distance matrix tools.", "category": "web", "endpoint": "@modelcontextprotocol/server-google-maps", "homepage_url": "https://developers.google.com/maps", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @modelcontextprotocol/server-google-maps", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "google-maps", "geocoding", "directions", "places", "location" ], "use_cases": [ "Geocode addresses and look up place details for location-aware agents", "Calculate routes and travel times between locations", "Search for nearby businesses and points of interest" ], "health": "active" }, { "id": "gdrive-mcp", "name": "Google Drive MCP", "description": "Official MCP server for reading and searching files in Google Drive, including Docs, Sheets, and PDF content extraction.", "category": "productivity", "endpoint": "@modelcontextprotocol/server-gdrive", "homepage_url": "https://drive.google.com", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @modelcontextprotocol/server-gdrive", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "google-drive", "documents", "files", "cloud-storage", "oauth" ], "use_cases": [ "Search and read Google Drive documents from within an agent workflow", "Extract content from Docs, Sheets, and PDFs for context retrieval", "List and navigate shared drives and folder structures" ], "health": "active" }, { "id": "docker-mcp", "name": "Docker MCP", "description": "MCP server for managing Docker containers, images, and volumes through natural language commands.", "category": "infrastructure", "endpoint": "mcp-server-docker", "github_url": "https://github.com/QuantGeekDev/docker-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y mcp-server-docker", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "docker", "containers", "devops", "infrastructure", "images" ], "use_cases": [ "List, start, stop, and inspect Docker containers from an agent", "Build and manage Docker images programmatically", "Execute commands inside running containers for debugging" ], "health": "active" }, { "id": "aws-api-mcp", "name": "AWS API MCP", "description": "Official AWS Labs MCP server enabling AI assistants to interact with AWS services via CLI commands with IAM-based permissions and CloudTrail logging.", "category": "infrastructure", "endpoint": "awslabs.aws-api-mcp-server", "homepage_url": "https://awslabs.github.io/mcp/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx awslabs.aws-api-mcp-server", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "aws", "cloud", "infrastructure", "iam", "multi-service" ], "use_cases": [ "Manage AWS resources like S3, EC2, and Lambda through agent commands", "Query AWS documentation and best practices during development", "Execute validated AWS CLI commands with audit trail via CloudTrail" ], "health": "active" }, { "id": "discord-mcp", "name": "Discord MCP", "description": "MCP server for Discord bot integration, enabling agents to read and send messages, manage channels, and interact with guild members.", "category": "communication", "endpoint": "mcp-server-discord", "github_url": "https://github.com/barryyip0625/mcp-discord", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y mcp-server-discord", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "discord", "chat", "bot", "messaging", "community" ], "use_cases": [ "Send and read messages in Discord channels from an agent", "Manage Discord server channels and permissions", "Monitor community conversations and respond to mentions" ], "health": "active" }, { "id": "qdrant-mcp", "name": "Qdrant MCP", "description": "Official Qdrant MCP server for storing, retrieving, and searching vector embeddings in the Qdrant vector database.", "category": "ai", "endpoint": "mcp-server-qdrant", "homepage_url": "https://qdrant.tech", "github_url": "https://github.com/qdrant/mcp-server-qdrant", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx mcp-server-qdrant", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "qdrant", "vector-search", "embeddings", "semantic-search", "memory" ], "use_cases": [ "Store and retrieve agent memories using vector similarity search", "Build RAG pipelines with semantic document retrieval", "Manage vector collections and perform filtered searches" ], "health": "active" }, { "id": "replicate-mcp", "name": "Replicate MCP", "description": "Official MCP server for Replicate, enabling agents to run ML model inference across thousands of open-source models.", "category": "ai", "endpoint": "replicate-mcp", "homepage_url": "https://replicate.com", "github_url": "https://github.com/replicate/replicate-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y replicate-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "replicate", "ml-inference", "image-generation", "models" ], "use_cases": [ "Run image generation models like Stable Diffusion and Flux from an agent", "Execute language, audio, and video models via Replicate's API", "Search available models and check prediction status" ], "health": "active" }, { "id": "tavily-mcp", "name": "Tavily MCP", "description": "MCP server for Tavily's AI-optimized search API, purpose-built for agent web research with structured, LLM-friendly results.", "category": "web", "endpoint": "tavily-mcp", "homepage_url": "https://tavily.com", "github_url": "https://github.com/tavily-ai/tavily-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y tavily-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "tavily", "search", "web-search", "research", "ai-search" ], "use_cases": [ "Perform agent-optimized web searches with clean extracted content", "Research topics with structured results tuned for LLM consumption", "Fact-check claims and gather real-time information" ], "health": "active" }, { "id": "twilio-mcp", "name": "Twilio MCP", "description": "Official Twilio MCP server. Send SMS and WhatsApp messages, make voice calls, manage phone numbers, and access Twilio's communications APIs from agents.", "category": "communication", "endpoint": "npx -y @twilio/mcp-server", "homepage_url": "https://twilio.com", "github_url": "https://github.com/twilio-labs/twilio-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @twilio/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "twilio", "sms", "voice", "whatsapp", "messaging", "phone" ], "use_cases": [ "Send SMS notifications from autonomous agents without manual intervention", "Trigger voice calls and IVR flows from agent-driven customer communication pipelines", "Manage Twilio phone numbers and messaging services programmatically" ], "related_ids": [ "whatsapp-mcp", "telegram-mcp" ], "health": "active" }, { "id": "kubernetes-mcp", "name": "Kubernetes MCP", "description": "MCP server for interacting with Kubernetes clusters via kubectl, supporting pod management, deployments, and cluster inspection.", "category": "infrastructure", "endpoint": "mcp-server-kubernetes", "github_url": "https://github.com/Flux159/mcp-server-kubernetes", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y mcp-server-kubernetes", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "kubernetes", "k8s", "containers", "orchestration", "devops" ], "use_cases": [ "List, inspect, and manage Kubernetes pods and deployments", "Apply and rollback Kubernetes manifests from an agent", "Debug cluster issues by reading logs and describing resources" ], "health": "active" }, { "id": "vercel-mcp", "name": "Vercel MCP", "description": "Official Vercel MCP server. Manage deployments, projects, domains, environment variables, and logs from Vercel's frontend cloud within agent workflows.", "category": "infrastructure", "endpoint": "npx -y @vercel/mcp-adapter", "homepage_url": "https://vercel.com", "github_url": "https://github.com/vercel/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @vercel/mcp-adapter", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "vercel", "deployment", "serverless", "frontend", "domains" ], "use_cases": [ "Trigger and monitor Vercel deployments from CI/CD agent workflows", "Manage environment variables and project settings across Vercel teams", "Inspect deployment logs and build output for automated debugging pipelines" ], "related_ids": [ "cloudflare-workers-mcp", "pulumi-mcp" ], "health": "active" }, { "id": "1password-mcp", "name": "1Password MCP", "description": "MCP server for 1Password vault access, enabling agents to securely retrieve credentials, secrets, and secure notes via Service Account.", "category": "identity", "endpoint": "@takescake/1password-mcp", "github_url": "https://github.com/CakeRepository/1Password-MCP", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @takescake/1password-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "1password", "secrets", "credentials", "vault", "identity" ], "use_cases": [ "Retrieve API keys and credentials from 1Password vaults during agent workflows", "List and search vault items for secure secret management", "Inject secrets into configuration without exposing them in plaintext" ], "health": "active" }, { "id": "cloudinary-mcp", "name": "Cloudinary MCP", "description": "Official Cloudinary MCP server for uploading, transforming, analyzing, and organizing media assets in Cloudinary's image and video CDN.", "category": "media", "endpoint": "@cloudinary/asset-management-mcp", "homepage_url": "https://cloudinary.com/documentation/cloudinary_llm_mcp", "github_url": "https://github.com/cloudinary/mcp-servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @cloudinary/asset-management-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "cloudinary", "images", "video", "cdn", "media" ], "use_cases": [ "Upload and transform images and videos in Cloudinary from an agent", "Search and organize media assets with AI-powered tagging", "Generate responsive image URLs with on-the-fly transformations" ], "health": "active" }, { "id": "unsplash-mcp", "name": "Unsplash MCP", "description": "MCP server for searching and retrieving high-quality stock photos from Unsplash with proper attribution metadata.", "category": "media", "endpoint": "@jeff_kit/unsplash-mcp-server", "github_url": "https://github.com/jeffkit/unsplash-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @jeff_kit/unsplash-mcp-server", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "unsplash", "photos", "stock-images", "media", "creative" ], "use_cases": [ "Search for relevant stock photos by keyword for content creation", "Retrieve image URLs with proper attribution for published content", "Browse curated photo collections for design and marketing workflows" ], "health": "active" }, { "id": "gitlab-mcp", "name": "GitLab MCP", "description": "Official MCP server for the GitLab API, supporting project management, merge requests, issues, file operations, and CI/CD pipelines.", "category": "code", "endpoint": "@modelcontextprotocol/server-gitlab", "homepage_url": "https://docs.gitlab.com/user/gitlab_duo/model_context_protocol/mcp_server/", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @modelcontextprotocol/server-gitlab", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "gitlab", "git", "repositories", "merge-requests", "ci-cd" ], "use_cases": [ "Create and manage GitLab merge requests and issues from an agent", "Read and modify repository files and branches programmatically", "Monitor CI/CD pipeline status and trigger deployments" ], "health": "active" }, { "id": "perplexity-mcp", "name": "Perplexity MCP", "description": "MCP server for Perplexity's AI-powered search API, providing sourced answers with citations for agent research tasks.", "category": "ai", "endpoint": "mcp-server-perplexity", "homepage_url": "https://perplexity.ai", "github_url": "https://github.com/ppl-ai/modelcontextprotocol", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y mcp-server-perplexity", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "perplexity", "ai-search", "research", "citations", "answers" ], "use_cases": [ "Get sourced answers with citations for complex research questions", "Perform deep web research with AI-synthesized summaries", "Fact-check information with referenced sources" ], "health": "active" }, { "id": "youtube-mcp", "name": "YouTube MCP", "description": "MCP server for YouTube Data API integration, enabling video search, transcript retrieval, and channel data access.", "category": "media", "endpoint": "mcp-server-youtube", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y mcp-server-youtube", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "youtube", "video", "transcripts", "media", "google" ], "use_cases": [ "Search YouTube videos and retrieve metadata for content research", "Extract video transcripts for summarization and analysis", "Access channel statistics and playlist information" ], "health": "active" }, { "id": "atlassian-jira-mcp", "name": "Atlassian Jira MCP", "description": "MCP server for Atlassian Jira Cloud enabling agents to search issues via JQL, manage projects, and track development info.", "category": "productivity", "endpoint": "@aashari/mcp-server-atlassian-jira", "homepage_url": "https://www.atlassian.com/software/jira", "github_url": "https://github.com/aashari/mcp-server-atlassian-jira", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @aashari/mcp-server-atlassian-jira", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "jira", "atlassian", "issues", "project-management", "agile" ], "use_cases": [ "Search and filter Jira issues using JQL from an agent", "Create, update, and transition issues through workflow states", "View development info including linked commits and pull requests" ], "health": "active" }, { "id": "vault-mcp", "name": "HashiCorp Vault MCP", "description": "MCP server for HashiCorp Vault secrets management, providing tools to read, list, and manage secrets from Vault KV stores.", "category": "identity", "endpoint": "mcp-server-vault", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y mcp-server-vault", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "vault", "hashicorp", "secrets", "identity", "security" ], "use_cases": [ "Read secrets from Vault KV stores during agent workflows", "List available secret paths and manage secret lifecycle", "Inject dynamic credentials for infrastructure provisioning" ], "health": "unknown" }, { "id": "aws-documentation-mcp", "name": "AWS Documentation MCP", "description": "Official AWS Labs MCP server for searching and retrieving AWS documentation, best practices, and getting-started guides.", "category": "web", "endpoint": "awslabs.aws-documentation-mcp-server", "homepage_url": "https://awslabs.github.io/mcp/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx awslabs.aws-documentation-mcp-server", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "aws", "documentation", "search", "reference", "official" ], "use_cases": [ "Search AWS documentation for service-specific guidance during development", "Retrieve AWS best practices and architecture recommendations", "Look up API references and getting-started guides for AWS services" ], "health": "active" }, { "id": "redis-mcp", "name": "Redis MCP", "description": "MCP server for Redis. Set, get, and manage keys; use pub/sub channels; run Lua scripts; inspect streams and sorted sets from agent workflows.", "category": "data", "endpoint": "npx -y @modelcontextprotocol/server-redis", "homepage_url": "https://redis.io", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @modelcontextprotocol/server-redis", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "redis", "cache", "pub-sub", "key-value", "streams" ], "use_cases": [ "Read and write Redis keys as a shared state layer between coordinating agents", "Publish and subscribe to Redis channels for event-driven agent communication", "Manage rate-limiting counters and session data during agent-driven API workflows" ], "related_ids": [ "upstash-mcp", "kafka-mcp" ], "health": "active" }, { "id": "mongodb-mcp", "name": "MongoDB MCP", "description": "Official MongoDB Atlas MCP server. Query collections, run aggregations, manage indexes, and interact with Atlas clusters from agent workflows.", "category": "data", "endpoint": "npx -y @modelcontextprotocol/server-mongodb", "homepage_url": "https://mongodb.com", "github_url": "https://github.com/mongodb-labs/mongodb-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @modelcontextprotocol/server-mongodb", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "mongodb", "atlas", "nosql", "database", "aggregation" ], "use_cases": [ "Query and update MongoDB collections from agent reasoning loops", "Run aggregation pipelines to analyze document collections in agent workflows", "Manage Atlas indexes and schemas during automated data engineering tasks" ], "related_ids": [ "supabase-mcp", "neon-mcp" ], "health": "active" }, { "id": "neon-mcp", "name": "Neon MCP", "description": "Official Neon serverless Postgres MCP server. Create branches, run queries, manage databases, and scale Postgres without managing infrastructure.", "category": "data", "endpoint": "npx -y @neondatabase/mcp-server-neon", "homepage_url": "https://neon.tech", "github_url": "https://github.com/neondatabase/mcp-server-neon", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @neondatabase/mcp-server-neon", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "neon", "postgres", "serverless", "database", "branching" ], "use_cases": [ "Spin up instant Postgres branches for safe schema experiments in agent workflows", "Run SQL queries against serverless Postgres with auto-scaling and zero cold starts", "Create and delete short-lived database instances for ephemeral agent tasks" ], "related_ids": [ "supabase-mcp", "planetscale-mcp" ], "health": "active" }, { "id": "datadog-mcp", "name": "Datadog MCP", "description": "MCP server for Datadog. Query metrics, logs, traces, monitors, and dashboards from Datadog's observability platform within agent workflows.", "category": "infrastructure", "endpoint": "npx -y datadog-mcp-server", "homepage_url": "https://datadoghq.com", "github_url": "https://github.com/DataDog/datadog-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y datadog-mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "datadog", "observability", "metrics", "logs", "monitoring", "apm" ], "use_cases": [ "Query Datadog metrics and dashboards from autonomous incident response agents", "Search and analyze application logs across distributed systems in agent workflows", "Trigger and resolve Datadog monitors from AI-driven on-call automation" ], "related_ids": [ "sentry-mcp", "grafana-mcp", "prometheus-mcp" ], "health": "active" }, { "id": "grafana-mcp", "name": "Grafana MCP", "description": "Official Grafana MCP server. Query dashboards, panels, data sources, and alerts from Grafana for AI-driven observability and incident response workflows.", "category": "infrastructure", "endpoint": "npx -y @grafana/mcp-server", "homepage_url": "https://grafana.com", "github_url": "https://github.com/grafana/mcp-grafana", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @grafana/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "grafana", "dashboards", "metrics", "alerts", "observability" ], "use_cases": [ "Query Grafana dashboards and panels for metric data in agent reasoning loops", "List and acknowledge Grafana alerts as part of autonomous incident response", "Fetch time-series data from any Grafana-connected data source for agent analysis" ], "related_ids": [ "datadog-mcp", "prometheus-mcp", "sentry-mcp" ], "health": "active" }, { "id": "pagerduty-mcp", "name": "PagerDuty MCP", "description": "Official PagerDuty MCP server. Manage incidents, services, on-call schedules, and escalation policies. Acknowledge, resolve, and create incidents directly from AI agents.", "category": "infrastructure", "endpoint": "github.com/PagerDuty/pagerduty-mcp-server", "homepage_url": "https://www.pagerduty.com", "github_url": "https://github.com/PagerDuty/pagerduty-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx --from git+https://github.com/PagerDuty/pagerduty-mcp-server pagerduty-mcp-server", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "pagerduty", "incidents", "on-call", "alerting", "monitoring" ], "use_cases": [ "Acknowledge and resolve incidents from AI agent workflows", "Query on-call schedules and escalation policies", "Create incidents programmatically from anomaly detection pipelines" ], "related_ids": [ "datadog-mcp", "grafana-mcp", "sentry-mcp" ], "health": "active" }, { "id": "resend-mcp", "name": "Resend MCP", "description": "Send transactional and marketing emails via Resend from MCP clients. Compose HTML or plain-text emails, manage audiences, and track delivery — no SMTP setup needed.", "category": "communication", "endpoint": "npx resend-mcp", "homepage_url": "https://resend.com", "github_url": "https://github.com/resend/mcp-send-email", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx resend-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "email", "transactional", "resend", "notifications", "communication" ], "use_cases": [ "Send transactional emails from agent-driven workflows", "Deliver notification emails without SMTP configuration", "Compose and send templated messages with dynamic content" ], "related_ids": [ "sendgrid-mcp" ], "health": "active" }, { "id": "sendgrid-mcp", "name": "SendGrid MCP", "description": "Send emails via Twilio SendGrid from MCP clients. Supports transactional messages, dynamic templates, and list management using your SendGrid API key.", "category": "communication", "endpoint": "npx sendgrid-mcp", "homepage_url": "https://sendgrid.com", "github_url": "https://github.com/Garoth/sendgrid-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx sendgrid-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "email", "sendgrid", "transactional", "templates", "communication" ], "use_cases": [ "Send templated transactional emails from agent workflows", "Trigger marketing campaigns via natural language commands", "Manage SendGrid contacts and suppression lists" ], "related_ids": [ "resend-mcp" ], "health": "active" }, { "id": "mapbox-mcp", "name": "Mapbox MCP", "description": "Official Mapbox MCP server. Geocode addresses, reverse-geocode coordinates, get directions, run isochrone analysis, and query Mapbox datasets from AI agents.", "category": "data", "endpoint": "npx @mapbox/mcp-server", "homepage_url": "https://mapbox.com", "github_url": "https://github.com/mapbox/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @mapbox/mcp-server", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "maps", "geocoding", "directions", "geospatial", "location" ], "use_cases": [ "Geocode and reverse-geocode locations in agent pipelines", "Get driving, walking, or cycling directions between points", "Run isochrone analysis to find reachable areas within a time limit" ], "related_ids": [ "google-maps-mcp" ], "health": "active" }, { "id": "semgrep-mcp", "name": "Semgrep MCP", "description": "Run Semgrep static analysis scans from MCP clients. Detect security vulnerabilities, code quality issues, and policy violations across any codebase.", "category": "code", "endpoint": "npx mcp-server-semgrep", "homepage_url": "https://semgrep.dev", "github_url": "https://github.com/semgrep/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mcp-server-semgrep", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "security", "sast", "static-analysis", "vulnerabilities", "code-quality" ], "use_cases": [ "Scan code for security vulnerabilities during AI-assisted development", "Enforce coding policies and detect anti-patterns automatically", "Run SAST scans as part of automated code review pipelines" ], "related_ids": [ "github-mcp", "sentry-mcp" ], "health": "active" }, { "id": "openweather-mcp", "name": "OpenWeather MCP", "description": "Fetch real-time and forecast weather data via the OpenWeatherMap API. Get current conditions, hourly and daily forecasts, and historical weather for any location.", "category": "data", "endpoint": "npx openweather-mcp", "homepage_url": "https://openweathermap.org", "github_url": "https://github.com/erikcarlsson/openweather-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx openweather-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "weather", "forecast", "climate", "location", "data" ], "use_cases": [ "Retrieve current weather conditions for any city or coordinates", "Get 7-day forecasts for logistics and scheduling agents", "Query historical weather data for analysis workflows" ], "related_ids": [ "google-maps-mcp", "mapbox-mcp" ], "health": "active" }, { "id": "cal-mcp", "name": "Cal.com MCP", "description": "Manage scheduling via Cal.com from MCP clients. List event types, create bookings, check availability, and cancel or reschedule appointments programmatically.", "category": "productivity", "endpoint": "npx cal-mcp", "homepage_url": "https://cal.com", "github_url": "https://github.com/calcom/cal.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx cal-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "calendar", "scheduling", "bookings", "availability", "cal.com" ], "use_cases": [ "Check availability and create bookings from agent workflows", "Cancel or reschedule meetings programmatically", "List event types and share booking links in automated emails" ], "related_ids": [ "notion-mcp", "linear-mcp" ], "health": "active" }, { "id": "asana-mcp", "name": "Asana MCP", "description": "Interact with Asana projects and tasks from MCP clients. Create, update, and list tasks, manage projects, assign work, and track progress via natural language.", "category": "productivity", "endpoint": "npx mcp-server-asana", "homepage_url": "https://asana.com", "github_url": "https://github.com/roychri/mcp-server-asana", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @roychri/mcp-server-asana", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "asana", "tasks", "projects", "productivity", "pm" ], "use_cases": [ "Create and assign Asana tasks from agent-driven workflows", "List project tasks and check completion status", "Update task due dates and assignees via natural language" ], "related_ids": [ "linear-mcp", "atlassian-jira-mcp", "notion-mcp" ], "health": "active" }, { "id": "paypal-mcp", "name": "PayPal MCP", "description": "Official PayPal MCP server. Create and capture orders, issue refunds, manage invoices, and query transaction history directly from AI agents using the PayPal API.", "category": "payments", "endpoint": "npx @paypal/mcp", "homepage_url": "https://developer.paypal.com", "github_url": "https://github.com/paypal/agent-toolkit", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @paypal/mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "paypal", "payments", "orders", "invoices", "refunds" ], "use_cases": [ "Create and capture PayPal payment orders from agent workflows", "Issue refunds and query transaction history programmatically", "Generate and send invoices to customers via natural language" ], "related_ids": [ "stripe-agent-toolkit" ], "health": "active" }, { "id": "hubspot-mcp", "name": "HubSpot MCP", "description": "Connect AI agents to HubSpot CRM. Search contacts, companies, and deals. Create and update records, log activities, and query pipelines via natural language.", "category": "data", "endpoint": "npx hubspot-mcp", "homepage_url": "https://www.hubspot.com", "github_url": "https://github.com/peakmojo/mcp-hubspot", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx hubspot-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "hubspot", "crm", "contacts", "deals", "sales" ], "use_cases": [ "Search and update HubSpot contacts and companies from AI agents", "Create deals and move them through pipeline stages", "Log sales activities and notes to CRM records automatically" ], "related_ids": [ "salesforce-mcp" ], "health": "active" }, { "id": "zendesk-mcp", "name": "Zendesk MCP", "description": "MCP server for Zendesk Support. Create and manage tickets, users, and organizations; search articles; run macros from agent-driven customer support workflows.", "category": "productivity", "endpoint": "npx -y zendesk-mcp-server", "homepage_url": "https://zendesk.com", "github_url": "https://github.com/zendesk/zendesk-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y zendesk-mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "zendesk", "support", "tickets", "helpdesk", "customer-service" ], "use_cases": [ "Create and route Zendesk support tickets automatically from agent monitoring workflows", "Search and retrieve Help Center articles for agent-driven customer support bots", "Update ticket statuses and apply macros from AI-powered support escalation pipelines" ], "related_ids": [ "linear-mcp", "jira-mcp" ], "health": "unknown" }, { "id": "figma-mcp", "name": "Figma MCP", "description": "Access Figma design files from MCP clients. Read frames, components, and styles. Extract design tokens, inspect layer properties, and retrieve assets for development.", "category": "productivity", "endpoint": "npx figma-mcp", "homepage_url": "https://www.figma.com", "github_url": "https://github.com/GLips/Figma-Context-MCP", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx figma-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "figma", "design", "components", "tokens", "ui" ], "use_cases": [ "Extract design tokens and styles from Figma files for development", "Read component specifications for AI-assisted UI implementation", "Retrieve assets and frame data to inform code generation" ], "related_ids": [ "cloudinary-mcp" ], "health": "active" }, { "id": "monday-mcp", "name": "Monday.com MCP", "description": "Interact with Monday.com boards and items from MCP clients. Read and update board items, manage columns, create new items, and track project status via natural language.", "category": "productivity", "endpoint": "npx mcp-server-monday", "homepage_url": "https://monday.com", "github_url": "https://github.com/Prat011/mcp-server-monday", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mcp-server-monday", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "monday", "project-management", "boards", "tasks", "productivity" ], "use_cases": [ "Read and update Monday.com board items from agent workflows", "Create new items and set column values programmatically", "Track project status and surface blockers via natural language queries" ], "related_ids": [ "asana-mcp", "linear-mcp", "atlassian-jira-mcp" ], "health": "unknown" }, { "id": "shopify-mcp", "name": "Shopify MCP", "description": "Connect AI agents to Shopify stores. Query products, orders, customers, and inventory. Create draft orders, update product metadata, and run GraphQL queries via MCP.", "category": "data", "endpoint": "npx shopify-mcp", "homepage_url": "https://shopify.com", "github_url": "https://github.com/GeLi2001/shopify-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx shopify-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "shopify", "ecommerce", "products", "orders", "inventory" ], "use_cases": [ "Query Shopify products, inventory, and order status from agents", "Create and update draft orders programmatically", "Run custom GraphQL queries against the Shopify Admin API" ], "related_ids": [ "stripe-agent-toolkit" ], "health": "active" }, { "id": "salesforce-mcp", "name": "Salesforce MCP", "description": "Connect AI agents to Salesforce CRM. Query objects with SOQL, create and update records, manage leads and opportunities, and interact with the Salesforce REST API.", "category": "data", "endpoint": "npx salesforce-mcp", "homepage_url": "https://www.salesforce.com", "github_url": "https://github.com/SuryaSekharSingh/salesforce-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx salesforce-mcp", "added": "2026-04-10", "updated": "2026-04-10", "tags": [ "salesforce", "crm", "soql", "leads", "opportunities" ], "use_cases": [ "Query Salesforce objects with SOQL from agent workflows", "Create and update leads, contacts, and opportunities", "Sync data between Salesforce and other tools via MCP orchestration" ], "related_ids": [ "hubspot-mcp" ], "health": "active" }, { "id": "circleci-mcp", "name": "CircleCI MCP", "description": "Official CircleCI MCP server. Trigger pipelines, check build status, retrieve logs, and orchestrate CI/CD workflows from AI agents.", "category": "code", "endpoint": "npx @circleci/mcp-server-circleci", "homepage_url": "https://circleci.com", "github_url": "https://github.com/CircleCI-Public/mcp-server-circleci", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @circleci/mcp-server-circleci", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "circleci", "ci-cd", "pipelines", "builds", "devops" ], "use_cases": [ "Trigger CI/CD builds and check pipeline status from agent workflows", "Retrieve build logs and diagnose pipeline failures automatically", "Manage CircleCI project configs and approval gates via AI" ], "related_ids": [ "github-mcp", "gitlab-mcp" ], "health": "active" }, { "id": "terraform-mcp", "name": "Terraform MCP", "description": "Official HashiCorp Terraform MCP server. Plan and apply infrastructure changes, manage workspaces, query resource state, and interact with HCP Terraform from AI agents.", "category": "code", "endpoint": "npx @hashicorp/terraform-mcp-server", "homepage_url": "https://www.terraform.io", "github_url": "https://github.com/hashicorp/terraform-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @hashicorp/terraform-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "terraform", "infrastructure", "iac", "hcp", "workspaces" ], "use_cases": [ "Plan and apply Terraform infrastructure changes via AI orchestration", "Query workspace state and resource configurations programmatically", "Manage HCP Terraform organizations, workspaces, and run settings" ], "related_ids": [ "kubernetes-mcp", "aws-api-mcp", "cloudflare-mcp" ], "health": "active" }, { "id": "confluence-mcp", "name": "Confluence MCP", "description": "Read and write Atlassian Confluence pages, spaces, and comments. Search documentation, create runbooks, and keep wikis up to date from agent workflows.", "category": "code", "endpoint": "npx mcp-confluence", "homepage_url": "https://www.atlassian.com/software/confluence", "github_url": "https://github.com/sooperset/mcp-atlassian", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mcp-confluence", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "confluence", "atlassian", "wiki", "documentation", "runbooks" ], "use_cases": [ "Search and retrieve Confluence documentation for agent context", "Auto-generate and publish runbooks and post-mortems to Confluence", "Keep technical wikis in sync with code changes via AI workflows" ], "related_ids": [ "atlassian-jira-mcp", "notion-mcp" ], "health": "active" }, { "id": "nx-mcp", "name": "Nx MCP", "description": "Official Nx MCP server. Query monorepo project graph, run affected targets, and get AI-aware build intelligence for Nx workspaces.", "category": "code", "endpoint": "npx nx-mcp", "homepage_url": "https://nx.dev", "github_url": "https://github.com/nrwl/nx", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx nx-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "nx", "monorepo", "build", "typescript", "workspace" ], "use_cases": [ "Query Nx project graph and understand monorepo dependencies", "Run affected builds and tests based on changed files", "Get intelligent build caching recommendations from AI" ], "related_ids": [ "github-mcp", "circleci-mcp" ], "health": "unknown" }, { "id": "mem0-mcp", "name": "Mem0 MCP", "description": "Persistent memory layer for AI agents. Store, search, and retrieve user preferences, conversation history, and learned facts across sessions. Official Mem0 MCP server.", "category": "ai", "endpoint": "npx @mem0ai/mem0-mcp", "homepage_url": "https://mem0.ai", "github_url": "https://github.com/mem0ai/mem0-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @mem0ai/mem0-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "memory", "persistence", "personalization", "recall", "long-term-memory" ], "use_cases": [ "Give agents persistent memory that survives across conversation sessions", "Store user preferences and retrieve them automatically in future chats", "Build personalized AI assistants with contextual recall" ], "related_ids": [ "memory-mcp", "sequential-thinking-mcp" ], "health": "active" }, { "id": "openai-mcp", "name": "OpenAI MCP", "description": "Access OpenAI models including GPT-4o, o1, DALL-E, and Whisper from MCP-compatible agents. Use OpenAI capabilities as a tool inside any MCP workflow.", "category": "ai", "endpoint": "npx openai-mcp-server", "homepage_url": "https://openai.com", "github_url": "https://github.com/pierrebrunelle/mcp-server-openai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx openai-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "openai", "gpt-4o", "dall-e", "whisper", "llm" ], "use_cases": [ "Call GPT-4o or o1 as a tool inside multi-model agent pipelines", "Generate images with DALL-E or transcribe audio with Whisper via MCP", "Route tasks to the best-fit model within an agent workflow" ], "related_ids": [ "replicate-mcp", "perplexity-mcp" ], "health": "unknown" }, { "id": "groq-mcp", "name": "Groq MCP", "description": "Ultra-fast LLM inference via Groq. Access Llama 3, Mixtral, and Gemma models at speeds up to 800 tokens/sec from any MCP-compatible agent.", "category": "ai", "endpoint": "npx groq-mcp", "homepage_url": "https://groq.com", "github_url": "https://github.com/groq/groq-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx groq-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "groq", "llama", "mixtral", "inference", "fast" ], "use_cases": [ "Run high-throughput inference tasks requiring sub-second response times", "Use open-weight models (Llama 3, Mixtral) as tools in agent pipelines", "Offload latency-sensitive subtasks to Groq from slower orchestrators" ], "related_ids": [ "replicate-mcp", "openai-mcp" ], "health": "unknown" }, { "id": "huggingface-mcp", "name": "HuggingFace MCP", "description": "Access 900,000+ models on HuggingFace Hub. Run inference, search models, retrieve datasets, and interact with Spaces from AI agent workflows.", "category": "ai", "endpoint": "npx @huggingface/mcp-server", "homepage_url": "https://huggingface.co", "github_url": "https://github.com/huggingface/huggingface-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @huggingface/mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "huggingface", "models", "datasets", "transformers", "hub" ], "use_cases": [ "Run inference on any of 900k+ HuggingFace models from an agent", "Search and retrieve model cards, datasets, and evaluation benchmarks", "Trigger and monitor HuggingFace Spaces and Inference Endpoints" ], "related_ids": [ "replicate-mcp", "openai-mcp", "groq-mcp" ], "health": "active" }, { "id": "coinbase-agentkit-mcp", "name": "Coinbase AgentKit MCP", "description": "Official Coinbase AgentKit MCP server. Give AI agents onchain capabilities: create wallets, transfer tokens, deploy contracts, and interact with DeFi protocols on Base and other EVM chains.", "category": "payments", "endpoint": "npx @coinbase/agentkit-mcp", "homepage_url": "https://www.coinbase.com/en-us/developer-platform/products/agentkit", "github_url": "https://github.com/coinbase/agentkit", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @coinbase/agentkit-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "coinbase", "base", "blockchain", "defi", "wallets", "onchain" ], "use_cases": [ "Give agents non-custodial wallets to send and receive crypto autonomously", "Deploy smart contracts and interact with DeFi protocols from AI workflows", "Enable x402 micropayments and onchain agent commerce on Base" ], "related_ids": [ "stripe-agent-toolkit", "paypal-mcp" ], "health": "active" }, { "id": "square-mcp", "name": "Square MCP", "description": "Access Square payment processing, inventory, and point-of-sale data. Process payments, manage catalog items, and query transaction history from AI agents.", "category": "payments", "endpoint": "npx square-mcp-server", "homepage_url": "https://squareup.com", "github_url": "https://github.com/square/square-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx square-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "square", "payments", "pos", "inventory", "transactions" ], "use_cases": [ "Query Square transaction history and payment reports from agent workflows", "Manage product catalog and inventory levels programmatically", "Trigger refunds or payment links via AI-orchestrated customer service" ], "related_ids": [ "stripe-agent-toolkit", "paypal-mcp" ], "health": "unknown" }, { "id": "lemon-squeezy-mcp", "name": "Lemon Squeezy MCP", "description": "Manage SaaS subscriptions, licenses, and digital product sales via Lemon Squeezy. Query orders, activate licenses, and handle subscription lifecycle from agent workflows.", "category": "payments", "endpoint": "npx lemon-squeezy-mcp", "homepage_url": "https://www.lemonsqueezy.com", "github_url": "https://github.com/lemon-squeezy/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx lemon-squeezy-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "lemon-squeezy", "saas", "subscriptions", "licenses", "billing" ], "use_cases": [ "Manage SaaS subscription upgrades, downgrades, and cancellations via AI", "Activate and validate software licenses programmatically", "Query sales data and revenue metrics from Lemon Squeezy stores" ], "related_ids": [ "stripe-agent-toolkit" ], "health": "unknown" }, { "id": "auth0-mcp", "name": "Auth0 MCP", "description": "Official Auth0 MCP server. Manage users, applications, connections, and tenant settings via the Auth0 Management API from agent workflows.", "category": "identity", "endpoint": "npx -y @auth0/mcp-server", "homepage_url": "https://auth0.com", "github_url": "https://github.com/auth0/auth0-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @auth0/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "auth0", "authentication", "users", "identity", "oauth", "management" ], "use_cases": [ "Manage user accounts and roles in Auth0 from automated provisioning agents", "Create and configure Auth0 applications and connections programmatically", "Retrieve and update tenant settings during AI-driven identity workflow automation" ], "related_ids": [ "clerk-mcp", "keycloak-mcp" ], "health": "active" }, { "id": "okta-mcp", "name": "Okta MCP", "description": "Manage Okta identity: users, groups, applications, and policies. Automate enterprise SSO, MFA configuration, and lifecycle management from AI agents.", "category": "identity", "endpoint": "npx okta-mcp-server", "homepage_url": "https://www.okta.com", "github_url": "https://github.com/okta/okta-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx okta-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "okta", "identity", "sso", "enterprise", "lifecycle" ], "use_cases": [ "Automate employee onboarding: provision Okta users and assign app groups", "Query and update MFA policies and authentication factors via AI", "Manage Okta application assignments and SSO configurations" ], "related_ids": [ "auth0-mcp", "1password-mcp", "vault-mcp" ], "health": "unknown" }, { "id": "aws-secrets-mcp", "name": "AWS Secrets Manager MCP", "description": "Retrieve and manage secrets stored in AWS Secrets Manager. Securely fetch API keys, database credentials, and configuration values from agents without hardcoding.", "category": "identity", "endpoint": "npx aws-secrets-mcp", "homepage_url": "https://aws.amazon.com/secrets-manager", "github_url": "https://github.com/aws/aws-secrets-manager-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx aws-secrets-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "aws", "secrets", "credentials", "security", "vault" ], "use_cases": [ "Retrieve API keys and credentials from AWS Secrets Manager at runtime", "Rotate secrets on schedule and update consuming services automatically", "Audit secret access and flag unauthorized retrieval attempts via AI" ], "related_ids": [ "vault-mcp", "1password-mcp", "aws-api-mcp" ], "health": "unknown" }, { "id": "teams-mcp", "name": "Microsoft Teams MCP", "description": "Send messages, manage channels, and interact with Microsoft Teams workspaces from AI agent workflows via the Microsoft Graph API.", "category": "communication", "endpoint": "npx teams-mcp-server", "homepage_url": "https://www.microsoft.com/en-us/microsoft-teams", "github_url": "https://github.com/IndigoMultimediaLtd/teams-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx teams-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "teams", "microsoft", "messaging", "channels", "collaboration" ], "use_cases": [ "Post agent reports and alerts to Microsoft Teams channels", "Search Teams message history for context retrieval", "Manage Teams channels and membership from automated workflows" ], "related_ids": [ "slack-mcp", "discord-mcp" ], "health": "active" }, { "id": "mailchimp-mcp", "name": "Mailchimp MCP", "description": "Manage email marketing campaigns, subscriber lists, and audience segments via Mailchimp from AI agent workflows.", "category": "communication", "endpoint": "npx mailchimp-mcp-server", "homepage_url": "https://mailchimp.com", "github_url": "https://github.com/Garoth/mailchimp-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mailchimp-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "mailchimp", "email-marketing", "campaigns", "subscribers", "lists" ], "use_cases": [ "Create and trigger email campaigns from agent-driven marketing workflows", "Manage subscriber lists and audience segments programmatically", "Query campaign analytics and open/click rates via natural language" ], "related_ids": [ "resend-mcp", "sendgrid-mcp" ], "health": "unknown" }, { "id": "intercom-mcp", "name": "Intercom MCP", "description": "Interact with Intercom customer messaging. Search conversations, create and reply to tickets, manage contacts, and surface customer data for support agents.", "category": "communication", "endpoint": "npx intercom-mcp-server", "homepage_url": "https://www.intercom.com", "github_url": "https://github.com/ravinahp/intercom-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx intercom-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "intercom", "customer-support", "messaging", "conversations", "crm" ], "use_cases": [ "Search and reply to Intercom conversations from AI support agents", "Create contacts and update customer attributes programmatically", "Escalate or tag conversations based on AI-driven classification" ], "related_ids": [ "zendesk-mcp", "slack-mcp" ], "health": "active" }, { "id": "todoist-mcp", "name": "Todoist MCP", "description": "Manage tasks and projects in Todoist. Create, update, complete, and query tasks with filters, priorities, and due dates from AI agent workflows.", "category": "productivity", "endpoint": "npx todoist-mcp-server", "homepage_url": "https://todoist.com", "github_url": "https://github.com/AbdelStark/todoist-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx todoist-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "todoist", "tasks", "productivity", "to-do", "projects" ], "use_cases": [ "Create and assign Todoist tasks from agent-driven workflows", "Query overdue or high-priority tasks for daily planning agents", "Complete tasks and update projects as automation steps conclude" ], "related_ids": [ "linear-mcp", "asana-mcp", "notion-mcp" ], "health": "active" }, { "id": "calendly-mcp", "name": "Calendly MCP", "description": "Access Calendly scheduling data. List event types, retrieve upcoming meetings, cancel events, and share booking links from AI agent workflows.", "category": "productivity", "endpoint": "npx calendly-mcp-server", "homepage_url": "https://calendly.com", "github_url": "https://github.com/ebkr/calendly-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx calendly-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "calendly", "scheduling", "meetings", "bookings", "calendar" ], "use_cases": [ "Retrieve upcoming Calendly meetings for daily briefing agents", "Share booking links in automated outreach and follow-up emails", "Cancel or reschedule events programmatically from agent workflows" ], "related_ids": [ "cal-mcp", "notion-mcp" ], "health": "unknown" }, { "id": "typeform-mcp", "name": "Typeform MCP", "description": "Query Typeform responses and manage forms from AI agents. Retrieve survey results, filter by date, and extract structured data from form submissions.", "category": "productivity", "endpoint": "npx typeform-mcp-server", "homepage_url": "https://www.typeform.com", "github_url": "https://github.com/suyogpardeshi/typeform-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx typeform-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "typeform", "forms", "surveys", "responses", "data-collection" ], "use_cases": [ "Retrieve and analyze Typeform survey responses in agent pipelines", "Filter form submissions by date range or answer value", "Extract structured data from form responses to feed downstream workflows" ], "related_ids": [ "hubspot-mcp", "notion-mcp" ], "health": "unknown" }, { "id": "snowflake-mcp", "name": "Snowflake MCP", "description": "Query Snowflake data warehouse from AI agents. Run SQL, inspect schemas, list tables, and retrieve query results without leaving your agent context.", "category": "data", "endpoint": "npx snowflake-mcp-server", "homepage_url": "https://www.snowflake.com", "github_url": "https://github.com/datawiz-io/snowflake-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx snowflake-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "snowflake", "data-warehouse", "sql", "analytics", "cloud" ], "use_cases": [ "Run SQL queries against Snowflake for analytics and reporting agents", "Inspect table schemas and data lineage for data pipeline orchestration", "Answer natural language questions over enterprise data warehouses" ], "related_ids": [ "postgres-mcp", "supabase-mcp", "mongodb-mcp" ], "health": "active" }, { "id": "elasticsearch-mcp", "name": "Elasticsearch MCP", "description": "Official Elastic MCP server. Search, index, and analyze documents in Elasticsearch and OpenSearch clusters from agent workflows.", "category": "data", "endpoint": "npx -y @elastic/mcp-server-elasticsearch", "homepage_url": "https://elastic.co", "github_url": "https://github.com/elastic/mcp-server-elasticsearch", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @elastic/mcp-server-elasticsearch", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "elasticsearch", "search", "indexing", "analytics", "elastic" ], "use_cases": [ "Run full-text and semantic search queries against Elasticsearch indices from agents", "Index and update documents in Elasticsearch as part of automated data pipelines", "Aggregate and analyze logs and events stored in Elastic clusters" ], "related_ids": [ "algolia-mcp" ], "health": "active" }, { "id": "render-mcp", "name": "Render MCP", "description": "Manage Render cloud deployments from AI agents. Deploy services, check build logs, manage environment variables, and monitor service health.", "category": "infrastructure", "endpoint": "npx render-mcp-server", "homepage_url": "https://render.com", "github_url": "https://github.com/briefercloud/render-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx render-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "render", "deployment", "hosting", "cloud", "devops" ], "use_cases": [ "Deploy and redeploy Render services from agent-driven CI/CD pipelines", "Retrieve build logs and diagnose deployment failures automatically", "Manage environment variables and service configurations via AI" ], "related_ids": [ "vercel-mcp", "cloudflare-mcp", "kubernetes-mcp" ], "health": "unknown" }, { "id": "algolia-mcp", "name": "Algolia MCP", "description": "Official Algolia MCP server. Search and manage indices, records, and rules across Algolia's hosted search platform from agent workflows.", "category": "data", "endpoint": "npx -y @algolia/mcp-server-node", "homepage_url": "https://algolia.com", "github_url": "https://github.com/algolia/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @algolia/mcp-server-node", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "algolia", "search", "indexing", "faceting", "e-commerce" ], "use_cases": [ "Search Algolia indices for products or content from within agent reasoning loops", "Add, update, or delete Algolia records as part of content pipeline automation", "Configure search rules and facets for e-commerce agent workflows" ], "related_ids": [ "elasticsearch-mcp" ], "health": "active" }, { "id": "contentful-mcp", "name": "Contentful MCP", "description": "Read and write content in Contentful CMS. Query entries, update fields, publish content, and manage assets from AI agent workflows.", "category": "web", "endpoint": "npx contentful-mcp-server", "homepage_url": "https://www.contentful.com", "github_url": "https://github.com/ivo-toby/contentful-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx contentful-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "contentful", "cms", "content", "headless", "publishing" ], "use_cases": [ "Fetch and update Contentful entries for headless CMS-driven workflows", "Publish and unpublish content programmatically as part of release pipelines", "Manage media assets and link them to entries via agent commands" ], "related_ids": [ "notion-mcp", "gdrive-mcp" ], "health": "active" }, { "id": "sanity-mcp", "name": "Sanity MCP", "description": "Interact with Sanity Studio datasets. Query documents with GROQ, create and update content, and manage assets in Sanity-powered projects from AI agents.", "category": "web", "endpoint": "npx @sanity-io/mcp-server", "homepage_url": "https://www.sanity.io", "github_url": "https://github.com/sanity-io/sanity-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @sanity-io/mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "sanity", "cms", "groq", "content", "headless" ], "use_cases": [ "Query Sanity datasets with GROQ from AI-assisted content workflows", "Create and update structured content documents programmatically", "Manage Sanity project assets and schemas via agent commands" ], "related_ids": [ "contentful-mcp", "notion-mcp" ], "health": "active" }, { "id": "bitbucket-mcp", "name": "Bitbucket MCP", "description": "Manage Bitbucket repositories, pull requests, and pipelines from AI agents. Create PRs, review diffs, trigger builds, and query repository data.", "category": "code", "endpoint": "npx bitbucket-mcp-server", "homepage_url": "https://bitbucket.org", "github_url": "https://github.com/aashari/mcp-server-atlassian-bitbucket", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @aashari/mcp-server-atlassian-bitbucket", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "bitbucket", "git", "atlassian", "pull-requests", "ci-cd" ], "use_cases": [ "Create and review Bitbucket pull requests from AI coding agents", "Trigger Bitbucket Pipelines and monitor build status", "Query repository history and branch information programmatically" ], "related_ids": [ "github-mcp", "gitlab-mcp", "atlassian-jira-mcp" ], "health": "active" }, { "id": "cohere-mcp", "name": "Cohere MCP", "description": "Access Cohere Command and Embed models from AI agents. Generate text, create embeddings, rerank search results, and build RAG pipelines via Cohere API.", "category": "ai", "endpoint": "npx cohere-mcp-server", "homepage_url": "https://cohere.com", "github_url": "https://github.com/cohere-ai/cohere-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx cohere-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "cohere", "embeddings", "reranking", "rag", "command" ], "use_cases": [ "Generate high-quality embeddings for vector search and RAG pipelines", "Rerank search results to improve retrieval relevance in agent workflows", "Use Cohere Command models as a tool within multi-model agent systems" ], "related_ids": [ "qdrant-mcp", "elasticsearch-mcp", "openai-mcp" ], "health": "active" }, { "id": "mistral-mcp", "name": "Mistral MCP", "description": "Access Mistral AI models including Mistral Large, Codestral, and Pixtral from MCP-compatible agents for text generation, code completion, and vision tasks.", "category": "ai", "endpoint": "npx mistral-mcp-server", "homepage_url": "https://mistral.ai", "github_url": "https://github.com/runekaagaard/mcp-mistral", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mistral-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "mistral", "llm", "codestral", "pixtral", "open-weights" ], "use_cases": [ "Use Mistral Large or Nemo as a reasoning tool inside agent pipelines", "Code completion and review with Codestral in development workflows", "Run vision tasks with Pixtral for multimodal agent applications" ], "related_ids": [ "openai-mcp", "groq-mcp", "huggingface-mcp" ], "health": "unknown" }, { "id": "anthropic-mcp", "name": "Anthropic Claude MCP", "description": "Call Anthropic Claude models as tools within MCP-compatible agent workflows. Access Claude 3.5 Sonnet, Haiku, and Opus for text generation, analysis, and reasoning.", "category": "ai", "endpoint": "npx anthropic-mcp-server", "homepage_url": "https://www.anthropic.com", "github_url": "https://github.com/dougmercer-yt/mcp-anthropic", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx anthropic-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "anthropic", "claude", "llm", "reasoning", "sonnet" ], "use_cases": [ "Use Claude models as tool calls inside multi-agent orchestration pipelines", "Delegate complex reasoning subtasks to Claude from other agent frameworks", "Run structured document analysis with Claude's 200k context window" ], "related_ids": [ "openai-mcp", "groq-mcp", "mistral-mcp" ], "health": "unknown" }, { "id": "airtable-mcp", "name": "Airtable MCP", "description": "Read and write Airtable bases from AI agents. Query records, create and update rows, manage tables, and build agent workflows on top of your Airtable data.", "category": "data", "endpoint": "npx airtable-mcp-server", "homepage_url": "https://airtable.com", "github_url": "https://github.com/domdomegg/airtable-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx airtable-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "airtable", "database", "spreadsheet", "records", "no-code" ], "use_cases": [ "Query and update Airtable records from automated agent workflows", "Use Airtable as a lightweight CRM or project tracker for AI pipelines", "Create new records and trigger Airtable automations from agent actions" ], "related_ids": [ "notion-mcp", "hubspot-mcp", "monday-mcp" ], "health": "active" }, { "id": "pinecone-mcp", "name": "Pinecone MCP", "description": "Query and manage Pinecone vector indices from AI agents. Upsert embeddings, run similarity search, filter by metadata, and manage namespaces for RAG pipelines.", "category": "data", "endpoint": "npx pinecone-mcp-server", "homepage_url": "https://www.pinecone.io", "github_url": "https://github.com/sirmews/mcp-pinecone", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx pinecone-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "pinecone", "vector-search", "embeddings", "rag", "semantic-search" ], "use_cases": [ "Upsert and query vector embeddings in Pinecone for semantic search", "Build RAG pipelines with Pinecone as the long-term knowledge store", "Manage vector namespaces and metadata filters from agent workflows" ], "related_ids": [ "qdrant-mcp", "elasticsearch-mcp", "cohere-mcp" ], "health": "active" }, { "id": "gmail-mcp", "name": "Gmail MCP", "description": "Read, search, and send Gmail messages from AI agents. Access inbox threads, compose emails, manage labels, and retrieve attachments via the Gmail API.", "category": "communication", "endpoint": "npx gmail-mcp-server", "homepage_url": "https://mail.google.com", "github_url": "https://github.com/vincentkoc/mcp-gmail", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx gmail-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "gmail", "email", "google", "inbox", "messaging" ], "use_cases": [ "Search and read Gmail threads for context retrieval in agent workflows", "Compose and send emails from AI-driven communication pipelines", "Manage labels and organize inbox as part of automated triage workflows" ], "related_ids": [ "resend-mcp", "sendgrid-mcp", "slack-mcp" ], "health": "active" }, { "id": "trello-mcp", "name": "Trello MCP", "description": "Manage Trello boards, lists, and cards from AI agents. Create cards, move them across lists, assign members, and query board state for lightweight project tracking.", "category": "productivity", "endpoint": "npx trello-mcp-server", "homepage_url": "https://trello.com", "github_url": "https://github.com/mirovar/trello-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx trello-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "trello", "kanban", "cards", "boards", "project-management" ], "use_cases": [ "Create and move Trello cards from agent-driven task management workflows", "Query board and list state to generate progress summaries via AI", "Assign members and add checklists to Trello cards programmatically" ], "related_ids": [ "asana-mcp", "monday-mcp", "linear-mcp" ], "health": "unknown" }, { "id": "elevenlabs-mcp", "name": "ElevenLabs MCP", "description": "Official ElevenLabs MCP server. Generate natural-sounding speech, clone voices, and produce multilingual audio from AI agents using state-of-the-art TTS.", "category": "media", "endpoint": "npx @elevenlabs/mcp", "homepage_url": "https://elevenlabs.io", "github_url": "https://github.com/elevenlabs/elevenlabs-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @elevenlabs/mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "elevenlabs", "tts", "voice", "audio", "speech-synthesis" ], "use_cases": [ "Convert agent-generated text to natural speech for voice interfaces", "Clone a voice and produce branded audio content programmatically", "Generate multilingual narration for videos, podcasts, and interactive apps" ], "related_ids": [ "cloudinary-mcp", "youtube-mcp" ], "health": "active" }, { "id": "fal-ai-mcp", "name": "fal.ai MCP", "description": "Run image generation, video synthesis, and computer vision models at scale via fal.ai. Fast async inference for Flux, SDXL, Stable Video Diffusion, and more.", "category": "media", "endpoint": "npx @fal-ai/mcp", "homepage_url": "https://fal.ai", "github_url": "https://github.com/fal-ai/fal-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @fal-ai/mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "fal", "image-generation", "flux", "sdxl", "video", "diffusion" ], "use_cases": [ "Generate high-quality images with Flux or SDXL in agent pipelines", "Run video synthesis and style transfer at scale with async queuing", "Combine image generation with computer vision for content workflows" ], "related_ids": [ "replicate-mcp", "cloudinary-mcp", "stability-ai-mcp" ], "health": "active" }, { "id": "stability-ai-mcp", "name": "Stability AI MCP", "description": "Generate, edit, and upscale images using Stability AI models including Stable Diffusion 3 and Stable Image Ultra. Control generation with precise prompts and style parameters.", "category": "media", "endpoint": "npx stability-ai-mcp", "homepage_url": "https://stability.ai", "github_url": "https://github.com/stability-ai/stability-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx stability-ai-mcp", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "stability-ai", "stable-diffusion", "image-generation", "upscale", "inpainting" ], "use_cases": [ "Generate product images, concepts, and marketing visuals via AI agents", "Upscale and enhance images programmatically within content pipelines", "Run inpainting and outpainting for automated image editing workflows" ], "related_ids": [ "fal-ai-mcp", "replicate-mcp", "cloudinary-mcp" ], "health": "unknown" }, { "id": "deepgram-mcp", "name": "Deepgram MCP", "description": "Real-time and batch speech-to-text transcription via Deepgram Nova-2. Transcribe audio files, detect speakers, and extract keywords from voice recordings in agent workflows.", "category": "media", "endpoint": "npx deepgram-mcp-server", "homepage_url": "https://deepgram.com", "github_url": "https://github.com/deepgram/deepgram-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx deepgram-mcp-server", "added": "2026-04-11", "updated": "2026-04-11", "tags": [ "deepgram", "stt", "transcription", "speech", "audio" ], "use_cases": [ "Transcribe meeting recordings and extract action items via AI pipelines", "Real-time voice-to-text for conversational agent interfaces", "Diarize speaker turns and generate structured transcripts from audio" ], "related_ids": [ "elevenlabs-mcp", "youtube-mcp" ], "health": "unknown" }, { "id": "paddle-mcp", "name": "Paddle MCP", "description": "Manage Paddle billing, subscriptions, and checkout for SaaS products. Handle subscription lifecycle, trials, pauses, cancellations, and revenue reporting programmatically.", "category": "payments", "endpoint": "npx paddle-mcp-server", "homepage_url": "https://paddle.com", "github_url": "https://github.com/paddlehq/paddle-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx paddle-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "paddle", "billing", "subscriptions", "saas", "payments" ], "use_cases": [ "Automate subscription lifecycle management for SaaS products in agent workflows", "Generate revenue reports and churn analysis via AI-driven analytics pipelines", "Handle trial-to-paid conversions and dunning logic with agent orchestration" ], "related_ids": [ "stripe-agent-toolkit", "lemon-squeezy-mcp" ], "health": "unknown" }, { "id": "adyen-mcp", "name": "Adyen MCP", "description": "Process enterprise payments globally with Adyen. Handle card payments, local payment methods, refunds, disputes, and advanced fraud prevention across 200+ countries.", "category": "payments", "endpoint": "npx adyen-mcp-server", "homepage_url": "https://adyen.com", "github_url": "https://github.com/adyen/adyen-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx adyen-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "adyen", "enterprise-payments", "global-payments", "fraud", "card-processing" ], "use_cases": [ "Process cross-border payments with local method support in agent-driven e-commerce", "Automate dispute resolution and chargeback management workflows", "Implement real-time fraud scoring and transaction decisioning via AI agents" ], "related_ids": [ "stripe-agent-toolkit", "paypal-mcp", "braintree-mcp" ], "health": "unknown" }, { "id": "braintree-mcp", "name": "Braintree MCP", "description": "Full-stack payment platform by PayPal. Process cards, PayPal, Venmo, and digital wallets with advanced fraud protection, vaulting, and subscription management.", "category": "payments", "endpoint": "npx braintree-mcp-server", "homepage_url": "https://braintreepayments.com", "github_url": "https://github.com/braintree/braintree-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx braintree-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "braintree", "paypal", "venmo", "card-vaulting", "subscriptions" ], "use_cases": [ "Vault payment methods and trigger charges in automated billing pipelines", "Process PayPal and Venmo transactions alongside card payments in unified checkout", "Build subscription and usage-based billing logic with agent orchestration" ], "related_ids": [ "paypal-mcp", "stripe-agent-toolkit" ], "health": "unknown" }, { "id": "razorpay-mcp", "name": "Razorpay MCP", "description": "India-first payment gateway supporting UPI, cards, net banking, wallets, and international cards. Handle orders, refunds, payouts, and subscription billing for South Asian markets.", "category": "payments", "endpoint": "npx razorpay-mcp-server", "homepage_url": "https://razorpay.com", "github_url": "https://github.com/razorpay/razorpay-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx razorpay-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "razorpay", "upi", "india", "payments", "net-banking" ], "use_cases": [ "Process UPI and Indian payment methods in agent-driven commerce workflows", "Automate payout disbursements to vendors and contractors in India", "Manage subscription billing and EMI plans for Indian SaaS products" ], "related_ids": [ "stripe-agent-toolkit", "paypal-mcp" ], "health": "unknown" }, { "id": "clerk-mcp", "name": "Clerk MCP", "description": "Modern authentication and user management for web apps. Manage users, sessions, organizations, roles, and permissions via Clerk's complete auth platform.", "category": "identity", "endpoint": "npx clerk-mcp-server", "homepage_url": "https://clerk.com", "github_url": "https://github.com/clerk/clerk-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx clerk-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "clerk", "auth", "user-management", "sessions", "organizations" ], "use_cases": [ "Automate user provisioning, deprovisioning, and role assignment in multi-tenant apps", "Query user session data and audit authentication events in security workflows", "Manage organization membership and permissions via agent-driven admin operations" ], "related_ids": [ "auth0-mcp", "okta-mcp" ], "health": "unknown" }, { "id": "keycloak-mcp", "name": "Keycloak MCP", "description": "Open-source identity and access management. Manage realms, clients, users, roles, and groups in self-hosted or cloud Keycloak deployments. Full SSO and federation support.", "category": "identity", "endpoint": "npx keycloak-mcp-server", "homepage_url": "https://keycloak.org", "github_url": "https://github.com/keycloak/keycloak-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx keycloak-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "keycloak", "sso", "iam", "oauth", "open-source" ], "use_cases": [ "Automate Keycloak realm configuration and client registration in DevOps pipelines", "Manage user federation and identity provider sync via agent-driven operations", "Audit role assignments and policy changes across Keycloak instances" ], "related_ids": [ "auth0-mcp", "vault-mcp", "okta-mcp" ], "health": "unknown" }, { "id": "supertokens-mcp", "name": "SuperTokens MCP", "description": "Open-source authentication with self-hosting option. Handle email/password, social login, passwordless, and MFA flows. Manage users, sessions, and roles programmatically.", "category": "identity", "endpoint": "npx supertokens-mcp-server", "homepage_url": "https://supertokens.com", "github_url": "https://github.com/supertokens/supertokens-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx supertokens-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "supertokens", "auth", "self-hosted", "sessions", "mfa" ], "use_cases": [ "Manage user accounts and session state in self-hosted auth deployments", "Automate MFA enrollment and recovery flows in agent-driven security workflows", "Migrate users between auth providers with zero-downtime agent orchestration" ], "related_ids": [ "auth0-mcp", "clerk-mcp" ], "health": "unknown" }, { "id": "pexels-mcp", "name": "Pexels MCP", "description": "Search and retrieve high-quality free stock photos and videos from Pexels. Access millions of curated images and clips for content pipelines, marketing, and media production.", "category": "media", "endpoint": "npx pexels-mcp-server", "homepage_url": "https://pexels.com", "github_url": "https://github.com/pexels/pexels-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx pexels-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "pexels", "stock-photos", "stock-video", "free", "media" ], "use_cases": [ "Source royalty-free images for automated content and marketing pipelines", "Retrieve stock video clips for AI-driven video production workflows", "Find contextually relevant visuals for blog posts and social content at scale" ], "related_ids": [ "unsplash-mcp", "cloudinary-mcp" ], "health": "unknown" }, { "id": "spotify-mcp", "name": "Spotify MCP", "description": "Access Spotify's music catalog, playlists, listening history, and recommendations. Search tracks, albums, and artists. Control playback and manage user playlists via the Spotify Web API.", "category": "media", "endpoint": "npx spotify-mcp-server", "homepage_url": "https://developer.spotify.com", "github_url": "https://github.com/spotify/spotify-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx spotify-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "spotify", "music", "playlists", "audio", "streaming" ], "use_cases": [ "Build AI-driven playlist generators from mood or activity context", "Analyze listening history for personalized music recommendation agents", "Automate playlist curation and track discovery for content creators" ], "related_ids": [ "elevenlabs-mcp", "youtube-mcp" ], "health": "unknown" }, { "id": "assemblyai-mcp", "name": "AssemblyAI MCP", "description": "Enterprise-grade speech intelligence. Transcribe audio and video with speaker diarization, sentiment analysis, topic detection, PII redaction, and auto chapters. Best-in-class accuracy.", "category": "media", "endpoint": "npx assemblyai-mcp-server", "homepage_url": "https://assemblyai.com", "github_url": "https://github.com/AssemblyAI/assemblyai-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx assemblyai-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "assemblyai", "transcription", "stt", "speaker-diarization", "sentiment" ], "use_cases": [ "Transcribe and analyze meeting recordings with speaker labels and action items", "Extract topic summaries and sentiment from podcast and call center audio at scale", "Redact PII from call recordings automatically in compliance workflows" ], "related_ids": [ "deepgram-mcp", "elevenlabs-mcp" ], "health": "active" }, { "id": "whisper-mcp", "name": "OpenAI Whisper MCP", "description": "Transcribe audio to text using OpenAI Whisper. Supports 99 languages, translation to English, and timestamp generation. Run locally or via OpenAI API for production transcription.", "category": "media", "endpoint": "npx openai-whisper-mcp", "homepage_url": "https://openai.com/research/whisper", "github_url": "https://github.com/openai/whisper-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx openai-whisper-mcp", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "whisper", "transcription", "stt", "multilingual", "openai" ], "use_cases": [ "Transcribe multilingual audio content for global content localization pipelines", "Generate timestamped transcripts for video captioning and subtitle workflows", "Translate non-English audio to English in real-time agent workflows" ], "related_ids": [ "deepgram-mcp", "assemblyai-mcp" ], "health": "active" }, { "id": "gcp-mcp", "name": "Google Cloud MCP", "description": "Manage Google Cloud Platform resources: Compute Engine, Cloud Storage, BigQuery, Cloud Run, GKE, and IAM. Deploy, monitor, and scale infrastructure via the GCP API.", "category": "infrastructure", "endpoint": "npx gcp-mcp-server", "homepage_url": "https://cloud.google.com", "github_url": "https://github.com/googleapis/gcp-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx gcp-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "gcp", "google-cloud", "bigquery", "cloud-run", "gke" ], "use_cases": [ "Provision and scale Cloud Run services and GKE clusters in AI-driven DevOps pipelines", "Query BigQuery datasets and export results in agent-driven analytics workflows", "Manage IAM permissions and service accounts programmatically via agent orchestration" ], "related_ids": [ "aws-api-mcp", "azure-mcp", "kubernetes-mcp" ], "health": "unknown" }, { "id": "azure-mcp", "name": "Azure MCP", "description": "Manage Microsoft Azure resources: VMs, App Services, Blob Storage, Azure OpenAI, AKS, and more. Deploy and operate cloud workloads via the Azure Resource Manager API.", "category": "infrastructure", "endpoint": "npx azure-mcp-server", "homepage_url": "https://azure.microsoft.com", "github_url": "https://github.com/microsoft/azure-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx azure-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "azure", "microsoft", "cloud", "aks", "azure-openai" ], "use_cases": [ "Deploy and manage Azure App Services and AKS clusters in CI/CD agent pipelines", "Query Azure Monitor logs and metrics for AI-driven incident response", "Manage Azure OpenAI deployments and quota via agent-driven operations" ], "related_ids": [ "aws-api-mcp", "gcp-mcp", "kubernetes-mcp" ], "health": "active" }, { "id": "pulumi-mcp", "name": "Pulumi MCP", "description": "Infrastructure as Code using general-purpose programming languages. Deploy and manage cloud resources across AWS, Azure, GCP, and Kubernetes via Pulumi's API and state management.", "category": "infrastructure", "endpoint": "npx pulumi-mcp-server", "homepage_url": "https://pulumi.com", "github_url": "https://github.com/pulumi/pulumi-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx pulumi-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "pulumi", "iac", "infrastructure-as-code", "cloud", "devops" ], "use_cases": [ "Preview and deploy infrastructure changes via AI-driven GitOps pipelines", "Query Pulumi stack state and outputs for downstream agent orchestration", "Automate drift detection and remediation across multi-cloud deployments" ], "related_ids": [ "terraform-mcp", "aws-api-mcp", "kubernetes-mcp" ], "health": "unknown" }, { "id": "sonarqube-mcp", "name": "SonarQube MCP", "description": "Continuous code quality and security analysis. Query issues, security hotspots, technical debt, coverage metrics, and quality gate status across projects and branches.", "category": "code", "endpoint": "npx sonarqube-mcp-server", "homepage_url": "https://sonarqube.org", "github_url": "https://github.com/SonarSource/sonarqube-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx sonarqube-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "sonarqube", "code-quality", "sast", "security", "technical-debt" ], "use_cases": [ "Surface code quality issues and security hotspots in AI-assisted code review", "Query quality gate status before merging PRs in agent-driven CI/CD workflows", "Track technical debt trends and prioritize remediation via agent analysis" ], "related_ids": [ "sentry-mcp", "semgrep-mcp", "github-mcp" ], "health": "unknown" }, { "id": "codecov-mcp", "name": "Codecov MCP", "description": "Track code coverage across commits, PRs, and branches. Identify uncovered lines, coverage trends, and component coverage. Integrate coverage data into CI/CD and code review workflows.", "category": "code", "endpoint": "npx codecov-mcp-server", "homepage_url": "https://codecov.io", "github_url": "https://github.com/codecov/codecov-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx codecov-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "codecov", "coverage", "testing", "ci", "code-quality" ], "use_cases": [ "Query PR coverage diffs and flag regressions in agent-driven code review", "Track coverage trends across repos for AI-assisted quality reporting", "Identify high-value test gaps by correlating coverage with bug frequency" ], "related_ids": [ "sonarqube-mcp", "github-mcp", "circleci-mcp" ], "health": "unknown" }, { "id": "whatsapp-mcp", "name": "WhatsApp Business MCP", "description": "Send and receive messages via WhatsApp Business API. Handle templates, media messages, interactive buttons, and message status tracking for business communication at scale.", "category": "communication", "endpoint": "npx whatsapp-business-mcp", "homepage_url": "https://business.whatsapp.com", "github_url": "https://github.com/whatsapp/whatsapp-business-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx whatsapp-business-mcp", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "whatsapp", "messaging", "business", "templates", "notifications" ], "use_cases": [ "Send transactional WhatsApp notifications from agent-driven order and logistics workflows", "Build AI customer support bots using WhatsApp Business messaging", "Automate template message campaigns for appointment reminders and alerts" ], "related_ids": [ "twilio-mcp", "slack-mcp" ], "health": "unknown" }, { "id": "telegram-mcp", "name": "Telegram Bot MCP", "description": "Build and operate Telegram bots via the Bot API. Send messages, manage groups, handle commands, inline queries, and webhooks. Supports media, polls, and rich UI elements.", "category": "communication", "endpoint": "npx telegram-bot-mcp", "homepage_url": "https://core.telegram.org/bots/api", "github_url": "https://github.com/telegram-mcp/telegram-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx telegram-bot-mcp", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "telegram", "bot", "messaging", "notifications", "webhooks" ], "use_cases": [ "Send agent task updates and alerts to Telegram channels from automated pipelines", "Build AI-powered Telegram bots for customer support and information retrieval", "Trigger agent workflows from Telegram commands and inline queries" ], "related_ids": [ "slack-mcp", "discord-mcp", "whatsapp-mcp" ], "health": "active" }, { "id": "apify-mcp", "name": "Apify MCP", "description": "Run web scraping and automation Actors from the Apify platform. Access a library of 3,000+ ready-made scrapers for social media, e-commerce, search engines, and more.", "category": "web", "endpoint": "npx apify-mcp-server", "homepage_url": "https://apify.com", "github_url": "https://github.com/apify/actors-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx apify-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "apify", "scraping", "automation", "actors", "web-crawling" ], "use_cases": [ "Run pre-built scrapers for LinkedIn, Amazon, Instagram, and Google in agent pipelines", "Extract structured e-commerce and pricing data at scale via Apify Actors", "Automate web monitoring and change detection in agent-driven workflows" ], "related_ids": [ "firecrawl-mcp", "playwright-mcp", "browserbase-mcp" ], "health": "active" }, { "id": "browserbase-mcp", "name": "Browserbase MCP", "description": "Cloud browser infrastructure for AI agents. Run headless Chromium at scale with session management, stealth mode, CAPTCHA handling, and streaming. Purpose-built for agent web automation.", "category": "web", "endpoint": "npx browserbase-mcp-server", "homepage_url": "https://browserbase.com", "github_url": "https://github.com/browserbase/mcp-server-browserbase", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx browserbase-mcp-server", "added": "2026-04-12", "updated": "2026-04-12", "tags": [ "browserbase", "cloud-browser", "headless", "agents", "automation" ], "use_cases": [ "Run persistent browser sessions for multi-step agent web automation tasks", "Handle CAPTCHAs and bot-detection transparently in AI agent web workflows", "Stream live browser state to agent reasoning loops for interactive automation" ], "related_ids": [ "playwright-mcp", "firecrawl-mcp", "apify-mcp" ], "health": "active" }, { "id": "upstash-mcp", "name": "Upstash MCP", "description": "Serverless Redis and Kafka over HTTP from Upstash. MCP server for key-value caching, message queuing, and vector storage — zero connection management.", "category": "data", "endpoint": "npx -y @upstash/mcp-server", "homepage_url": "https://upstash.com", "github_url": "https://github.com/upstash/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @upstash/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "upstash", "redis", "kafka", "serverless", "vector", "cache" ], "use_cases": [ "Use serverless Redis for agent state and session caching without managing connections", "Produce and consume Kafka messages from agent workflows over HTTP", "Store and query vector embeddings via Upstash Vector for RAG pipelines" ], "related_ids": [ "redis-mcp", "kafka-mcp" ], "health": "active" }, { "id": "prometheus-mcp", "name": "Prometheus MCP", "description": "MCP server for Prometheus metrics. Run PromQL queries, inspect targets, and retrieve time-series metric data for AI-driven infrastructure monitoring.", "category": "infrastructure", "endpoint": "npx -y prometheus-mcp-server", "homepage_url": "https://prometheus.io", "github_url": "https://github.com/pab1it0/prometheus-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y prometheus-mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "prometheus", "metrics", "promql", "monitoring", "time-series" ], "use_cases": [ "Execute PromQL queries to retrieve infrastructure metrics from agent workflows", "Monitor service health and latency metrics for autonomous incident detection", "Inspect scrape targets and alert rules during AI-driven ops automation" ], "related_ids": [ "grafana-mcp", "datadog-mcp" ], "health": "active" }, { "id": "jira-mcp", "name": "Jira MCP", "description": "MCP server for Atlassian Jira. Create, read, update, and transition issues; manage projects and sprints; run JQL queries from agent workflows.", "category": "productivity", "endpoint": "npx -y @atlassian/jira-mcp", "homepage_url": "https://atlassian.com/software/jira", "github_url": "https://github.com/atlassian/jira-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @atlassian/jira-mcp", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "jira", "issues", "project-management", "atlassian", "sprints", "jql" ], "use_cases": [ "Create and update Jira tickets automatically from agent-driven incident response", "Run JQL queries to fetch issue sets for automated reporting and triage", "Transition issue statuses and manage sprint backlogs from agent pipelines" ], "related_ids": [ "linear-mcp", "github-mcp" ], "health": "active" }, { "id": "planetscale-mcp", "name": "PlanetScale MCP", "description": "MCP server for PlanetScale serverless MySQL. Query databases, inspect schemas, manage branches, and run deploy requests from agent workflows.", "category": "data", "endpoint": "npx -y @planetscale/mcp-server", "homepage_url": "https://planetscale.com", "github_url": "https://github.com/planetscale/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @planetscale/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "planetscale", "mysql", "serverless", "database", "branching" ], "use_cases": [ "Query PlanetScale MySQL databases from agent workflows without connection limits", "Create and merge database branches for safe schema changes in automated pipelines", "Inspect table schemas and run migrations from agent-driven data engineering tasks" ], "related_ids": [ "supabase-mcp", "neon-mcp" ], "health": "unknown" }, { "id": "kafka-mcp", "name": "Kafka MCP", "description": "MCP server for Apache Kafka. Produce and consume messages, manage topics and consumer groups, and inspect cluster metadata from agent workflows.", "category": "data", "endpoint": "npx -y kafka-mcp-server", "homepage_url": "https://kafka.apache.org", "github_url": "https://github.com/confluentinc/kafka-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y kafka-mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "kafka", "messaging", "event-streaming", "pub-sub", "confluent" ], "use_cases": [ "Produce events to Kafka topics from agent-driven data pipeline triggers", "Consume and process Kafka messages in event-driven agent workflows", "Inspect topic offsets and consumer group lag for autonomous pipeline monitoring" ], "related_ids": [ "upstash-mcp", "redis-mcp" ], "health": "unknown" }, { "id": "opentelemetry-mcp", "name": "OpenTelemetry MCP", "description": "MCP server for OpenTelemetry. Query traces, metrics, and logs from OTEL-compatible backends (Jaeger, Zipkin, OTLP) for AI-driven observability workflows.", "category": "infrastructure", "endpoint": "npx -y otel-mcp-server", "homepage_url": "https://opentelemetry.io", "github_url": "https://github.com/open-telemetry/otel-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y otel-mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "opentelemetry", "otel", "traces", "spans", "observability", "distributed-tracing" ], "use_cases": [ "Query distributed traces and spans from agent-driven debugging and root-cause analysis", "Correlate metrics, logs, and traces across services in autonomous incident response", "Inspect OTEL service maps and dependency graphs for AI-powered performance analysis" ], "related_ids": [ "prometheus-mcp", "grafana-mcp", "datadog-mcp" ], "health": "unknown" }, { "id": "bigquery-mcp", "name": "BigQuery MCP", "description": "Google BigQuery access via MCP. Run SQL queries, manage datasets and tables, and analyze large-scale structured data directly from agents.", "category": "data", "endpoint": "npx @modelcontextprotocol/server-bigquery", "homepage_url": "https://cloud.google.com/bigquery", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @modelcontextprotocol/server-bigquery", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "bigquery", "google", "sql", "analytics", "data-warehouse" ], "use_cases": [ "Run analytical SQL queries across petabyte-scale datasets", "Export query results to downstream agents or pipelines", "Manage BigQuery datasets and table schemas programmatically" ], "health": "active" }, { "id": "clickhouse-mcp", "name": "ClickHouse MCP", "description": "ClickHouse OLAP database access via MCP. Execute fast analytical queries against columnar data for real-time analytics and reporting.", "category": "data", "endpoint": "npx @clickhouse/mcp-server", "homepage_url": "https://clickhouse.com", "github_url": "https://github.com/ClickHouse/mcp-clickhouse", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @clickhouse/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "clickhouse", "olap", "analytics", "columnar", "real-time" ], "use_cases": [ "Query time-series and event data at sub-second latency", "Build real-time analytics dashboards powered by agents", "Aggregate log and metric data for observability workflows" ], "health": "active" }, { "id": "turso-mcp", "name": "Turso MCP", "description": "Turso edge SQLite database access via MCP. Query, update, and manage Turso databases — SQLite at global scale with per-tenant isolation.", "category": "data", "endpoint": "npx @turso/mcp-server", "homepage_url": "https://turso.tech", "github_url": "https://github.com/tursodatabase/mcp-server-turso", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @turso/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "turso", "sqlite", "edge", "database", "multi-tenant" ], "use_cases": [ "Read and write to edge SQLite databases from agents", "Manage per-user or per-tenant database instances", "Build lightweight agent memory stores on SQLite" ], "health": "active" }, { "id": "fly-io-mcp", "name": "Fly.io MCP", "description": "Fly.io infrastructure management via MCP. Deploy apps, manage machines, inspect logs, and scale services globally from agents.", "category": "infrastructure", "endpoint": "npx @fly-apps/mcp-server", "homepage_url": "https://fly.io", "github_url": "https://github.com/fly-apps/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @fly-apps/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "fly.io", "deployment", "infrastructure", "machines", "scaling" ], "use_cases": [ "Deploy and scale containerized apps from agent workflows", "Inspect app health, logs, and machine status remotely", "Automate blue/green deployments and rollbacks" ], "health": "active" }, { "id": "netlify-mcp", "name": "Netlify MCP", "description": "Netlify deployment and site management via MCP. Trigger deploys, manage environment variables, inspect build logs, and control DNS from agents.", "category": "infrastructure", "endpoint": "npx @netlify/mcp-server", "homepage_url": "https://netlify.com", "github_url": "https://github.com/netlify/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @netlify/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "netlify", "deployment", "hosting", "jamstack", "serverless" ], "use_cases": [ "Trigger site deploys and inspect build status from agents", "Manage environment variables and deploy contexts", "Monitor site analytics and form submissions" ], "health": "active" }, { "id": "railway-mcp", "name": "Railway MCP", "description": "Railway infrastructure management via MCP. Deploy services, manage environment variables, inspect deployments, and scale projects from agents.", "category": "infrastructure", "endpoint": "npx @railway/mcp-server", "homepage_url": "https://railway.app", "github_url": "https://github.com/railwayapp/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @railway/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "railway", "deployment", "infrastructure", "postgres", "hosting" ], "use_cases": [ "Deploy and manage Railway services from agent workflows", "Inspect deployment logs and service health", "Manage environment variables and private networking" ], "health": "active" }, { "id": "together-ai-mcp", "name": "Together AI MCP", "description": "Together AI inference API via MCP. Run open-source LLMs — Llama, Mistral, DBRX, and more — with fast parallel inference at scale.", "category": "ai", "endpoint": "npx @togetherai/mcp-server", "homepage_url": "https://together.ai", "github_url": "https://github.com/togethercomputer/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @togetherai/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "together-ai", "llm", "inference", "open-source", "llama" ], "use_cases": [ "Run Llama, Mistral, or DBRX inference in agent pipelines", "Fine-tune open-source models on custom datasets", "Parallel batch inference for high-throughput workflows" ], "health": "active" }, { "id": "ollama-mcp", "name": "Ollama MCP", "description": "Local LLM inference via Ollama. Run Llama, Mistral, Gemma, and other models locally — no API keys, no data leaving the machine.", "category": "ai", "endpoint": "npx ollama-mcp", "homepage_url": "https://ollama.com", "github_url": "https://github.com/ollama/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx ollama-mcp", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "ollama", "local-llm", "privacy", "llama", "open-source" ], "use_cases": [ "Run LLMs locally without sending data to external APIs", "Prototype agent workflows using open-source models", "Switch between models for cost vs quality tradeoffs" ], "health": "active" }, { "id": "langsmith-mcp", "name": "LangSmith MCP", "description": "LangSmith LLM observability via MCP. Trace agent runs, inspect prompts and outputs, evaluate quality, and debug complex chain failures.", "category": "ai", "endpoint": "npx @langchain/langsmith-mcp", "homepage_url": "https://smith.langchain.com", "github_url": "https://github.com/langchain-ai/langsmith-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @langchain/langsmith-mcp", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "langsmith", "observability", "tracing", "evaluation", "llm-ops" ], "use_cases": [ "Trace multi-step agent runs end-to-end for debugging", "Evaluate prompt quality and output accuracy at scale", "Monitor LLM cost, latency, and failure rates in production" ], "health": "active" }, { "id": "weights-biases-mcp", "name": "Weights & Biases MCP", "description": "Weights & Biases ML experiment tracking via MCP. Log runs, compare metrics, manage model artifacts, and query training history from agents.", "category": "ai", "endpoint": "npx @wandb/mcp-server", "homepage_url": "https://wandb.ai", "github_url": "https://github.com/wandb/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @wandb/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "wandb", "mlops", "experiment-tracking", "model-registry", "evaluation" ], "use_cases": [ "Log and compare ML training runs from agent pipelines", "Query model performance metrics and artifacts", "Track dataset versions and lineage across experiments" ], "health": "active" }, { "id": "plaid-mcp", "name": "Plaid MCP", "description": "Plaid financial data API via MCP. Access bank accounts, transactions, balances, and income verification for fintech agent workflows.", "category": "payments", "endpoint": "npx @plaid/mcp-server", "homepage_url": "https://plaid.com", "github_url": "https://github.com/plaid/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @plaid/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "plaid", "banking", "transactions", "fintech", "income" ], "use_cases": [ "Retrieve transaction history for financial analysis agents", "Verify account balances before executing payments", "Income and identity verification for onboarding workflows" ], "health": "active" }, { "id": "chargebee-mcp", "name": "Chargebee MCP", "description": "Chargebee subscription billing via MCP. Manage subscriptions, invoices, customers, and revenue metrics from agent workflows.", "category": "payments", "endpoint": "npx @chargebee/mcp-server", "homepage_url": "https://chargebee.com", "github_url": "https://github.com/chargebee/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @chargebee/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "chargebee", "subscriptions", "billing", "revenue", "saas" ], "use_cases": [ "Create, update, or cancel subscriptions from agent workflows", "Query MRR, churn, and revenue metrics for reporting", "Automate dunning and invoice management" ], "health": "active" }, { "id": "workos-mcp", "name": "WorkOS MCP", "description": "WorkOS enterprise SSO and directory sync via MCP. Manage organizations, users, SSO connections, and SCIM provisioning for B2B SaaS agents.", "category": "identity", "endpoint": "npx @workos/mcp-server", "homepage_url": "https://workos.com", "github_url": "https://github.com/workos/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @workos/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "workos", "sso", "saml", "scim", "enterprise-auth" ], "use_cases": [ "Provision and deprovision users via SCIM from agent automation", "Query SSO connections and organization directory data", "Automate user onboarding flows for enterprise customers" ], "health": "active" }, { "id": "clickup-mcp", "name": "ClickUp MCP", "description": "ClickUp project management via MCP. Create tasks, manage spaces, update statuses, and query workload from agents.", "category": "productivity", "endpoint": "npx @clickup/mcp-server", "homepage_url": "https://clickup.com", "github_url": "https://github.com/clickup/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @clickup/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "clickup", "project-management", "tasks", "productivity", "workflow" ], "use_cases": [ "Create and assign tasks from agent-driven workflows", "Update task status and priority based on external triggers", "Query team workload and sprint progress for reporting" ], "health": "active" }, { "id": "miro-mcp", "name": "Miro MCP", "description": "Miro visual collaboration via MCP. Create boards, add stickies and shapes, update diagrams, and export content from agents.", "category": "productivity", "endpoint": "npx @miro/mcp-server", "homepage_url": "https://miro.com", "github_url": "https://github.com/miroapp/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @miro/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "miro", "whiteboard", "diagram", "collaboration", "visual" ], "use_cases": [ "Generate diagrams and flowcharts on Miro boards from agents", "Add research synthesis to shared visual workspaces", "Update architectural diagrams from code-analysis pipelines" ], "health": "active" }, { "id": "coda-mcp", "name": "Coda MCP", "description": "Coda docs and tables via MCP. Read, create, and update Coda pages and rows — combining doc and database in a single workspace.", "category": "productivity", "endpoint": "npx @coda/mcp-server", "homepage_url": "https://coda.io", "github_url": "https://github.com/codahq/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @coda/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "coda", "docs", "tables", "automation", "productivity" ], "use_cases": [ "Read and update Coda table rows from agent automations", "Generate structured documents with dynamic content", "Use Coda as an agent-accessible knowledge and task base" ], "health": "active" }, { "id": "loom-mcp", "name": "Loom MCP", "description": "Loom video messaging via MCP. Access video library, retrieve transcripts, manage spaces, and search recordings from agents.", "category": "communication", "endpoint": "npx @loom/mcp-server", "homepage_url": "https://loom.com", "github_url": "https://github.com/loom/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @loom/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "loom", "video", "transcripts", "async-communication", "recording" ], "use_cases": [ "Retrieve Loom video transcripts for summarization agents", "Search recordings by keyword or speaker across workspaces", "Organize and tag recordings based on content analysis" ], "health": "active" }, { "id": "mux-mcp", "name": "Mux MCP", "description": "Mux video infrastructure via MCP. Upload, transcode, and stream video at scale — plus analytics, thumbnails, and live streaming from agents.", "category": "media", "endpoint": "npx @mux/mcp-server", "homepage_url": "https://mux.com", "github_url": "https://github.com/muxinc/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @mux/mcp-server", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "mux", "video", "streaming", "transcoding", "media" ], "use_cases": [ "Upload and transcode video assets from agent pipelines", "Retrieve playback URLs and thumbnail assets for content agents", "Query video analytics and engagement metrics" ], "health": "active" }, { "id": "puppeteer-mcp", "name": "Puppeteer MCP", "description": "Puppeteer browser automation via MCP. Navigate pages, click, fill forms, take screenshots, and extract content using headless Chrome.", "category": "web", "endpoint": "npx @modelcontextprotocol/server-puppeteer", "homepage_url": "https://pptr.dev", "github_url": "https://github.com/modelcontextprotocol/servers", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @modelcontextprotocol/server-puppeteer", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "puppeteer", "browser", "automation", "scraping", "headless-chrome" ], "use_cases": [ "Automate form fills and UI flows with headless Chrome", "Take full-page screenshots for visual regression testing", "Scrape JavaScript-rendered content from dynamic sites" ], "health": "active" }, { "id": "stagehand-mcp", "name": "Stagehand MCP", "description": "Stagehand AI-native browser automation via MCP. Natural language browser control — act, extract, observe — powered by Browserbase infrastructure.", "category": "web", "endpoint": "npx @browserbase/stagehand-mcp", "homepage_url": "https://stagehand.dev", "github_url": "https://github.com/browserbase/stagehand", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @browserbase/stagehand-mcp", "added": "2026-04-13", "updated": "2026-04-13", "tags": [ "stagehand", "browser", "ai-automation", "natural-language", "browserbase" ], "use_cases": [ "Control browsers with natural language instructions from agents", "Extract structured data from web pages without writing selectors", "Automate complex multi-step web workflows for AI pipelines" ], "health": "active" }, { "id": "posthog-mcp", "name": "PostHog MCP", "description": "Official PostHog MCP server. Query product analytics, funnels, session replays, feature flags, and experiments from AI agents.", "category": "data", "endpoint": "npx @posthog/mcp-server", "homepage_url": "https://posthog.com", "github_url": "https://github.com/PostHog/posthog", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @posthog/wizard@latest mcp add", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "analytics", "product-analytics", "funnels", "session-replay", "feature-flags" ], "use_cases": [ "Query product analytics events and user behavior from AI tools", "Analyze funnels, retention, and session replays via natural language", "Manage feature flags and experiments from your IDE" ], "health": "active" }, { "id": "chroma-mcp", "name": "Chroma MCP", "description": "MCP server for Chroma vector database. Manage collections, add documents, run vector search, full-text search, and metadata filtering.", "category": "data", "endpoint": "uvx chroma-mcp", "homepage_url": "https://www.trychroma.com", "github_url": "https://github.com/chroma-core/chroma-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx chroma-mcp", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "vector-database", "embeddings", "search", "rag", "semantic-search" ], "use_cases": [ "Store and query embeddings for RAG pipelines from AI agents", "Manage vector collections and run semantic search", "Build retrieval-augmented generation workflows" ], "related_ids": [ "pinecone-mcp", "qdrant-mcp", "weaviate-mcp" ], "health": "active" }, { "id": "weaviate-mcp", "name": "Weaviate MCP", "description": "Official MCP server for Weaviate vector database. Insert objects and run hybrid search queries against Weaviate instances.", "category": "data", "endpoint": "weaviate-mcp-server", "homepage_url": "https://weaviate.io", "github_url": "https://github.com/weaviate/mcp-server-weaviate", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "vector-database", "hybrid-search", "embeddings", "semantic-search" ], "use_cases": [ "Insert and query objects in Weaviate from AI agents", "Run hybrid vector + keyword search over knowledge bases", "Build agentic retrieval pipelines with Weaviate" ], "related_ids": [ "pinecone-mcp", "qdrant-mcp", "chroma-mcp" ], "health": "active" }, { "id": "motherduck-mcp", "name": "MotherDuck MCP", "description": "Local MCP server for DuckDB and MotherDuck. Run SQL analytics over local files, in-memory data, S3, and MotherDuck cloud databases.", "category": "data", "endpoint": "uvx mcp-server-motherduck", "homepage_url": "https://motherduck.com", "github_url": "https://github.com/motherduckdb/mcp-server-motherduck", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx mcp-server-motherduck --db-path :memory:", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "duckdb", "sql", "analytics", "data-warehouse", "olap" ], "use_cases": [ "Run SQL analytics over CSV, Parquet, and JSON files from agents", "Query MotherDuck cloud data warehouses via natural language", "Perform ad-hoc data analysis without setting up infrastructure" ], "related_ids": [ "bigquery-mcp", "snowflake-mcp" ], "health": "active" }, { "id": "excalidraw-mcp", "name": "Excalidraw MCP", "description": "Official Excalidraw MCP App. Stream hand-drawn diagrams with viewport control and interactive fullscreen editing inside MCP-compatible clients.", "category": "media", "endpoint": "https://mcp.excalidraw.com", "homepage_url": "https://excalidraw.com", "github_url": "https://github.com/excalidraw/excalidraw-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "diagrams", "whiteboard", "drawing", "visualization", "mcp-app" ], "use_cases": [ "Generate hand-drawn style diagrams from AI conversations", "Create architecture and flow diagrams interactively", "Render visual explanations directly inside Claude or ChatGPT" ], "health": "active" }, { "id": "loki-mcp", "name": "Grafana Loki MCP", "description": "Official Grafana MCP server for Loki log querying. Execute LogQL queries against Loki instances with time range and multi-tenant support.", "category": "infrastructure", "endpoint": "loki-mcp-server", "homepage_url": "https://grafana.com/oss/loki/", "github_url": "https://github.com/grafana/loki-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "logging", "loki", "logql", "observability", "grafana" ], "use_cases": [ "Query application logs via LogQL from AI coding assistants", "Debug production issues by searching Loki logs naturally", "Correlate log data across multi-tenant Grafana stacks" ], "related_ids": [ "grafana-mcp" ], "health": "active" }, { "id": "axiom-mcp", "name": "Axiom MCP", "description": "Official Axiom MCP server. Query logs, traces, and event data using APL. List, create, and inspect datasets with full schema visibility.", "category": "infrastructure", "endpoint": "https://mcp.axiom.co", "homepage_url": "https://axiom.co", "github_url": "https://github.com/axiomhq/mcp-server-axiom", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "observability", "logging", "traces", "apl", "analytics" ], "use_cases": [ "Query observability data with APL from AI agents", "Analyze logs, traces, and metrics using natural language", "Manage Axiom datasets and explore schemas from your IDE" ], "health": "active" }, { "id": "portainer-mcp", "name": "Portainer MCP", "description": "Official Portainer MCP server. Manage Docker and Kubernetes environments, stacks, users, and teams through AI assistants with 40+ tools.", "category": "infrastructure", "endpoint": "portainer-mcp", "homepage_url": "https://portainer.io", "github_url": "https://github.com/portainer/portainer-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "containers", "docker", "kubernetes", "devops", "infrastructure" ], "use_cases": [ "Manage Docker containers and stacks from AI assistants", "Deploy and monitor Kubernetes workloads via natural language", "Administer Portainer environments, users, and access controls" ], "related_ids": [ "docker-mcp", "kubernetes-mcp" ], "health": "active" }, { "id": "argocd-mcp", "name": "ArgoCD MCP", "description": "MCP server for Argo CD. List, create, sync, and manage GitOps applications and resources. View logs and run resource actions.", "category": "infrastructure", "endpoint": "npx argocd-mcp@latest stdio", "homepage_url": "https://argoproj.github.io/cd/", "github_url": "https://github.com/argoproj-labs/mcp-for-argocd", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx argocd-mcp@latest stdio", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "gitops", "argocd", "kubernetes", "cd", "deployments" ], "use_cases": [ "Sync and manage ArgoCD applications from AI coding tools", "View deployment status and resource trees via natural language", "Trigger GitOps deployments and inspect workload logs" ], "related_ids": [ "kubernetes-mcp" ], "health": "active" }, { "id": "prisma-mcp", "name": "Prisma MCP", "description": "Official Prisma MCP server. Manage Prisma Postgres databases, model schemas, run migrations, and spin up new database instances from AI tools.", "category": "data", "endpoint": "npx prisma mcp", "homepage_url": "https://prisma.io", "github_url": "https://github.com/prisma/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx prisma mcp", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "orm", "database", "postgres", "schema", "migrations" ], "use_cases": [ "Manage Prisma Postgres databases from AI assistants", "Model database schemas and run migrations via natural language", "Spin up new database instances for development and testing" ], "related_ids": [ "postgres-mcp", "supabase-mcp" ], "health": "active" }, { "id": "snyk-mcp", "name": "Snyk MCP", "description": "MCP server for Snyk security scanning. Scan repositories for vulnerabilities, verify tokens, and manage security across multiple organizations.", "category": "code", "endpoint": "npx -y github:sammcj/mcp-snyk", "homepage_url": "https://snyk.io", "github_url": "https://github.com/sammcj/mcp-snyk", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y github:sammcj/mcp-snyk", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "security", "vulnerability-scanning", "sca", "devsecops", "snyk" ], "use_cases": [ "Scan repos for security vulnerabilities from AI coding tools", "Check dependency security posture during code review", "Integrate security scanning into agentic development workflows" ], "related_ids": [ "semgrep-mcp", "sonarqube-mcp" ], "health": "active" }, { "id": "mixpanel-mcp", "name": "Mixpanel MCP", "description": "MCP server for Mixpanel analytics. Query events, funnels, and retention data. Talk to your product analytics from any MCP client.", "category": "data", "endpoint": "npx @smithery/cli run @dragonkhoi/mixpanel-mcp", "homepage_url": "https://mixpanel.com", "github_url": "https://github.com/dragonkhoi/mixpanel-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "analytics", "product-analytics", "events", "funnels", "retention" ], "use_cases": [ "Query Mixpanel event data from Claude or Cursor", "Analyze user funnels and retention via natural language", "Build product analytics reports from AI assistants" ], "related_ids": [ "posthog-mcp", "amplitude-mcp" ], "health": "active" }, { "id": "amplitude-mcp", "name": "Amplitude MCP", "description": "MCP server for Amplitude Analytics API. Query events with filters and date ranges, segment data across dimensions.", "category": "data", "endpoint": "npx -y amplitude-mcp", "homepage_url": "https://amplitude.com", "github_url": "https://github.com/silviorodrigues/amplitude-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y amplitude-mcp --amplitude-api-key=KEY --amplitude-secret-key=SECRET", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "analytics", "product-analytics", "events", "segmentation", "amplitude" ], "use_cases": [ "Query and segment Amplitude event data from AI tools", "Run event analytics with property filters and time grouping", "Build data-driven product insights via natural language" ], "related_ids": [ "posthog-mcp", "mixpanel-mcp" ], "health": "active" }, { "id": "backstage-mcp", "name": "Backstage MCP", "description": "MCP server wrapping the Backstage Catalog API. Browse, filter, and create entities in your Backstage developer portal from AI assistants.", "category": "infrastructure", "endpoint": "http://localhost:8080", "homepage_url": "https://backstage.io", "github_url": "https://github.com/p7ayfu77/backstage-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "developer-portal", "service-catalog", "backstage", "platform-engineering" ], "use_cases": [ "Browse and search Backstage service catalog from AI agents", "Query entities by kind, namespace, or labels via natural language", "Create new entities in the Backstage catalog programmatically" ], "health": "active" }, { "id": "salesforce-mcp", "name": "Salesforce MCP", "description": "Official Salesforce CLI MCP server. Interact with Salesforce orgs — query data, manage records, deploy metadata — from AI assistants.", "category": "data", "endpoint": "npx @salesforce/cli mcp", "homepage_url": "https://salesforce.com", "github_url": "https://github.com/salesforcecli/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @salesforce/cli mcp", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "crm", "salesforce", "soql", "enterprise", "data-management" ], "use_cases": [ "Query Salesforce data using SOQL from AI coding tools", "Manage Salesforce records and metadata via natural language", "Deploy and retrieve Salesforce metadata from AI assistants" ], "related_ids": [ "hubspot-mcp" ], "health": "active" }, { "id": "openapi-mcp", "name": "OpenAPI MCP", "description": "AWS Labs MCP server that dynamically generates tools from OpenAPI specs. Let LLMs interact with any REST API via its OpenAPI definition.", "category": "code", "endpoint": "uvx awslabs.openapi-mcp-server", "homepage_url": "https://awslabs.github.io/mcp/servers/openapi-mcp-server", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "openapi", "swagger", "api", "rest", "code-generation" ], "use_cases": [ "Turn any OpenAPI spec into callable MCP tools for agents", "Let AI agents interact with REST APIs via their documentation", "Generate API client code and test calls from specifications" ], "health": "active" }, { "id": "workers-mcp", "name": "Cloudflare Workers MCP", "description": "Talk to any Cloudflare Worker from MCP clients. Bridge between MCP protocol and Worker endpoints for serverless tool hosting.", "category": "infrastructure", "endpoint": "npx workers-mcp", "homepage_url": "https://developers.cloudflare.com/agents/", "github_url": "https://github.com/cloudflare/workers-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx workers-mcp", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "cloudflare", "workers", "serverless", "edge", "deployment" ], "use_cases": [ "Connect AI assistants to custom Cloudflare Workers", "Host MCP tools as serverless Worker functions on the edge", "Bridge MCP protocol with existing Worker-based APIs" ], "related_ids": [ "cloudflare-mcp" ], "health": "active" }, { "id": "swagger-mcp", "name": "Swagger MCP", "description": "MCP server for exploring and testing APIs through Swagger/OpenAPI docs. Browse endpoints, view schemas, and execute test requests.", "category": "code", "endpoint": "npx swagger-mcp", "homepage_url": "https://swagger.io", "github_url": "https://github.com/amrsa1/swagger-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "swagger", "api-testing", "openapi", "documentation", "developer-tools" ], "use_cases": [ "Explore API endpoints and schemas from AI coding tools", "Test API calls against Swagger documentation via natural language", "Generate test requests from OpenAPI specs inside your IDE" ], "related_ids": [ "openapi-mcp" ], "health": "active" }, { "id": "valkey-mcp", "name": "Valkey MCP", "description": "AWS Labs MCP server for Amazon ElastiCache Valkey datastores. Operate on Valkey data types — strings, hashes, lists, sets, sorted sets, and streams.", "category": "data", "endpoint": "uvx awslabs.valkey-mcp-server", "homepage_url": "https://valkey.io", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "valkey", "redis", "cache", "key-value", "elasticache" ], "use_cases": [ "Manage Valkey/Redis data structures from AI agents", "Inspect and modify cache entries via natural language", "Operate on ElastiCache Valkey instances from coding tools" ], "related_ids": [ "redis-mcp", "upstash-mcp" ], "health": "active" }, { "id": "snyk-agent-scan", "name": "Snyk Agent Scan", "description": "Security scanner for AI agents, MCP servers, and agent skills. Scan and inspect the supply chain of agent components on your machine.", "category": "code", "endpoint": "npx snyk-agent-scan", "homepage_url": "https://snyk.io", "github_url": "https://github.com/snyk/agent-scan", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx snyk-agent-scan", "added": "2026-04-20", "updated": "2026-04-20", "tags": [ "security", "agent-security", "supply-chain", "scanning", "mcp-security" ], "use_cases": [ "Scan MCP servers and agent skills for security vulnerabilities", "Audit the supply chain of AI agent components", "Detect malicious or compromised MCP server dependencies" ], "related_ids": [ "snyk-mcp", "semgrep-mcp" ], "health": "active" }, { "id": "langfuse-mcp", "name": "Langfuse MCP", "description": "Official MCP server for Langfuse LLM observability. Access and manage prompts, traces, and datasets through the Model Context Protocol.", "category": "ai", "endpoint": "npx mcp-server-langfuse", "homepage_url": "https://langfuse.com", "github_url": "https://github.com/langfuse/mcp-server-langfuse", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx mcp-server-langfuse", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "observability", "llm", "tracing", "prompts", "eval" ], "use_cases": [ "Manage and version prompts from your IDE via AI agents", "Query LLM traces and debug production issues", "Pull datasets for evaluation workflows" ], "related_ids": [ "langsmith-mcp", "opentelemetry-mcp" ], "health": "active" }, { "id": "opik-mcp", "name": "Opik MCP", "description": "MCP server for Comet Opik, providing unified access to LLM prompts, projects, traces, and evaluation metrics from your IDE.", "category": "ai", "endpoint": "npx @comet-ml/opik-mcp", "homepage_url": "https://www.comet.com/site/products/opik/", "github_url": "https://github.com/comet-ml/opik-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "observability", "llm", "eval", "tracing", "experiments" ], "use_cases": [ "Query LLM traces and cost metrics from your editor", "Manage prompt versions and run evaluations", "Analyze experiment results without leaving your IDE" ], "related_ids": [ "langfuse-mcp", "weights-biases-mcp" ], "health": "active" }, { "id": "arize-phoenix-mcp", "name": "Arize Phoenix MCP", "description": "MCP server for Arize Phoenix AI observability. Explore projects, traces, spans, prompts, datasets, and experiments via the Model Context Protocol.", "category": "ai", "endpoint": "npx @arizeai/phoenix-mcp", "homepage_url": "https://arize.com/phoenix", "github_url": "https://github.com/Arize-ai/phoenix", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @arizeai/phoenix-mcp", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "observability", "tracing", "evaluation", "opentelemetry", "llm" ], "use_cases": [ "Explore LLM traces and spans for debugging", "Manage prompts and run evaluations from AI agents", "Pull experiment results and dataset examples" ], "related_ids": [ "langfuse-mcp", "opik-mcp" ], "health": "active" }, { "id": "confident-ai-mcp", "name": "Confident AI MCP", "description": "Official MCP server for Confident AI and DeepEval. Run LLM evaluations, manage prompt templates, pull datasets, and trigger cloud evals from your editor.", "category": "ai", "endpoint": "npx confident-mcp-server", "homepage_url": "https://deepeval.com", "github_url": "https://github.com/confident-ai/confident-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "evaluation", "llm", "testing", "prompts", "deepeval" ], "use_cases": [ "Run LLM evaluations with DeepEval metrics from your IDE", "Manage and version prompt templates", "Pull evaluation datasets for local test runs" ], "related_ids": [ "opik-mcp", "langfuse-mcp" ], "health": "active" }, { "id": "braintrust-mcp", "name": "Braintrust MCP", "description": "MCP server for Braintrust AI evaluation and observability. Access experiments, datasets, scoring functions, and production logs for LLM quality management.", "category": "ai", "endpoint": "npx braintrust-mcp", "homepage_url": "https://www.braintrust.dev", "github_url": "https://github.com/braintrustdata/braintrust-sdk", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "evaluation", "observability", "experiments", "scoring", "llm-ops" ], "use_cases": [ "Run and review AI evaluation experiments from your IDE", "Access scoring functions and quality metrics", "Query production LLM logs for debugging and analysis" ], "related_ids": [ "langfuse-mcp", "opik-mcp" ], "health": "active" }, { "id": "mcp-llm-eval", "name": "MCP LLM Eval", "description": "Local MCP server that packages LLM evaluation gates as reusable CI/CD primitives. Run datasets against models, score with LLM-as-judge, enforce quality thresholds.", "category": "ai", "endpoint": "uvx mcp-llm-eval", "homepage_url": "https://pypi.org/project/mcp-llm-eval/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "evaluation", "llm", "ci-cd", "quality-gates", "testing" ], "use_cases": [ "Enforce LLM output quality thresholds in CI/CD pipelines", "Run eval datasets against multiple models and compare", "Use LLM-as-judge scoring for automated quality checks" ], "related_ids": [ "confident-ai-mcp", "opik-mcp" ], "health": "active" }, { "id": "mcp-eval", "name": "MCP Eval", "description": "Evaluation framework for testing MCP servers and agents end-to-end. Exercises your full system with real LLM-to-tool calls and OpenTelemetry-backed observability.", "category": "code", "endpoint": "npx @lastmile-ai/mcp-eval", "homepage_url": "https://github.com/lastmile-ai/mcp-eval", "github_url": "https://github.com/lastmile-ai/mcp-eval", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "testing", "evaluation", "mcp", "opentelemetry", "ci-cd" ], "use_cases": [ "Test MCP server implementations end-to-end with real agents", "Run rich assertion suites with CI/CD integration", "Monitor MCP server health with OpenTelemetry tracing" ], "related_ids": [ "mcp-evals", "mcp-llm-eval" ], "health": "active" }, { "id": "mcp-evals", "name": "MCP Evals", "description": "Node.js package and GitHub Action for evaluating MCP tool implementations using LLM-based scoring. Validate your MCP server tools are working correctly.", "category": "code", "endpoint": "npx mcp-evals", "homepage_url": "https://github.com/mclenhard/mcp-evals", "github_url": "https://github.com/mclenhard/mcp-evals", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "testing", "github-actions", "evaluation", "mcp", "ci-cd" ], "use_cases": [ "Evaluate MCP tool implementations in CI via GitHub Actions", "Score MCP server responses using LLM-based grading", "Automate MCP server quality checks on every PR" ], "related_ids": [ "mcp-eval", "mcp-llm-eval" ], "health": "active" }, { "id": "mcp-bench", "name": "MCP Bench", "description": "Benchmarking framework by Accenture for evaluating LLM tool-use via MCP. End-to-end pipeline assessing how effectively models discover, select, and use tools.", "category": "ai", "endpoint": "python -m mcp_bench", "homepage_url": "https://github.com/Accenture/mcp-bench", "github_url": "https://github.com/Accenture/mcp-bench", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "benchmarking", "evaluation", "tool-use", "llm", "research" ], "use_cases": [ "Benchmark LLM tool-use capabilities across models", "Evaluate tool discovery and selection accuracy", "Compare model performance on complex real-world MCP tasks" ], "related_ids": [ "mcp-eval", "confident-ai-mcp" ], "health": "active" }, { "id": "promptfoo-mcp", "name": "Promptfoo MCP", "description": "MCP server exposing Promptfoo eval and red-team testing tools to AI agents. Run prompt evaluations, security tests, and quality checks from your IDE.", "category": "ai", "endpoint": "npx promptfoo@latest mcp", "homepage_url": "https://www.promptfoo.dev", "github_url": "https://github.com/promptfoo/promptfoo", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx promptfoo@latest mcp --transport stdio", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "evaluation", "red-team", "security", "prompts", "testing" ], "use_cases": [ "Run prompt evaluations across models from your editor", "Red-team test LLM applications for vulnerabilities", "Automate prompt quality checks in development workflows" ], "related_ids": [ "mcp-llm-eval", "confident-ai-mcp" ], "health": "active" }, { "id": "dbt-mcp", "name": "dbt MCP", "description": "Official MCP server by dbt Labs. Connect AI agents with governed access to dbt models, sources, tests, and documentation. Available as local and remote server.", "category": "data", "endpoint": "uvx dbt-mcp", "homepage_url": "https://www.getdbt.com", "github_url": "https://github.com/dbt-labs/dbt-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "dbt", "data-modeling", "analytics", "sql", "data-engineering" ], "use_cases": [ "Query dbt model metadata and documentation from AI agents", "Explore data lineage and test results", "Generate and validate SQL against dbt project context" ], "related_ids": [ "snowflake-mcp", "bigquery-mcp" ], "health": "active" }, { "id": "databricks-mcp", "name": "Databricks MCP", "description": "MCP server for Databricks Unity Catalog. Enables AI agents to discover catalogs, schemas, and tables, analyze lineage, and execute SQL queries.", "category": "data", "endpoint": "uvx databricks-mcp-server", "homepage_url": "https://www.databricks.com", "github_url": "https://github.com/RafaelCartenet/mcp-databricks-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "databricks", "unity-catalog", "sql", "data-lakehouse", "spark" ], "use_cases": [ "Discover and explore Databricks Unity Catalog metadata", "Execute SQL queries against Databricks warehouses", "Analyze data lineage across catalogs and schemas" ], "related_ids": [ "snowflake-mcp", "bigquery-mcp" ], "health": "active" }, { "id": "buildkite-mcp", "name": "Buildkite MCP", "description": "Official MCP server for Buildkite CI/CD. Access pipeline details, build information, job logs, artifacts, and user data for monitoring and troubleshooting.", "category": "code", "endpoint": "npx @buildkite/buildkite-mcp-server", "homepage_url": "https://buildkite.com", "github_url": "https://github.com/buildkite/buildkite-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "ci-cd", "pipelines", "builds", "devops", "automation" ], "use_cases": [ "Monitor CI/CD pipeline status and build results", "Retrieve job logs and artifacts for debugging", "Query build history and pipeline configurations" ], "related_ids": [ "circleci-mcp", "github-mcp" ], "health": "active" }, { "id": "tekton-mcp", "name": "Tekton MCP", "description": "MCP server for Tekton Pipelines on Kubernetes. Start, monitor, and manage cloud-native CI/CD pipelines through natural language commands.", "category": "code", "endpoint": "npx tekton-mcp-server", "homepage_url": "https://tekton.dev", "github_url": "https://github.com/openshift-pipelines/tekton-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "ci-cd", "kubernetes", "pipelines", "cloud-native", "devops" ], "use_cases": [ "Trigger and monitor Tekton pipelines from AI agents", "Inspect pipeline run status and task logs", "Manage CI/CD workflows on Kubernetes clusters" ], "related_ids": [ "buildkite-mcp", "kubernetes-mcp" ], "health": "active" }, { "id": "traceloop-otel-mcp", "name": "Traceloop OpenTelemetry MCP", "description": "Unified MCP server for querying OpenTelemetry traces across backends (Jaeger, Tempo, Traceloop). Enables AI agents to analyze distributed traces for debugging.", "category": "infrastructure", "endpoint": "npx @traceloop/opentelemetry-mcp-server", "homepage_url": "https://traceloop.com", "github_url": "https://github.com/traceloop/opentelemetry-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "opentelemetry", "tracing", "observability", "jaeger", "tempo" ], "use_cases": [ "Query distributed traces across multiple OTel backends", "Debug production issues by analyzing trace spans", "Correlate LLM observability with infrastructure traces" ], "related_ids": [ "opentelemetry-mcp", "datadog-mcp" ], "health": "active" }, { "id": "obsidian-mcp", "name": "Obsidian MCP", "description": "Knowledge management MCP server for Obsidian vaults. Read, write, search, and manage notes, tags, and frontmatter via the Obsidian Local REST API.", "category": "productivity", "endpoint": "npx obsidian-mcp-server", "homepage_url": "https://obsidian.md", "github_url": "https://github.com/cyanheads/obsidian-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "obsidian", "notes", "knowledge-management", "markdown", "pkm" ], "use_cases": [ "Search and retrieve notes from Obsidian vaults via AI agents", "Create and update notes with structured frontmatter", "Build persistent AI memory backed by Obsidian" ], "related_ids": [ "notion-mcp", "memory-mcp" ], "health": "active" }, { "id": "box-mcp", "name": "Box MCP", "description": "MCP server for Box cloud storage. Search, read, and access files and folders stored in Box from AI agents and development tools.", "category": "data", "endpoint": "npx box-mcp-server", "homepage_url": "https://www.box.com", "github_url": "https://github.com/hmk/box-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "box", "cloud-storage", "files", "documents", "enterprise" ], "use_cases": [ "Search and retrieve files from Box via AI agents", "Access enterprise documents and folders programmatically", "Integrate Box content into AI-powered workflows" ], "related_ids": [ "gdrive-mcp", "contentful-mcp" ], "health": "active" }, { "id": "mcp-use", "name": "MCP Use", "description": "Fullstack MCP framework for building MCP apps and servers. Production-ready deployment with observability, metrics, logs, and GitHub-integrated branch deployments.", "category": "code", "endpoint": "npx mcp-use", "homepage_url": "https://github.com/mcp-use/mcp-use", "github_url": "https://github.com/mcp-use/mcp-use", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "framework", "mcp", "deployment", "observability", "developer-tools" ], "use_cases": [ "Build and deploy MCP servers with built-in observability", "Develop MCP apps for ChatGPT, Claude, and other clients", "Ship production MCP services with metrics and logging" ], "related_ids": [ "openapi-mcp", "swagger-mcp" ], "health": "active" }, { "id": "qualys-totalai-mcp", "name": "Qualys TotalAI MCP", "description": "Security scanning for AI infrastructure and MCP servers. Detect shadow IT, credential exposure, tool poisoning, and supply chain risks in agent deployments.", "category": "infrastructure", "endpoint": "npx qualys-totalai-mcp", "homepage_url": "https://www.qualys.com/apps/totalai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-22", "updated": "2026-04-22", "tags": [ "security", "ai-security", "compliance", "scanning", "enterprise" ], "use_cases": [ "Scan MCP server deployments for security vulnerabilities", "Detect credential exposure and shadow AI usage", "Audit agent infrastructure for compliance" ], "related_ids": [ "snyk-mcp", "snyk-agent-scan" ], "health": "active" }, { "id": "n8n-mcp", "name": "n8n MCP", "description": "Self-hostable workflow automation platform. Connect any app or API, build complex multi-step automations, and trigger workflows from agent actions.", "category": "productivity", "endpoint": "npx n8n-mcp", "homepage_url": "https://n8n.io", "github_url": "https://github.com/n8n-io/n8n-mcp", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "automation", "workflow", "self-hosted", "integrations", "no-code" ], "use_cases": [ "Trigger n8n workflows from agent actions", "Automate multi-step processes across connected apps", "Build and manage automation pipelines programmatically" ], "related_ids": [ "zapier-mcp", "make-mcp" ], "health": "active" }, { "id": "zapier-mcp", "name": "Zapier MCP", "description": "Connect 7,000+ apps via Zapier automation. Trigger Zaps, run actions, and orchestrate cross-app workflows from any AI agent.", "category": "productivity", "endpoint": "https://mcp.zapier.com", "homepage_url": "https://zapier.com/mcp", "github_url": "https://github.com/zapier/zapier-mcp", "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "automation", "workflow", "integrations", "zaps", "triggers" ], "use_cases": [ "Trigger Zapier workflows from agent decisions", "Connect AI agents to 7,000+ apps without custom integrations", "Automate business processes across the full app stack" ], "related_ids": [ "n8n-mcp", "make-mcp" ], "health": "active" }, { "id": "make-mcp", "name": "Make MCP", "description": "Visual automation platform (formerly Integromat). Build, run, and monitor complex multi-step scenarios connecting hundreds of apps and services.", "category": "productivity", "endpoint": "https://mcp.make.com", "homepage_url": "https://make.com", "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "automation", "workflow", "scenarios", "integrations", "visual" ], "use_cases": [ "Run Make scenarios from agent workflows", "Monitor automation execution and handle errors", "Chain complex multi-step processes across apps" ], "related_ids": [ "n8n-mcp", "zapier-mcp" ], "health": "active" }, { "id": "attio-mcp", "name": "Attio MCP", "description": "Modern CRM built for AI-native teams. Manage contacts, companies, deals, and pipelines. Fully programmable with a powerful API-first design.", "category": "productivity", "endpoint": "npx attio-mcp", "homepage_url": "https://attio.com", "github_url": "https://github.com/attio/mcp-server", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "crm", "contacts", "deals", "pipeline", "sales" ], "use_cases": [ "Query and update CRM records from agent workflows", "Manage sales pipeline stages and deal progress", "Enrich contact and company data programmatically" ], "related_ids": [ "hubspot-mcp", "salesforce-mcp", "pipedrive-mcp" ], "health": "active" }, { "id": "pipedrive-mcp", "name": "Pipedrive MCP", "description": "Sales-focused CRM for pipeline management. Create and update deals, contacts, and activities. Track sales performance and automate follow-ups.", "category": "productivity", "endpoint": "npx pipedrive-mcp", "homepage_url": "https://pipedrive.com", "github_url": "https://github.com/pipedrive/mcp-server", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "crm", "pipeline", "sales", "deals", "contacts" ], "use_cases": [ "Create and update deals from inbound lead agents", "Log activities and schedule follow-up tasks", "Query pipeline stage data for sales reporting agents" ], "related_ids": [ "attio-mcp", "hubspot-mcp", "close-mcp" ], "health": "active" }, { "id": "close-mcp", "name": "Close MCP", "description": "Sales CRM built for high-velocity teams. Log calls, emails, and SMS. Manage leads, opportunities, and sequences from agent-powered sales workflows.", "category": "productivity", "endpoint": "npx close-mcp", "homepage_url": "https://close.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "crm", "sales", "leads", "sequences", "calling" ], "use_cases": [ "Log call and email activity from sales agents", "Manage lead status and opportunity progression", "Trigger and monitor outreach sequences" ], "related_ids": [ "pipedrive-mcp", "attio-mcp", "hubspot-mcp" ], "health": "unknown" }, { "id": "apollo-io-mcp", "name": "Apollo.io MCP", "description": "B2B sales intelligence and engagement platform. Search 270M+ contacts, enrich leads, run sequences, and power prospecting workflows.", "category": "data", "endpoint": "npx apollo-io-mcp", "homepage_url": "https://apollo.io", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "b2b", "prospecting", "data-enrichment", "sales-intelligence", "leads" ], "use_cases": [ "Search and enrich prospect data for outreach agents", "Find verified contact emails and phone numbers", "Trigger and manage sales engagement sequences" ], "related_ids": [ "hubspot-mcp", "salesforce-mcp", "attio-mcp" ], "health": "unknown" }, { "id": "klaviyo-mcp", "name": "Klaviyo MCP", "description": "E-commerce marketing automation for email and SMS. Manage lists, segments, flows, and campaigns. Power personalized marketing from agent workflows.", "category": "communication", "endpoint": "npx klaviyo-mcp", "homepage_url": "https://klaviyo.com", "github_url": "https://github.com/klaviyo/mcp-server", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "email", "sms", "marketing", "ecommerce", "automation" ], "use_cases": [ "Add contacts to flows and trigger email sequences", "Segment customers based on behavioral data", "Personalize marketing campaigns from agent context" ], "related_ids": [ "mailchimp-mcp", "sendgrid-mcp", "customer-io-mcp" ], "health": "active" }, { "id": "customer-io-mcp", "name": "Customer.io MCP", "description": "Behavioral marketing automation platform. Send targeted messages based on user actions. Manage campaigns, broadcasts, and transactional messages.", "category": "communication", "endpoint": "npx customerio-mcp", "homepage_url": "https://customer.io", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "email", "marketing", "automation", "behavioral", "messaging" ], "use_cases": [ "Trigger campaigns based on agent-detected user events", "Send transactional emails from workflow agents", "Manage customer segments and journeys programmatically" ], "related_ids": [ "klaviyo-mcp", "mailchimp-mcp", "sendgrid-mcp" ], "health": "unknown" }, { "id": "brevo-mcp", "name": "Brevo MCP", "description": "All-in-one marketing platform for email, SMS, WhatsApp, and chat. Send transactional and marketing messages, manage contacts and campaigns at scale.", "category": "communication", "endpoint": "npx brevo-mcp", "homepage_url": "https://brevo.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "email", "sms", "whatsapp", "marketing", "transactional" ], "use_cases": [ "Send multi-channel marketing messages from agents", "Manage contact lists and campaign performance", "Automate transactional email delivery" ], "related_ids": [ "mailchimp-mcp", "sendgrid-mcp", "klaviyo-mcp" ], "health": "unknown" }, { "id": "novu-mcp", "name": "Novu MCP", "description": "Open-source notification infrastructure for developers. Manage in-app, email, SMS, push, and chat notifications via a unified API and workflow engine.", "category": "communication", "endpoint": "npx @novu/mcp", "homepage_url": "https://novu.co", "github_url": "https://github.com/novuhq/novu-mcp", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @novu/mcp", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "notifications", "email", "sms", "push", "in-app", "open-source" ], "use_cases": [ "Send multi-channel notifications from agent workflows", "Manage notification preferences and digests", "Trigger workflow-based notifications at any pipeline stage" ], "related_ids": [ "knock-mcp", "sendgrid-mcp", "twilio-mcp" ], "health": "active" }, { "id": "knock-mcp", "name": "Knock MCP", "description": "Developer-first notification infrastructure. Build and manage cross-channel notification workflows across email, SMS, push, in-app, and Slack.", "category": "communication", "endpoint": "npx knock-mcp", "homepage_url": "https://knock.app", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "notifications", "email", "push", "sms", "in-app", "workflows" ], "use_cases": [ "Trigger user notifications at key workflow moments", "Manage notification preferences and frequency caps", "Build multi-channel alert systems for agent outputs" ], "related_ids": [ "novu-mcp", "sendgrid-mcp", "twilio-mcp" ], "health": "unknown" }, { "id": "fireflies-mcp", "name": "Fireflies MCP", "description": "AI meeting assistant that records, transcribes, and analyzes conversations. Search meeting history, extract action items, and surface key insights.", "category": "productivity", "endpoint": "npx fireflies-mcp", "homepage_url": "https://fireflies.ai", "github_url": "https://github.com/firefliesai/mcp-server", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "meetings", "transcription", "ai", "action-items", "search" ], "use_cases": [ "Search past meeting transcripts for context", "Extract action items and decisions from calls", "Summarize conversations for async team updates" ], "related_ids": [ "fathom-mcp", "assemblyai-mcp", "whisper-mcp" ], "health": "active" }, { "id": "fathom-mcp", "name": "Fathom MCP", "description": "AI meeting notetaker that records video calls and generates instant summaries, action items, and follow-up emails. Integrates with major video platforms.", "category": "productivity", "endpoint": "npx fathom-mcp", "homepage_url": "https://fathom.video", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "meetings", "notes", "transcription", "summaries", "video" ], "use_cases": [ "Retrieve meeting notes and summaries from past calls", "Extract key decisions and follow-ups from recordings", "Sync meeting insights to CRM or project tools" ], "related_ids": [ "fireflies-mcp", "assemblyai-mcp" ], "health": "unknown" }, { "id": "convex-mcp", "name": "Convex MCP", "description": "Real-time backend platform with reactive queries, serverless functions, and built-in sync. Run database queries and mutations from AI agents.", "category": "data", "endpoint": "npx convex-mcp", "homepage_url": "https://convex.dev", "github_url": "https://github.com/get-convex/convex-mcp", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "database", "realtime", "backend", "serverless", "reactive" ], "use_cases": [ "Query and mutate Convex data from agent workflows", "Trigger serverless functions from agent decisions", "Sync real-time state across agent and user sessions" ], "related_ids": [ "supabase-mcp", "neon-mcp", "postgres-mcp" ], "health": "active" }, { "id": "cockroachdb-mcp", "name": "CockroachDB MCP", "description": "Distributed SQL database with PostgreSQL compatibility. Run queries, manage schemas, and execute transactions across CockroachDB clusters.", "category": "data", "endpoint": "npx cockroachdb-mcp", "homepage_url": "https://cockroachlabs.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "database", "distributed", "sql", "postgres-compatible", "cloud" ], "use_cases": [ "Execute distributed SQL queries from agent workflows", "Manage multi-region database schemas", "Handle high-scale transactional workloads from agents" ], "related_ids": [ "postgres-mcp", "neon-mcp", "planetscale-mcp" ], "health": "unknown" }, { "id": "segment-mcp", "name": "Segment MCP", "description": "Customer data platform by Twilio. Collect, unify, and route user events and traits across your stack. Query profiles and trigger audience syncs.", "category": "data", "endpoint": "npx segment-mcp", "homepage_url": "https://segment.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "cdp", "analytics", "events", "data-pipeline", "identity" ], "use_cases": [ "Track user events from agent interactions", "Query unified customer profiles for personalization agents", "Sync audience segments to downstream marketing tools" ], "related_ids": [ "mixpanel-mcp", "amplitude-mcp", "posthog-mcp" ], "health": "unknown" }, { "id": "clay-mcp", "name": "Clay MCP", "description": "Data enrichment and outreach automation platform. Enrich leads from 75+ data sources, build contact lists, and run AI-powered research at scale.", "category": "data", "endpoint": "npx clay-mcp", "homepage_url": "https://clay.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "data-enrichment", "prospecting", "research", "outreach", "b2b" ], "use_cases": [ "Enrich contact and company data from 75+ sources", "Build targeted prospect lists with AI research", "Automate personalized outreach copy generation" ], "related_ids": [ "apollo-io-mcp", "hubspot-mcp", "salesforce-mcp" ], "health": "unknown" }, { "id": "hasura-mcp", "name": "Hasura MCP", "description": "Instant GraphQL and REST APIs over your database. Query, mutate, and subscribe to data via auto-generated GraphQL from Postgres, MySQL, and more.", "category": "code", "endpoint": "npx hasura-mcp", "homepage_url": "https://hasura.io", "github_url": "https://github.com/hasura/mcp-server", "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "graphql", "api", "database", "postgres", "rest" ], "use_cases": [ "Query any connected database via auto-generated GraphQL", "Run mutations and subscriptions from agent workflows", "Manage access control rules and permissions programmatically" ], "related_ids": [ "postgres-mcp", "supabase-mcp", "neon-mcp" ], "health": "active" }, { "id": "stytch-mcp", "name": "Stytch MCP", "description": "Developer-first authentication and authorization platform. Manage users, sessions, OAuth connections, and MFA. Programmatic identity for agent-native apps.", "category": "identity", "endpoint": "npx stytch-mcp", "homepage_url": "https://stytch.com", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-04-24", "updated": "2026-04-24", "tags": [ "auth", "identity", "sessions", "oauth", "mfa", "users" ], "use_cases": [ "Manage user authentication flows from agent pipelines", "Verify and revoke sessions programmatically", "Provision and manage users for multi-tenant apps" ], "related_ids": [ "auth0-mcp", "clerk-mcp", "workos-mcp" ], "health": "unknown" }, { "id": "wazuh-mcp", "name": "Wazuh MCP Server", "description": "AI-powered security operations for Wazuh SIEM. Enables conversational SOC workflows for threat detection, incident triage, compliance checks, and real-time monitoring.", "category": "infrastructure", "endpoint": "https://github.com/gensecaihq/Wazuh-MCP-Server", "homepage_url": "https://wazuhmcp.netlify.app/", "github_url": "https://github.com/gensecaihq/Wazuh-MCP-Server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/gensecaihq/Wazuh-MCP-Server.git && cd Wazuh-MCP-Server && pip install -r requirements.txt && pip install -e .", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "siem", "wazuh", "soc", "threat-detection" ], "use_cases": [ "Query Wazuh SIEM alerts and agent health in natural language", "Automate incident triage and compliance checks across monitored endpoints", "Analyze security threats and check IOC reputation through conversational workflows" ], "health": "unknown" }, { "id": "virustotal-mcp", "name": "VirusTotal MCP Server", "description": "MCP server for the VirusTotal API providing security analysis of URLs, files, IPs, and domains with relationship analysis and pagination support.", "category": "infrastructure", "endpoint": "https://github.com/BurtTheCoder/mcp-virustotal", "homepage_url": "https://github.com/BurtTheCoder/mcp-virustotal", "github_url": "https://github.com/BurtTheCoder/mcp-virustotal", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g @anthropic/mcp-virustotal", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "malware", "threat-intel", "virustotal", "scanning" ], "use_cases": [ "Analyze suspicious URLs, files, and domains for malware and threats", "Check IP address reputation and fetch detailed security reports", "Investigate file hashes and explore relationship data across VirusTotal datasets" ], "health": "unknown" }, { "id": "mcp-threatintel", "name": "Threat Intelligence MCP Server", "description": "Unified threat intelligence MCP server aggregating data from AlienVault OTX, AbuseIPDB, GreyNoise, and abuse.ch feeds for correlated IOC lookups.", "category": "infrastructure", "endpoint": "https://github.com/aplaceforallmystuff/mcp-threatintel", "homepage_url": "https://github.com/aplaceforallmystuff/mcp-threatintel", "github_url": "https://github.com/aplaceforallmystuff/mcp-threatintel", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g mcp-threatintel-server", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "threat-intel", "ioc", "otx", "greynoise" ], "use_cases": [ "Query IPs, domains, hashes, and URLs across multiple threat intelligence sources", "Correlate indicators of compromise across AlienVault OTX, AbuseIPDB, and GreyNoise", "Monitor botnet C2 infrastructure via abuse.ch Feodo Tracker feeds" ], "health": "unknown" }, { "id": "google-threat-intel-mcp", "name": "Google Threat Intelligence MCP Server", "description": "Official Google MCP server for threat intelligence (VirusTotal/GTI), Security Operations (Chronicle), SOAR, and Security Command Center integration.", "category": "infrastructure", "endpoint": "https://github.com/google/mcp-security", "homepage_url": "https://google.github.io/mcp-security/", "github_url": "https://github.com/google/mcp-security", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/google/mcp-security.git && cd mcp-security && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "google", "chronicle", "threat-intel", "soc" ], "use_cases": [ "Search for threat actors, malware families, campaigns, and vulnerabilities via Google Threat Intelligence", "Investigate security events and run threat hunts in Google Security Operations (Chronicle)", "Manage cloud security posture and risk findings through Security Command Center" ], "health": "unknown" }, { "id": "cisco-mcp-scanner", "name": "Cisco AI Defense MCP Scanner", "description": "Security scanner for MCP servers using YARA, LLM-as-judge, and Cisco AI Defense engines to detect prompt injection, tool poisoning, and supply chain threats.", "category": "infrastructure", "endpoint": "https://github.com/cisco-ai-defense/mcp-scanner", "homepage_url": "https://github.com/cisco-ai-defense/mcp-scanner", "github_url": "https://github.com/cisco-ai-defense/mcp-scanner", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uv tool install --python 3.13 cisco-ai-mcp-scanner", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "scanning", "supply-chain", "cisco", "devsecops" ], "use_cases": [ "Scan MCP server tools, prompts, and resources for prompt injection and tool poisoning", "Audit Python dependencies for known CVEs using integrated pip-audit scanning", "Detect hidden malicious behavior in MCP server supply chains" ], "health": "unknown" }, { "id": "misp-mcp", "name": "MISP MCP Server", "description": "MCP server integrating with MISP (Malware Information Sharing Platform) for threat intelligence including IOC search, threat actor lookup, and malware detection.", "category": "infrastructure", "endpoint": "https://github.com/bornpresident/MISP-MCP-SERVER", "homepage_url": "https://www.misp-project.org/", "github_url": "https://github.com/bornpresident/MISP-MCP-SERVER", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/bornpresident/MISP-MCP-SERVER.git && cd MISP-MCP-SERVER && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "misp", "threat-intel", "ioc", "malware" ], "use_cases": [ "Search MISP for indicators of compromise by attribute type, tag, or threat actor", "Submit and manage IOCs in MISP for cross-platform threat intelligence sharing", "Generate threat intelligence reports with TLP classification" ], "health": "unknown" }, { "id": "nuclei-mcp", "name": "Nuclei MCP Server", "description": "MCP server for ProjectDiscovery Nuclei vulnerability scanner enabling context-aware scanning with intelligent template selection for CVEs, exposures, and misconfigurations.", "category": "infrastructure", "endpoint": "https://github.com/addcontent/nuclei-mcp", "homepage_url": "https://github.com/projectdiscovery/nuclei", "github_url": "https://github.com/addcontent/nuclei-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/addcontent/nuclei-mcp.git && cd nuclei-mcp && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "security", "vulnerability-scanning", "nuclei", "pentest", "devsecops" ], "use_cases": [ "Run targeted vulnerability scans using Nuclei templates for CVEs and misconfigurations", "Perform context-aware security assessments with AI-guided template selection", "Integrate automated vulnerability scanning into AI-driven security workflows" ], "health": "unknown" }, { "id": "zapier-mcp", "name": "Zapier MCP Server", "description": "Official Zapier remote MCP server providing AI agents direct access to 9,000+ apps and 40,000+ actions for workflow automation.", "category": "productivity", "endpoint": "https://mcp.zapier.com", "homepage_url": "https://mcp.zapier.com", "github_url": "https://github.com/zapier/zapier-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx mcp-remote https://mcp.zapier.com/api-key/mcp", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "automation", "low-code", "zapier", "integrations", "workflows" ], "use_cases": [ "Connect AI agents to 9,000+ apps for automated multi-step workflows", "Trigger Zapier Zaps and actions from conversational AI interfaces", "Orchestrate cross-app automations like CRM updates, email sends, and data syncs" ], "health": "unknown" }, { "id": "n8n-mcp", "name": "n8n MCP Server", "description": "MCP server providing AI assistants access to n8n node documentation, properties, and operations for building and managing n8n workflows programmatically.", "category": "productivity", "endpoint": "https://github.com/czlonkowski/n8n-mcp", "homepage_url": "https://github.com/czlonkowski/n8n-mcp", "github_url": "https://github.com/czlonkowski/n8n-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g n8n-mcp", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "automation", "low-code", "n8n", "workflows", "no-code" ], "use_cases": [ "Build n8n workflows from natural language descriptions using AI assistants", "Query documentation and properties for 543+ n8n nodes with detailed schemas", "Generate and validate workflow configurations using pre-extracted node templates" ], "health": "unknown" }, { "id": "retool-mcp", "name": "Retool MCP Server", "description": "MCP server for managing self-hosted Retool instances, enabling AI-driven app creation, workflow automation, resource management, and user administration.", "category": "productivity", "endpoint": "https://github.com/TechnicalRhino/retool-mcp", "homepage_url": "https://retool.com/blog/how-to-use-mcp-in-retool", "github_url": "https://github.com/TechnicalRhino/retool-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/TechnicalRhino/retool-mcp.git && cd retool-mcp && npm install", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "low-code", "retool", "internal-tools", "admin", "workflows" ], "use_cases": [ "Create and manage Retool apps and folders through AI assistants", "Automate Retool workflow configuration and resource management", "Administer users, groups, and audit logs in Retool via natural language" ], "health": "unknown" }, { "id": "web3-mcp", "name": "Web3 MCP Server", "description": "Multi-chain MCP server by Strangelove Ventures supporting Solana, Ethereum, THORChain, XRP Ledger, TON, Cardano, and UTXO chains for blockchain operations.", "category": "data", "endpoint": "https://github.com/strangelove-ventures/web3-mcp", "homepage_url": "https://github.com/strangelove-ventures/web3-mcp", "github_url": "https://github.com/strangelove-ventures/web3-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/strangelove-ventures/web3-mcp.git && cd web3-mcp && npm install", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "blockchain", "web3", "multi-chain", "defi", "crypto" ], "use_cases": [ "Check balances and transfer tokens across Solana, Ethereum, Cardano, and other chains", "Perform cross-chain swaps via THORChain from a unified interface", "Query blockchain state and account info across multiple networks from AI agents" ], "health": "unknown" }, { "id": "solana-mcp", "name": "Solana MCP Server", "description": "MCP server powered by Solana Agent Kit for interacting with the Solana blockchain, supporting 60+ on-chain actions including token ops, NFTs, DeFi, and wallet management.", "category": "data", "endpoint": "https://github.com/sendaifun/solana-mcp", "homepage_url": "https://github.com/sendaifun/solana-mcp", "github_url": "https://github.com/sendaifun/solana-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g solana-mcp", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "blockchain", "solana", "defi", "nft", "web3" ], "use_cases": [ "Execute Solana transactions, token transfers, and swaps via AI agents", "Mint, list, and manage NFTs on Solana programmatically", "Interact with DeFi protocols for staking, lending, and perpetual trading on Solana" ], "health": "unknown" }, { "id": "etherscan-mcp", "name": "Etherscan MCP Server", "description": "MCP server for querying Ethereum blockchain data via Etherscan API, including ETH balances, transaction history, ERC-20 transfers, contract ABIs, gas prices, and ENS resolution.", "category": "data", "endpoint": "https://github.com/crazyrabbitLTC/mcp-etherscan-server", "homepage_url": "https://etherscan.io/", "github_url": "https://github.com/crazyrabbitLTC/mcp-etherscan-server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/crazyrabbitLTC/mcp-etherscan-server.git && cd mcp-etherscan-server && npm install", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "blockchain", "ethereum", "etherscan", "web3", "explorer" ], "use_cases": [ "Check ETH and ERC-20 token balances and view transaction history for any address", "Fetch smart contract ABIs and monitor gas prices on Ethereum", "Resolve ENS names and track token transfer activity across the Ethereum network" ], "health": "unknown" }, { "id": "moralis-mcp", "name": "Moralis Web3 API MCP Server", "description": "MCP server providing access to 100+ Moralis Web3 API endpoints for querying blockchain data across multiple networks, including NFTs, tokens, wallet analytics, and DeFi positions.", "category": "data", "endpoint": "https://github.com/MoralisWeb3/moralis-mcp-server", "homepage_url": "https://moralis.com/", "github_url": "https://github.com/MoralisWeb3/moralis-mcp-server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/MoralisWeb3/moralis-mcp-server.git && cd moralis-mcp-server && npm install", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "blockchain", "web3", "moralis", "nft", "defi" ], "use_cases": [ "Query NFT metadata, ownership, and collection data across Ethereum, Polygon, and BSC", "Analyze wallet portfolios and DeFi positions across multiple chains", "Fetch real-time token prices, transfers, and on-chain analytics via Moralis APIs" ], "health": "unknown" }, { "id": "docusign-mcp", "name": "DocuSign MCP Server", "description": "MCP server for DocuSign eSignature API enabling envelope management, template operations, document handling, and signing workflows with JWT authentication.", "category": "productivity", "endpoint": "https://github.com/luthersystems/mcp-server-docusign", "homepage_url": "https://developers.docusign.com/platform/mcp-server/", "github_url": "https://github.com/luthersystems/mcp-server-docusign", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/luthersystems/mcp-server-docusign.git && cd mcp-server-docusign && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "legal", "contracts", "esignature", "docusign", "documents" ], "use_cases": [ "Create, send, and manage DocuSign envelopes for contract signing via AI agents", "Check signing status and manage document templates programmatically", "Automate bulk send operations and workspace document management" ], "health": "unknown" }, { "id": "legal-mcp", "name": "Legal MCP Server", "description": "MCP server for legal workflows providing integration with authoritative legal sources for research, document analysis, citation management, and case management.", "category": "data", "endpoint": "https://github.com/agentic-ops/legal-mcp", "homepage_url": "https://github.com/agentic-ops/legal-mcp", "github_url": "https://github.com/agentic-ops/legal-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/agentic-ops/legal-mcp.git && cd legal-mcp && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "legal", "research", "compliance", "case-management", "citations" ], "use_cases": [ "Conduct legal research across authoritative sources with AI-assisted analysis", "Analyze legal documents and manage citation references automatically", "Manage cases and track legal workflows across multiple jurisdictions" ], "health": "unknown" }, { "id": "us-law-mcp", "name": "US Law MCP Server", "description": "MCP server for querying 130+ US federal compliance statutes and regulations including HIPAA, CCPA, SOX, GLBA, FERPA, and FISMA directly from AI assistants.", "category": "data", "endpoint": "https://github.com/Ansvar-Systems/US-law-mcp", "homepage_url": "https://github.com/Ansvar-Systems/US-law-mcp", "github_url": "https://github.com/Ansvar-Systems/US-law-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Ansvar-Systems/US-law-mcp.git && cd US-law-mcp && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "legal", "compliance", "regulation", "us-law", "privacy" ], "use_cases": [ "Query HIPAA, CCPA, SOX, and other federal compliance statutes via natural language", "Research state privacy and breach notification laws for compliance planning", "Cross-reference cybersecurity regulations across multiple US federal frameworks" ], "health": "unknown" }, { "id": "recruitee-mcp", "name": "Recruitee MCP Server", "description": "MCP server for Recruitee ATS enabling AI-powered candidate search, filtering, recruitment statistics, and pipeline management.", "category": "productivity", "endpoint": "https://github.com/appunite/recruitee-mcp-server", "homepage_url": "https://github.com/appunite/recruitee-mcp-server", "github_url": "https://github.com/appunite/recruitee-mcp-server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/appunite/recruitee-mcp-server.git && cd recruitee-mcp-server && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "hr", "recruiting", "ats", "recruitee", "hiring" ], "use_cases": [ "Search and filter candidates by skills, status, talent pool, and tags", "Generate recruitment statistics including average salary and time-to-hire metrics", "Summarize candidate profiles and manage recruitment pipelines via AI agents" ], "health": "unknown" }, { "id": "greenhouse-mcp", "name": "Greenhouse MCP Server", "description": "MCP server wrapping the Greenhouse Harvest API for AI-driven recruitment workflows including job listing, candidate management, and hiring stage progression.", "category": "productivity", "endpoint": "https://github.com/alexmeckes/greenhouse-mcp", "homepage_url": "https://www.greenhouse.com/", "github_url": "https://github.com/alexmeckes/greenhouse-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/alexmeckes/greenhouse-mcp.git && cd greenhouse-mcp && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "hr", "recruiting", "ats", "greenhouse", "hiring" ], "use_cases": [ "List jobs, search candidates, and manage applications through natural language", "Advance or reject candidates through hiring stages with structured reasoning", "Add notes to candidate profiles and create new candidates in Greenhouse via AI" ], "health": "unknown" }, { "id": "lever-mcp", "name": "Lever MCP Server", "description": "MCP server integrating Lever ATS with AI assistants, providing 16 tools for candidate search, profile management, application handling, and pipeline operations.", "category": "productivity", "endpoint": "https://github.com/the-sid-dani/lever-mcp-server", "homepage_url": "https://github.com/the-sid-dani/lever-mcp-server", "github_url": "https://github.com/the-sid-dani/lever-mcp-server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/the-sid-dani/lever-mcp-server.git && cd lever-mcp-server && pip install -r requirements.txt", "added": "2026-04-25", "updated": "2026-04-25", "tags": [ "hr", "recruiting", "ats", "lever", "hiring" ], "use_cases": [ "Search candidates by skills, company, and referral source across Lever pipelines", "Access candidate profiles, notes, and application files through natural language", "Archive candidates and manage pipeline stages and roles via AI assistants" ], "health": "unknown" }, { "id": "mysql-mcp", "name": "MySQL MCP", "description": "Read and write to MySQL databases via natural language. Execute queries, inspect schemas, manage tables, and analyze data across MySQL and MariaDB instances.", "category": "data", "endpoint": "npx @benborla29/mcp-server-mysql", "homepage_url": "https://www.mysql.com", "github_url": "https://github.com/benborla/mcp-server-mysql", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @benborla29/mcp-server-mysql", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "mysql", "database", "sql", "mariadb", "queries" ], "use_cases": [ "Query MySQL databases with natural language via AI assistants", "Inspect table schemas and relationships across databases", "Automate reporting and data analysis on MySQL data" ], "related_ids": [ "postgres-mcp", "planetscale-mcp", "cockroachdb-mcp" ], "health": "unknown" }, { "id": "dynamodb-mcp", "name": "DynamoDB MCP", "description": "Interact with AWS DynamoDB via natural language. Query tables, put and get items, scan with filters, manage indexes, and inspect table metadata.", "category": "data", "endpoint": "npx dynamodb-mcp-server", "homepage_url": "https://aws.amazon.com/dynamodb/", "github_url": "https://github.com/Automata-Labs-team/MCP-Server-DynamoDB", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx dynamodb-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "dynamodb", "aws", "nosql", "database", "serverless" ], "use_cases": [ "Query DynamoDB tables and indexes with natural language", "Put, get, update, and delete items across DynamoDB tables", "Inspect table capacity, TTL settings, and stream configurations" ], "related_ids": [ "aws-api-mcp", "mongodb-mcp", "upstash-mcp" ], "health": "unknown" }, { "id": "fauna-mcp", "name": "Fauna MCP", "description": "Query and manage Fauna serverless databases. Run FQL queries, manage collections and documents, handle indexes, and interact with Fauna's distributed document-relational model.", "category": "data", "endpoint": "npx fauna-mcp", "homepage_url": "https://fauna.com", "github_url": "https://github.com/fauna/fauna-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx fauna-mcp", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "fauna", "database", "serverless", "fql", "document" ], "use_cases": [ "Run FQL queries against Fauna collections via AI agents", "Create and update documents with natural language instructions", "Manage indexes and relationships in Fauna databases" ], "related_ids": [ "mongodb-mcp", "supabase-mcp", "convex-mcp" ], "health": "unknown" }, { "id": "google-sheets-mcp", "name": "Google Sheets MCP", "description": "Read, write, and analyze Google Sheets via natural language. Create and update cells, manage tabs, run formulas, and build reports directly from spreadsheet data.", "category": "productivity", "endpoint": "npx @modelcontextprotocol/server-google-sheets", "homepage_url": "https://sheets.google.com", "github_url": "https://github.com/isaacwasserman/mcp-gsheets", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @modelcontextprotocol/server-google-sheets", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "google-sheets", "spreadsheets", "google", "data", "reporting" ], "use_cases": [ "Read and update Google Sheets cells and ranges via AI assistants", "Generate reports and summaries from spreadsheet data", "Automate data entry and formula management across tabs" ], "related_ids": [ "gdrive-mcp", "airtable-mcp", "notion-mcp" ], "health": "unknown" }, { "id": "google-ai-mcp", "name": "Google AI (Gemini) MCP", "description": "Access Google Gemini models via MCP. Run text generation, multimodal inputs, code execution, and grounding with Google Search through the Gemini API.", "category": "ai", "endpoint": "npx @google/generative-ai-mcp", "homepage_url": "https://ai.google.dev", "github_url": "https://github.com/google-gemini/gemini-api-quickstart", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @google/generative-ai-mcp", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "gemini", "google", "llm", "multimodal", "ai" ], "use_cases": [ "Generate text and analyze images with Gemini models via agents", "Run Gemini with Google Search grounding for real-time answers", "Access code execution and structured output from Gemini APIs" ], "related_ids": [ "openai-mcp", "anthropic-mcp", "groq-mcp" ], "health": "unknown" }, { "id": "xai-mcp", "name": "xAI (Grok) MCP", "description": "Integrate xAI's Grok models into agent workflows. Access Grok's real-time knowledge, large context window, and reasoning capabilities via the xAI API.", "category": "ai", "endpoint": "npx xai-mcp", "homepage_url": "https://x.ai", "github_url": "https://github.com/xai-org/xai-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx xai-mcp", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "xai", "grok", "llm", "reasoning", "real-time" ], "use_cases": [ "Run Grok models with large context for long-document analysis", "Access Grok's real-time knowledge in agent pipelines", "Use Grok for reasoning-heavy workflows alongside other models" ], "related_ids": [ "openai-mcp", "anthropic-mcp", "google-ai-mcp" ], "health": "unknown" }, { "id": "openrouter-mcp", "name": "OpenRouter MCP", "description": "Route LLM requests across 200+ models via a single MCP interface. Access GPT, Claude, Gemini, Llama, Mistral, and more with unified pricing, fallbacks, and load balancing.", "category": "ai", "endpoint": "npx openrouter-mcp", "homepage_url": "https://openrouter.ai", "github_url": "https://github.com/mcp-ecosystem/openrouter-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx openrouter-mcp", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "openrouter", "llm", "routing", "multi-model", "fallback" ], "use_cases": [ "Route agent LLM calls across 200+ models with cost optimization", "Set up automatic fallbacks when primary models are unavailable", "Compare model outputs and latency across providers in one place" ], "related_ids": [ "openai-mcp", "anthropic-mcp", "groq-mcp", "together-ai-mcp" ], "health": "unknown" }, { "id": "zoom-mcp", "name": "Zoom MCP", "description": "Manage Zoom meetings, webinars, and recordings via natural language. Create meetings, list participants, retrieve transcripts, and manage scheduling through the Zoom API.", "category": "communication", "endpoint": "npx zoom-mcp-server", "homepage_url": "https://zoom.us", "github_url": "https://github.com/zoom/zoom-mcp-server", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx zoom-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "zoom", "meetings", "video", "webinar", "transcripts" ], "use_cases": [ "Create and manage Zoom meetings from agent workflows", "Retrieve meeting transcripts and summaries via AI assistants", "List and update webinar registrations and participant data" ], "related_ids": [ "teams-mcp", "slack-mcp", "loom-mcp" ], "health": "unknown" }, { "id": "crisp-mcp", "name": "Crisp MCP", "description": "Manage customer conversations via Crisp. Read and reply to support tickets, update contact profiles, search conversation history, and trigger automated messages.", "category": "communication", "endpoint": "npx crisp-mcp-server", "homepage_url": "https://crisp.chat", "github_url": "https://github.com/crisp-im/crisp-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx crisp-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "crisp", "customer-support", "chat", "helpdesk", "messaging" ], "use_cases": [ "Read and respond to customer support conversations via AI agents", "Search and update contact profiles in Crisp inbox", "Trigger automated messages and manage conversation routing" ], "related_ids": [ "intercom-mcp", "zendesk-mcp", "slack-mcp" ], "health": "unknown" }, { "id": "jenkins-mcp", "name": "Jenkins MCP", "description": "Interact with Jenkins CI/CD pipelines via natural language. Trigger builds, check job status, retrieve logs, manage parameters, and monitor pipeline health.", "category": "infrastructure", "endpoint": "npx jenkins-mcp-server", "homepage_url": "https://www.jenkins.io", "github_url": "https://github.com/jenkinsci/jenkins-mcp-plugin", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx jenkins-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "jenkins", "ci-cd", "pipelines", "builds", "automation" ], "use_cases": [ "Trigger and monitor Jenkins builds via AI agent workflows", "Retrieve build logs and pipeline status in natural language", "Manage Jenkins job parameters and downstream dependencies" ], "related_ids": [ "buildkite-mcp", "circleci-mcp", "tekton-mcp" ], "health": "unknown" }, { "id": "rabbitmq-mcp", "name": "RabbitMQ MCP", "description": "Manage RabbitMQ message queues via natural language. Publish and consume messages, inspect queue depths, manage exchanges and bindings, and monitor broker health.", "category": "infrastructure", "endpoint": "npx rabbitmq-mcp-server", "homepage_url": "https://www.rabbitmq.com", "github_url": "https://github.com/kenliao94/mcp-server-rabbitmq", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx rabbitmq-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "rabbitmq", "message-queue", "amqp", "broker", "async" ], "use_cases": [ "Publish and consume messages from RabbitMQ queues via agents", "Monitor queue depths and consumer lag across exchanges", "Manage RabbitMQ bindings, policies, and dead-letter queues" ], "related_ids": [ "kafka-mcp", "upstash-mcp", "valkey-mcp" ], "health": "unknown" }, { "id": "consul-mcp", "name": "Consul MCP", "description": "Interact with HashiCorp Consul for service discovery and configuration. Query service catalog, manage KV store, inspect health checks, and control access policies.", "category": "infrastructure", "endpoint": "npx consul-mcp-server", "homepage_url": "https://www.consul.io", "github_url": "https://github.com/hashicorp/consul-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx consul-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "consul", "service-discovery", "hashicorp", "kv-store", "service-mesh" ], "use_cases": [ "Query Consul service catalog and health check status via agents", "Read and write configuration values in Consul KV store", "Inspect service mesh policies and intentions across namespaces" ], "related_ids": [ "vault-mcp", "terraform-mcp", "kubernetes-mcp" ], "health": "unknown" }, { "id": "smartsheet-mcp", "name": "Smartsheet MCP", "description": "Read, update, and manage Smartsheet projects via natural language. Access sheets, rows, and columns, manage automation workflows, and generate cross-sheet reports.", "category": "productivity", "endpoint": "npx smartsheet-mcp-server", "homepage_url": "https://www.smartsheet.com", "github_url": "https://github.com/smartsheet/smartsheet-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx smartsheet-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "smartsheet", "project-management", "spreadsheet", "enterprise", "workflows" ], "use_cases": [ "Read and update Smartsheet rows and project status via AI assistants", "Generate cross-sheet reports and summaries from project data", "Automate row creation and status updates from agent workflows" ], "related_ids": [ "monday-mcp", "asana-mcp", "airtable-mcp" ], "health": "unknown" }, { "id": "basecamp-mcp", "name": "Basecamp MCP", "description": "Manage Basecamp projects, to-dos, and messages via natural language. Create and update tasks, read message boards, check schedules, and manage campfire conversations.", "category": "productivity", "endpoint": "npx basecamp-mcp-server", "homepage_url": "https://basecamp.com", "github_url": "https://github.com/basecamp/basecamp-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx basecamp-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "basecamp", "project-management", "todos", "team", "collaboration" ], "use_cases": [ "Create and update to-dos and project tasks in Basecamp via agents", "Read message boards and campfire threads for project context", "Check project schedules and deadlines across Basecamp teams" ], "related_ids": [ "asana-mcp", "clickup-mcp", "trello-mcp" ], "health": "unknown" }, { "id": "woocommerce-mcp", "name": "WooCommerce MCP", "description": "Manage WooCommerce stores via natural language. Query orders, update products, manage customers, apply coupons, and analyze sales data through the WooCommerce REST API.", "category": "payments", "endpoint": "npx woocommerce-mcp-server", "homepage_url": "https://woocommerce.com", "github_url": "https://github.com/mikeyhodl/woocommerce-mcp", "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx woocommerce-mcp-server", "added": "2026-05-06", "updated": "2026-05-06", "tags": [ "woocommerce", "ecommerce", "wordpress", "orders", "products" ], "use_cases": [ "Query and update WooCommerce orders and customer records via agents", "Manage product inventory, pricing, and attributes at scale", "Analyze sales trends and generate store reports with AI assistants" ], "related_ids": [ "shopify-mcp", "stripe-agent-toolkit", "square-mcp" ], "health": "unknown" }, { "id": "amazon-bedrock-mcp", "name": "Amazon Bedrock MCP", "description": "Access Amazon Bedrock foundation models via MCP. Invoke Claude, Titan, Llama, Mistral, and other models hosted on AWS Bedrock directly from agent workflows.", "category": "ai", "endpoint": "uvx awslabs.amazon-bedrock-mcp-server", "homepage_url": "https://aws.amazon.com/bedrock/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx awslabs.amazon-bedrock-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "aws", "bedrock", "foundation-models", "claude", "llama", "amazon" ], "use_cases": [ "Invoke any AWS Bedrock-hosted foundation model from an agent", "Run multi-model workflows using Bedrock's model garden", "Access Bedrock Agents and Knowledge Bases programmatically" ], "health": "active" }, { "id": "litellm-mcp", "name": "LiteLLM MCP", "description": "Universal LLM gateway via MCP. Route agent requests to 100+ LLM providers — OpenAI, Anthropic, Bedrock, Gemini, Groq — through a single interface with cost tracking and load balancing.", "category": "ai", "endpoint": "npx litellm-mcp-server", "homepage_url": "https://litellm.ai", "github_url": "https://github.com/BerriAI/litellm", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx litellm-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "llm-gateway", "multi-model", "openai", "anthropic", "cost-tracking", "load-balancing" ], "use_cases": [ "Route agent calls to the cheapest or fastest LLM for each task", "Track token spend and cost per model across a multi-agent system", "Switch LLM providers without changing agent code" ], "health": "active" }, { "id": "azure-openai-mcp", "name": "Azure OpenAI MCP", "description": "Access Azure-hosted OpenAI models via MCP. Use GPT-4o, o1, and other models deployed in your Azure OpenAI resource with enterprise compliance and private networking.", "category": "ai", "endpoint": "npx @azure/openai-mcp-server", "homepage_url": "https://azure.microsoft.com/en-us/products/ai-services/openai-service", "github_url": "https://github.com/Azure/azure-sdk-for-js", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @azure/openai-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "azure", "openai", "gpt-4o", "enterprise", "microsoft", "compliance" ], "use_cases": [ "Call Azure OpenAI deployments from agent workflows with enterprise auth", "Run inference inside a private Azure VNet for compliance-sensitive workloads", "Manage Azure OpenAI deployments and monitor usage from agents" ], "health": "active" }, { "id": "deepseek-mcp", "name": "DeepSeek MCP", "description": "Access DeepSeek reasoning and chat models via MCP. Run DeepSeek-R1 and DeepSeek-V3 for cost-efficient reasoning tasks, long-context analysis, and code generation.", "category": "ai", "endpoint": "npx deepseek-mcp-server", "homepage_url": "https://deepseek.com", "github_url": "https://github.com/deepseek-ai/deepseek-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx deepseek-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "deepseek", "reasoning", "r1", "v3", "cost-efficient", "long-context" ], "use_cases": [ "Run chain-of-thought reasoning tasks at low cost with DeepSeek-R1", "Process long documents with DeepSeek's extended context window", "Generate and review code using DeepSeek Coder" ], "health": "active" }, { "id": "neo4j-mcp", "name": "Neo4j MCP", "description": "Query and manage Neo4j graph databases via MCP. Run Cypher queries, traverse relationships, and build knowledge graphs that agents can navigate and update.", "category": "data", "endpoint": "npx @neo4j/mcp-server", "homepage_url": "https://neo4j.com", "github_url": "https://github.com/neo4j-contrib/mcp-neo4j", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @neo4j/mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "neo4j", "graph-database", "cypher", "knowledge-graph", "relationships", "nosql" ], "use_cases": [ "Run Cypher queries to traverse entity relationships in a knowledge graph", "Build and update graph structures from agent-gathered data", "Use Neo4j as a memory layer for agents that need relational context" ], "health": "active" }, { "id": "duckdb-mcp", "name": "DuckDB MCP", "description": "Run in-process analytical SQL queries via MCP. DuckDB handles Parquet, CSV, and JSON files natively — no server required. Fast local analytics for agents that need to reason over structured data.", "category": "data", "endpoint": "uvx duckdb-mcp", "homepage_url": "https://duckdb.org", "github_url": "https://github.com/motherduck-data/duckdb-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx duckdb-mcp", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "duckdb", "analytics", "sql", "parquet", "csv", "local", "in-process" ], "use_cases": [ "Query Parquet and CSV files with SQL without spinning up a database server", "Run fast analytical aggregations over local datasets from an agent", "Join multiple file formats (JSON, CSV, Parquet) in a single SQL query" ], "health": "active" }, { "id": "apache-airflow-mcp", "name": "Apache Airflow MCP", "description": "Trigger, monitor, and manage Apache Airflow DAGs via MCP. Agents can start pipeline runs, check task status, read logs, and respond to failures without human intervention.", "category": "infrastructure", "endpoint": "npx airflow-mcp-server", "homepage_url": "https://airflow.apache.org", "github_url": "https://github.com/apache/airflow", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx airflow-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "airflow", "dag", "pipeline", "orchestration", "workflow", "data-engineering" ], "use_cases": [ "Trigger an Airflow DAG run in response to an upstream event", "Monitor task status and surface failures to an agent for remediation", "Read Airflow logs to diagnose pipeline issues programmatically" ], "health": "active" }, { "id": "prefect-mcp", "name": "Prefect MCP", "description": "Orchestrate and observe Prefect workflows via MCP. Trigger flow runs, monitor states, manage deployments, and retrieve logs — letting agents drive data pipeline operations end to end.", "category": "infrastructure", "endpoint": "uvx prefect-mcp", "homepage_url": "https://prefect.io", "github_url": "https://github.com/PrefectHQ/prefect-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx prefect-mcp", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "prefect", "workflow", "orchestration", "data-pipeline", "flow-runs", "monitoring" ], "use_cases": [ "Trigger Prefect flow runs from agent decisions or external events", "Check flow run states and retrieve results from completed pipelines", "Create or update Prefect deployments programmatically from an agent" ], "health": "active" }, { "id": "modal-mcp", "name": "Modal MCP", "description": "Run serverless GPU and CPU workloads on Modal via MCP. Deploy functions, trigger jobs, and retrieve results — giving agents access to scalable compute without managing infrastructure.", "category": "infrastructure", "endpoint": "uvx modal-mcp-server", "homepage_url": "https://modal.com", "github_url": "https://github.com/modal-labs/modal-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx modal-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "modal", "serverless", "gpu", "compute", "ml", "python" ], "use_cases": [ "Run GPU-intensive ML jobs from an agent without provisioning servers", "Deploy and invoke Python functions on Modal's serverless compute from agent workflows", "Scale batch processing tasks dynamically based on agent-determined load" ], "health": "active" }, { "id": "doppler-mcp", "name": "Doppler MCP", "description": "Access and manage secrets from Doppler via MCP. Agents can fetch environment-specific configs, rotate secrets, and audit access — keeping credentials out of code and out of prompts.", "category": "infrastructure", "endpoint": "npx doppler-mcp-server", "homepage_url": "https://doppler.com", "github_url": "https://github.com/DopplerHQ/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx doppler-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "doppler", "secrets", "env-vars", "config", "secret-management", "security" ], "use_cases": [ "Fetch environment-specific secrets at runtime without hardcoding credentials", "Rotate API keys and propagate updated secrets across services via an agent", "Audit secret access logs and surface anomalies programmatically" ], "health": "active" }, { "id": "minio-mcp", "name": "MinIO MCP", "description": "Interact with MinIO S3-compatible object storage via MCP. Upload, download, list, and delete objects across buckets — giving agents a self-hosted storage layer with full S3 API compatibility.", "category": "infrastructure", "endpoint": "uvx minio-mcp-server", "homepage_url": "https://min.io", "github_url": "https://github.com/minio/minio-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx minio-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "minio", "s3", "object-storage", "self-hosted", "buckets", "storage" ], "use_cases": [ "Store and retrieve agent-generated files in a self-hosted S3-compatible store", "Manage bucket policies and lifecycle rules programmatically", "Use MinIO as an intermediate storage layer in multi-step data pipelines" ], "health": "active" }, { "id": "webflow-mcp", "name": "Webflow MCP", "description": "Manage Webflow sites, CMS collections, and pages via MCP. Agents can create and update CMS items, publish changes, and read site structure — enabling AI-driven content operations on Webflow.", "category": "web", "endpoint": "npx @webflow/mcp-server", "homepage_url": "https://webflow.com", "github_url": "https://github.com/webflow/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @webflow/mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "webflow", "cms", "no-code", "site-builder", "pages", "content" ], "use_cases": [ "Create and update CMS collection items from agent-generated content", "Publish or unpublish pages programmatically based on content approval logic", "Read Webflow site structure to generate sitemaps or content audits" ], "health": "active" }, { "id": "wordpress-mcp", "name": "WordPress MCP", "description": "Manage WordPress sites via MCP using the REST API. Create posts, update pages, manage media, handle comments, and query site data — giving agents full CMS control over WordPress properties.", "category": "web", "endpoint": "npx wordpress-mcp-server", "homepage_url": "https://wordpress.org", "github_url": "https://github.com/automattic/wordpress-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx wordpress-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "wordpress", "cms", "blogging", "rest-api", "posts", "pages" ], "use_cases": [ "Publish AI-generated content to WordPress as drafts or live posts", "Update page content and metadata across a WordPress multisite from an agent", "Query post categories, tags, and taxonomy to inform content strategy" ], "health": "active" }, { "id": "ghost-mcp", "name": "Ghost MCP", "description": "Publish and manage content on Ghost via MCP. Create posts, manage members, send newsletters, and read publication analytics — integrating Ghost's headless CMS into agent-driven content workflows.", "category": "media", "endpoint": "npx ghost-mcp-server", "homepage_url": "https://ghost.org", "github_url": "https://github.com/TryGhost/ghost-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx ghost-mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "ghost", "cms", "newsletter", "blogging", "publishing", "members" ], "use_cases": [ "Publish agent-generated articles to Ghost as drafts for human review", "Query Ghost member and subscriber data to inform content targeting", "Trigger newsletter sends programmatically based on content pipeline output" ], "health": "active" }, { "id": "replit-mcp", "name": "Replit MCP", "description": "Create, run, and manage code in Replit via MCP. Agents can spin up Repls, execute code, read output, and collaborate on projects — giving AI workflows a cloud coding environment on demand.", "category": "code", "endpoint": "npx @replit/mcp-server", "homepage_url": "https://replit.com", "github_url": "https://github.com/replit/replit-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @replit/mcp-server", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "replit", "cloud-ide", "code-execution", "repl", "collaboration", "hosting" ], "use_cases": [ "Create a Repl and execute agent-generated code in an isolated environment", "Run and test code snippets without local environment dependencies", "Host and share lightweight applications spun up by agent workflows" ], "health": "active" }, { "id": "readwise-mcp", "name": "Readwise MCP", "description": "Access reading highlights and saved articles from Readwise via MCP. Agents can retrieve highlights by book, article, or tag — surfacing your reading knowledge base for summarization, synthesis, and retrieval.", "category": "productivity", "endpoint": "uvx readwise-mcp", "homepage_url": "https://readwise.io", "github_url": "https://github.com/readwiseio/readwise-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx readwise-mcp", "added": "2026-05-07", "updated": "2026-05-07", "tags": [ "readwise", "highlights", "reading", "knowledge-base", "books", "articles" ], "use_cases": [ "Retrieve relevant highlights from your Readwise library for agent-driven synthesis", "Surface book notes and article highlights when researching a topic", "Use Readwise highlights as a personal knowledge base for RAG workflows" ], "health": "active" }, { "id": "splunk-mcp", "name": "Splunk", "description": "Connect AI agents to Splunk data for SIEM, observability, and log analysis using the Model Context Protocol. Supports search, dashboards, and security investigations with encrypted token auth and granular admin controls.", "category": "data", "endpoint": "splunkbase://app/7931", "homepage_url": "https://www.splunk.com/en_us/blog/artificial-intelligence/unlock-the-power-of-splunk-cloud-platform-with-the-mcp-server.html", "github_url": "https://github.com/darwineee/Splunk-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx @anthropic-ai/create-mcp --preset splunk", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "siem", "observability", "logs", "security", "monitoring", "analytics" ], "use_cases": [ "Query Splunk indexes and run saved searches from AI agents", "Investigate security incidents with natural language across Splunk data", "Build automated observability workflows that analyze log patterns" ], "health": "active" }, { "id": "servicenow-mcp", "name": "ServiceNow", "description": "MCP server for ServiceNow ITSM with 60+ tools spanning incidents, changes, users, CMDB, and knowledge base. Supports record CRUD, script management, and natural language interactions with ServiceNow instances.", "category": "productivity", "endpoint": "npx servicenow-mcp", "homepage_url": "https://www.servicenow.com/community/developer-articles/how-to-create-your-own-servicenow-mcp-server/ta-p/3298144", "github_url": "https://github.com/ShunyaAI/snow-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install snow-mcp", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "itsm", "service-desk", "incidents", "enterprise", "workflow", "cmdb" ], "use_cases": [ "Manage IT incidents and change requests through AI agents", "Search and update ServiceNow records using natural language", "Automate service desk workflows across ITSM processes" ], "health": "active" }, { "id": "microsoft-fabric-mcp", "name": "Microsoft Fabric", "description": "Official MCP server for Microsoft Fabric analytics platform. Cloud-hosted with Entra ID authentication and RBAC enforcement. Agents can manage workspaces, items, permissions, query real-time data with KQL, and access OneLake.", "category": "data", "endpoint": "https://api.fabric.microsoft.com/mcp", "homepage_url": "https://blog.fabric.microsoft.com/en-US/blog/introducing-fabric-mcp-public-preview/", "github_url": "https://github.com/microsoft/fabric-rti-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset microsoft-fabric", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "analytics", "data-platform", "microsoft", "lakehouse", "real-time", "kql" ], "use_cases": [ "Query and analyze data across Microsoft Fabric lakehouses and warehouses", "Manage Fabric workspaces and permissions through AI agents", "Run real-time intelligence queries with KQL via Eventhouse" ], "health": "active" }, { "id": "jama-mcp", "name": "Jama Connect", "description": "First engineering management software with an official MCP server. Agents access requirements, test cases, and traceability data in Jama Connect while maintaining lifecycle workflows, audit requirements, and regulatory compliance.", "category": "productivity", "endpoint": "npx jama-mcp-server", "homepage_url": "https://www.jamasoftware.com/press/jama-software-launches-model-context-protocol-mcp-server/", "github_url": "https://github.com/t-j-thomas/jama-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "pip install jama-mcp-server", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "engineering", "requirements", "traceability", "compliance", "testing", "product-management" ], "use_cases": [ "Access and iterate on engineering requirements with AI-assisted spec development", "Trace requirements to test cases and verify coverage through natural language", "Maintain regulatory compliance while using AI agents for engineering workflows" ], "health": "active" }, { "id": "marketo-mcp", "name": "Adobe Marketo Engage", "description": "Official MCP server for Adobe Marketo Engage marketing automation platform. 100+ operations across forms, programs, smart campaigns, leads, and emails. Enables AI agents to manage marketing workflows at scale.", "category": "communication", "endpoint": "https://marketo.adobe.com/mcp", "homepage_url": "https://business.adobe.com/products/marketo/adobe-marketo.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset marketo", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "marketing-automation", "email", "campaigns", "leads", "adobe", "b2b" ], "use_cases": [ "Manage smart campaigns and program workflows through AI agents", "Automate lead scoring and nurture sequences with natural language", "Create and modify email templates and forms via MCP tools" ], "health": "active" }, { "id": "amazon-ads-mcp", "name": "Amazon Ads", "description": "Official MCP server for Amazon Advertising with 50+ tools covering Sponsored Products, Sponsored Brands, Sponsored Display, DSP, and Amazon Marketing Cloud. Full campaign management through AI agents.", "category": "web", "endpoint": "https://advertising.amazon.com/mcp", "homepage_url": "https://advertising.amazon.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset amazon-ads", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "advertising", "amazon", "campaigns", "ppc", "dsp", "marketing" ], "use_cases": [ "Manage Amazon PPC campaigns and bid strategies through AI agents", "Generate campaign performance reports and optimize ad spend", "Create and manage Sponsored Products and Sponsored Brands campaigns" ], "health": "active" }, { "id": "spanner-mcp", "name": "Google Cloud Spanner", "description": "Google-managed MCP server for Cloud Spanner, the globally distributed relational database. Agents can query data, manage schemas, run graph queries with Spanner Graph, and perform vector similarity search. IAM-authenticated.", "category": "data", "endpoint": "https://mcp.googleapis.com/spanner", "homepage_url": "https://cloud.google.com/blog/products/databases/managed-mcp-servers-for-google-cloud-databases", "github_url": "https://github.com/google/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset gcp-spanner", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "database", "google-cloud", "distributed", "relational", "graph", "sql" ], "use_cases": [ "Query globally distributed Spanner databases from AI agents", "Manage database schemas and run graph queries with natural language", "Perform vector similarity search across Spanner data" ], "health": "active" }, { "id": "firestore-mcp", "name": "Google Cloud Firestore", "description": "Google-managed MCP server for Firestore, the serverless NoSQL document database. Agents can sync with live document collections, check session states, manage data, and build real-time applications. IAM-authenticated.", "category": "data", "endpoint": "https://mcp.googleapis.com/firestore", "homepage_url": "https://cloud.google.com/blog/products/databases/managed-mcp-servers-for-google-cloud-databases", "github_url": "https://github.com/google/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset gcp-firestore", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "database", "google-cloud", "nosql", "document", "serverless", "realtime" ], "use_cases": [ "Read and write Firestore documents from AI agents", "Sync with live document collections for real-time workflows", "Query nested document structures with natural language" ], "health": "active" }, { "id": "cloud-run-mcp", "name": "Google Cloud Run", "description": "Google-managed MCP server for Cloud Run serverless container platform. Agents can deploy services, manage revisions, configure traffic splitting, and monitor running containers. IAM-authenticated with full audit logging.", "category": "infrastructure", "endpoint": "https://mcp.googleapis.com/cloudrun", "homepage_url": "https://cloud.google.com/blog/products/ai-machine-learning/google-managed-mcp-servers-are-available-for-everyone", "github_url": "https://github.com/google/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @anthropic-ai/create-mcp --preset gcp-cloud-run", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "serverless", "containers", "google-cloud", "deployment", "scaling", "compute" ], "use_cases": [ "Deploy and manage Cloud Run services through AI agents", "Configure traffic splitting and rollout strategies with natural language", "Monitor container health and scale services automatically" ], "health": "active" }, { "id": "bedrock-agentcore-payments", "name": "AWS Bedrock AgentCore Payments", "description": "First managed payment capability purpose-built for autonomous agents. Built with Coinbase and Stripe, enables AI agents to autonomously access and pay for APIs, MCP servers, web content, and other agents using USDC.", "category": "payments", "endpoint": "https://bedrock.us-east-1.amazonaws.com/agentcore/payments", "homepage_url": "https://aws.amazon.com/about-aws/whats-new/2026/04/amazon-bedrock-agentcore-payments-preview/", "x402": true, "verified": true, "protocols": [ "MCP", "x402" ], "transport": "http", "auth": "oauth", "install_cmd": "pip install boto3 && aws bedrock-agent configure-payments", "added": "2026-05-08", "updated": "2026-05-08", "tags": [ "payments", "aws", "usdc", "agent-commerce", "coinbase", "stripe", "autonomous" ], "use_cases": [ "Enable AI agents to pay for external APIs and MCP servers autonomously", "Set spending limits and budget controls for autonomous agent transactions", "Process USDC payments between agents using Coinbase and Stripe infrastructure" ], "health": "active" }, { "id": "dynatrace-mcp", "name": "Dynatrace MCP", "description": "Official Dynatrace MCP server for observability. Query metrics with DQL, investigate problems and vulnerabilities, analyze Kubernetes events, forecast timeseries data, and access production insights from AI agents.", "category": "infrastructure", "endpoint": "npx -y @dynatrace-oss/dynatrace-mcp-server", "homepage_url": "https://www.dynatrace.com/hub/detail/dynatrace-mcp-server/", "github_url": "https://github.com/dynatrace-oss/dynatrace-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @dynatrace-oss/dynatrace-mcp-server", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "dynatrace", "observability", "dql", "apm", "kubernetes" ], "use_cases": [ "Generate and run DQL queries to investigate production issues from agent workflows", "Forecast and analyze timeseries metrics for capacity planning agents", "Diagnose vulnerabilities and Kubernetes events using AI-driven incident response" ], "health": "active" }, { "id": "salesforce-data360-mcp", "name": "Salesforce Data 360 MCP", "description": "Official Salesforce Data 360 MCP server. Connect LLMs to Salesforce data with a facade tool architecture exposing roughly 200 API operations without hitting context window limits.", "category": "data", "endpoint": "java -jar data360-mcp-server-1.0.0.jar", "homepage_url": "https://developer.salesforce.com/blogs/2026/05/introducing-the-data-360-mcp-server-developer-preview", "github_url": "https://github.com/forcedotcom/d360-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/forcedotcom/d360-mcp-server && cd d360-mcp-server && mvn clean package -DskipTests", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "salesforce", "data-360", "crm", "connect-api", "enterprise" ], "use_cases": [ "Access Salesforce Data 360 APIs from AI coding assistants without context window overflow", "Query and manage Salesforce data across roughly 200 API operations via natural language", "Build enterprise data pipelines connecting LLMs to Salesforce org data" ], "health": "active" }, { "id": "microsoft-learn-mcp", "name": "Microsoft Learn MCP", "description": "Official Microsoft Learn MCP server and CLI. Powers LLMs and AI agents with real-time, trusted Microsoft documentation and code samples. Only accesses official first-party Microsoft docs.", "category": "web", "endpoint": "npx @microsoft/learn-mcp", "homepage_url": "https://learn.microsoft.com/en-us/training/support/mcp", "github_url": "https://github.com/MicrosoftDocs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @microsoft/learn-mcp", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "microsoft", "documentation", "learn", "azure", "official" ], "use_cases": [ "Search and retrieve trusted Microsoft documentation during AI-assisted development", "Fetch Azure and .NET code samples from official sources for agent context", "Prevent LLM hallucinations by grounding responses in first-party Microsoft docs" ], "health": "active" }, { "id": "dropbox-dash-mcp", "name": "Dropbox Dash MCP", "description": "Official Dropbox MCP server. Search files, retrieve metadata, and access content across your Dropbox workspace. Available as both a remote server and local STDIO implementation.", "category": "productivity", "endpoint": "https://mcp.dropbox.com/dash", "homepage_url": "https://help.dropbox.com/integrations/set-up-MCP-server", "github_url": "https://github.com/dropbox/mcp-server-dash", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "uv pip install -e git+https://github.com/dropbox/mcp-server-dash.git", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "dropbox", "files", "cloud-storage", "search", "dash" ], "use_cases": [ "Search and retrieve Dropbox files and metadata from AI agent workflows", "Access Dropbox Dash unified search across connected apps and content", "Navigate folder structures and extract file content for context retrieval" ], "health": "active" }, { "id": "meta-ads-mcp", "name": "Meta Ads MCP", "description": "MCP server for Meta (Facebook/Instagram) advertising. Manage campaigns, retrieve performance data, analyze ad creatives, and optimize Meta Ads from AI agents.", "category": "data", "endpoint": "npx -y meta-ads-mcp", "homepage_url": "https://www.facebook.com/business/help/1456422242197840", "github_url": "https://github.com/pipeboard-co/meta-ads-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y meta-ads-mcp", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "meta", "facebook", "instagram", "advertising", "marketing" ], "use_cases": [ "Retrieve ad campaign performance data and analytics from Meta platforms", "Manage Facebook and Instagram ad campaigns from agent-driven marketing workflows", "Analyze ad creatives and optimize targeting via natural language commands" ], "health": "active" }, { "id": "ms365-mcp", "name": "Microsoft 365 MCP", "description": "MCP server for Microsoft 365 via the Graph API. Access Outlook email, Calendar, OneDrive, Excel, Teams, SharePoint, Planner, and 200+ endpoints from AI agents.", "category": "productivity", "endpoint": "npx -y @softeria/ms-365-mcp-server", "homepage_url": "https://github.com/Softeria/ms-365-mcp-server", "github_url": "https://github.com/Softeria/ms-365-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @softeria/ms-365-mcp-server", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "microsoft-365", "outlook", "onedrive", "teams", "graph-api" ], "use_cases": [ "Read and send Outlook emails and manage calendar events from agent workflows", "Access OneDrive files and Excel workbooks via the Microsoft Graph API", "Interact with Teams channels, SharePoint sites, and Planner tasks from AI agents" ], "health": "active" }, { "id": "financial-datasets-mcp", "name": "Financial Datasets MCP", "description": "MCP server for stock market and cryptocurrency data. Retrieve income statements, balance sheets, cash flow statements, stock prices, and company news from AI agents.", "category": "data", "endpoint": "pip install financial-datasets-mcp", "homepage_url": "https://financialdatasets.ai", "github_url": "https://github.com/financial-datasets/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install financial-datasets-mcp", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "finance", "stocks", "market-data", "crypto", "fundamentals" ], "use_cases": [ "Retrieve financial statements and fundamentals for equity research agents", "Get real-time and historical stock and crypto prices for trading analysis", "Access company news and financial data for investment decision workflows" ], "health": "active" }, { "id": "bank-mcp", "name": "Bank MCP", "description": "Multi-provider banking MCP server. Securely access bank accounts, balances, and transactions through Plaid, Teller, Enable Banking, and Tink from AI agents with read-only access.", "category": "payments", "endpoint": "npx -y @elcukro/bank-mcp", "homepage_url": "https://github.com/elcukro/bank-mcp", "github_url": "https://github.com/elcukro/bank-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @elcukro/bank-mcp", "added": "2026-05-09", "updated": "2026-05-09", "tags": [ "banking", "plaid", "teller", "accounts", "transactions" ], "use_cases": [ "Give AI agents secure read-only access to bank account balances and transactions", "Aggregate financial data from multiple banking providers for personal finance agents", "Analyze spending patterns and transaction history from agent-driven budgeting workflows" ], "health": "active" }, { "id": "temporal-mcp", "name": "Temporal MCP", "description": "MCP server for Temporal workflow orchestration. Lets AI agents start, monitor, signal, cancel, and inspect workflows entirely through natural language. Exposes 19 tools covering the full Temporal surface area including batch operations and schedule management via cron expressions.", "category": "infrastructure", "endpoint": "temporal-mcp", "homepage_url": "https://temporal.io/code-exchange/temporal-mcp-server", "github_url": "https://github.com/mocksi/temporal-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx temporal-mcp", "added": "2026-05-10", "updated": "2026-05-10", "tags": [ "temporal", "workflow-orchestration", "automation", "devops" ], "use_cases": [ "Start and monitor long-running workflows via natural language", "Batch cancel or signal workflows in bulk", "Manage workflow schedules with cron expressions" ], "health": "active" }, { "id": "tinybird-mcp", "name": "Tinybird MCP", "description": "MCP server for Tinybird real-time analytics. Connects AI agents directly to your Tinybird workspace to query data sources, call analytics endpoints, and use APIs as tools. Enterprise-grade security and observability with zero infrastructure setup.", "category": "data", "endpoint": "https://mcp.tinybird.co", "homepage_url": "https://www.tinybird.co/docs/forward/analytics-agents/mcp", "github_url": "https://github.com/tinybirdco/tinybird-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx @tinybird/mcp-server", "added": "2026-05-10", "updated": "2026-05-10", "tags": [ "analytics", "real-time", "data-api", "observability" ], "use_cases": [ "Query real-time analytics data via natural language", "Call Tinybird API endpoints as agent tools", "Build data-driven agents without manual API integration" ], "health": "active" }, { "id": "lucid-mcp", "name": "Lucid MCP", "description": "Official MCP server from Lucid Software for interacting with Lucidchart diagrams, Lucidspark boards, and Lucidscale architecture maps. Find documents with natural language queries, get summaries of complex diagrams, and extract data from visual content without leaving your AI tool.", "category": "productivity", "endpoint": "https://mcp.lucid.app", "homepage_url": "https://community.lucid.co/community-news-and-announcements-9/introducing-the-lucid-model-context-protocol-mcp-server-12230", "github_url": "https://github.com/lucidsoftware/lucid-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @lucid/mcp", "added": "2026-05-10", "updated": "2026-05-10", "tags": [ "diagrams", "visual-collaboration", "lucidchart", "architecture" ], "use_cases": [ "Search and retrieve Lucidchart diagrams via natural language", "Get instant summaries of complex architecture diagrams", "Extract data from Lucidspark boards into agent workflows" ], "health": "active" }, { "id": "lovable-mcp", "name": "Lovable MCP", "description": "MCP server for Lovable, the AI app builder. Lets agents create, iterate, and deploy full-stack web applications directly from the terminal or AI agent workflows. Research preview launched May 2026.", "category": "code", "endpoint": "lovable-mcp", "homepage_url": "https://lovable.dev", "github_url": "https://github.com/lovable-dev/lovable-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @lovable/mcp", "added": "2026-05-10", "updated": "2026-05-10", "tags": [ "app-builder", "deployment", "full-stack", "code-generation" ], "use_cases": [ "Create and deploy web apps via agent workflows", "Iterate on existing Lovable projects from the terminal", "Automate app scaffolding and deployment pipelines" ], "health": "active" }, { "id": "microsoft-purview-mcp", "name": "Microsoft Purview MCP", "description": "MCP server for Microsoft Purview compliance and governance. Connects AI agents to Purview's compliance engine for audit trails, retention policies, data governance workflows, and eDiscovery. Transforms complex compliance operations into conversational commands.", "category": "infrastructure", "endpoint": "microsoft-purview-mcp", "homepage_url": "https://learn.microsoft.com/en-us/purview/", "github_url": "https://github.com/microsoft/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @microsoft/purview-mcp", "added": "2026-05-10", "updated": "2026-05-10", "tags": [ "compliance", "governance", "microsoft", "audit", "data-management" ], "use_cases": [ "Query compliance and audit trails via natural language", "Manage data retention policies through agent workflows", "Automate eDiscovery and governance reporting" ], "health": "active" }, { "id": "blender-mcp", "name": "Blender MCP", "description": "Official Blender MCP server for AI-powered 3D modeling, scene analysis, and Python scripting within Blender.", "category": "media", "endpoint": "uvx blender-mcp", "homepage_url": "https://www.blender.org/lab/mcp-server/", "github_url": "https://github.com/ahujasid/blender-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx blender-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "blender", "3d-modeling", "creative", "design", "python" ], "use_cases": [ "Analyze and debug Blender 3D scenes with AI assistance", "Generate Python scripts to batch-modify objects in Blender", "Create and manipulate 3D models through natural language" ], "health": "active" }, { "id": "adobe-express-mcp", "name": "Adobe Express MCP", "description": "Official Adobe Express developer MCP server for building add-ons and integrating with Adobe Creative Cloud workflows.", "category": "media", "endpoint": "npx -y @adobe/express-developer-mcp", "homepage_url": "https://developer.adobe.com/express/add-ons/docs/guides/getting-started/local-development/mcp-server", "github_url": "https://github.com/adobe/generator-app-remote-mcp-server-generic", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @adobe/express-developer-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "adobe", "creative-cloud", "express", "design", "photoshop" ], "use_cases": [ "Build Adobe Express add-ons with AI-assisted development", "Automate design workflows across Adobe Creative Cloud apps", "Integrate AI assistants with Photoshop, Premiere, and Express" ], "health": "active" }, { "id": "ableton-mcp", "name": "Ableton Live MCP", "description": "MCP server for controlling Ableton Live — create tracks, edit MIDI, manage sessions, and automate music production via AI.", "category": "media", "endpoint": "uvx ableton-mcp", "homepage_url": "https://github.com/ahujasid/ableton-mcp", "github_url": "https://github.com/ahujasid/ableton-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx ableton-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "ableton", "music", "audio", "daw", "creative", "production" ], "use_cases": [ "Control Ableton Live sessions through natural language commands", "Create and edit MIDI tracks and arrangements with AI", "Automate music production workflows and sound design" ], "health": "active" }, { "id": "resolume-mcp", "name": "Resolume MCP", "description": "MCP server for Resolume Arena and Avenue with 206 tools for playback, composition control, Advanced Output, and show recovery.", "category": "media", "endpoint": "uv run python -m resolume_mcp", "homepage_url": "https://resolume.com/support/en/mcp-servers", "github_url": "https://github.com/drohi-r/resolume-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/drohi-r/resolume-mcp && cd resolume-mcp && uv sync", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "resolume", "vj", "visual", "live-performance", "video", "creative" ], "use_cases": [ "Control Resolume VJ software for live visual performances via AI", "Manage composition layers, clips, and playback through natural language", "Automate Advanced Output configuration and show recovery" ], "health": "active" }, { "id": "sketchup-mcp", "name": "SketchUp MCP", "description": "MCP server for SketchUp 3D modeling — create geometry, manage scenes, apply materials, and export models with AI assistance.", "category": "media", "endpoint": "uvx sketchup-mcp", "homepage_url": "https://github.com/mhyrr/sketchup-mcp", "github_url": "https://github.com/mhyrr/sketchup-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx sketchup-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "sketchup", "3d-modeling", "architecture", "design", "cad" ], "use_cases": [ "Create and modify 3D models in SketchUp through natural language", "Automate architectural and design workflows in SketchUp", "Manage scenes, materials, and geometry with AI assistance" ], "health": "active" }, { "id": "autodesk-fusion-mcp", "name": "Autodesk Fusion MCP", "description": "MCP server for Autodesk Fusion 360 — create and modify 3D CAD models, run simulations, and automate engineering workflows.", "category": "code", "endpoint": "uvx fusion-mcp-server", "homepage_url": "https://www.autodesk.com/solutions/autodesk-ai/autodesk-mcp-servers", "github_url": "https://github.com/Joe-Spencer/fusion-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx fusion-mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "autodesk", "fusion360", "cad", "3d-modeling", "engineering", "manufacturing" ], "use_cases": [ "Create and modify 3D CAD models in Fusion 360 through conversations", "Automate parametric design and engineering workflows", "Execute Fusion 360 API commands via natural language" ], "health": "active" }, { "id": "canvas-lms-mcp", "name": "Canvas LMS MCP", "description": "MCP server for Canvas LMS with 88 tools for managing courses, assignments, discussions, grades, and analytics for students and educators.", "category": "productivity", "endpoint": "uvx canvas-mcp-server", "homepage_url": "https://github.com/vishalsachdev/canvas-mcp", "github_url": "https://github.com/vishalsachdev/canvas-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx canvas-mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "canvas", "lms", "education", "courses", "grading", "students" ], "use_cases": [ "Manage Canvas LMS courses, assignments, and grades via AI", "Automate student enrollment and course content management", "Query analytics and generate reports for educators" ], "health": "active" }, { "id": "home-assistant-mcp", "name": "Home Assistant MCP", "description": "Official Home Assistant MCP server integration for controlling smart home devices, automations, and scenes via AI assistants.", "category": "infrastructure", "endpoint": "uvx home-assistant-mcp-server", "homepage_url": "https://www.home-assistant.io/integrations/mcp_server/", "github_url": "https://github.com/homeassistant-ai/ha-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx home-assistant-mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "home-assistant", "smart-home", "iot", "automation", "devices" ], "use_cases": [ "Control smart home devices and scenes through natural language", "Create and manage home automations with AI assistance", "Query device states and sensor data across your smart home" ], "health": "active" }, { "id": "voidly-mcp", "name": "Voidly Censorship Intelligence MCP", "description": "MCP server for the Voidly censorship intelligence platform — 83 tools covering 126 countries with 19.6M+ samples and real-time risk data.", "category": "data", "endpoint": "npx -y @voidly/mcp-server", "homepage_url": "https://voidly.ai", "github_url": "https://github.com/voidly-ai/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @voidly/mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "censorship", "intelligence", "privacy", "geopolitics", "risk", "data" ], "use_cases": [ "Query global censorship indexes and country-level blocking data", "Check if specific domains are blocked in target countries", "Forecast censorship risk and analyze internet freedom trends" ], "health": "active" }, { "id": "autodesk-help-mcp", "name": "Autodesk Product Help MCP", "description": "Official Autodesk read-only MCP server providing AI access to product documentation across 110+ Autodesk products.", "category": "productivity", "endpoint": "https://help.autodesk.com/mcp", "homepage_url": "https://help.autodesk.com/view/ADSKMCP/ENU/", "github_url": "https://github.com/autodesk", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "npx -y @anthropic-ai/mcpb", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "autodesk", "documentation", "help", "cad", "engineering", "reference" ], "use_cases": [ "Query Autodesk product documentation across 110+ products", "Get contextual help for Fusion, Revit, AutoCAD, and more", "Integrate Autodesk knowledge base into AI-assisted engineering workflows" ], "health": "active" }, { "id": "airbyte-mcp", "name": "Airbyte MCP", "description": "MCP server for Airbyte — the open-source ELT platform. Manage connectors, trigger syncs, inspect connection status, and orchestrate data pipelines across 300+ sources and destinations.", "category": "data", "endpoint": "npx -y @airbyte/mcp-server", "homepage_url": "https://airbyte.com", "github_url": "https://github.com/airbytehq/airbyte", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @airbyte/mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "etl", "elt", "data-pipeline", "connectors", "sync", "data-integration" ], "use_cases": [ "Trigger and monitor Airbyte sync jobs from AI agents", "Manage data connectors across 300+ sources and destinations", "Inspect pipeline health and troubleshoot failed syncs" ], "health": "active" }, { "id": "llamaindex-mcp", "name": "LlamaIndex MCP", "description": "MCP server for LlamaIndex — the leading data framework for LLM applications. Query knowledge bases, run RAG pipelines, manage document indexes, and connect agents to structured data.", "category": "ai", "endpoint": "npx -y llamaindex-mcp", "homepage_url": "https://www.llamaindex.ai", "github_url": "https://github.com/run-llama/llama_index", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install llama-index-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "rag", "llm", "knowledge-base", "vector-search", "document-indexing", "agents" ], "use_cases": [ "Query document indexes and knowledge bases via natural language", "Build and manage RAG pipelines for agent memory", "Connect agents to structured and unstructured enterprise data" ], "health": "active" }, { "id": "polygon-mcp", "name": "Polygon.io MCP", "description": "MCP server for Polygon.io — real-time and historical financial market data. Access stock tickers, options chains, crypto prices, forex rates, and earnings data for financial agents.", "category": "data", "endpoint": "npx -y @polygon.io/mcp-server", "homepage_url": "https://polygon.io", "github_url": "https://github.com/polygon-io/client-js", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @polygon.io/mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "finance", "stocks", "market-data", "crypto", "options", "forex", "real-time" ], "use_cases": [ "Fetch real-time and historical stock, crypto, and forex prices", "Query options chains and earnings calendars for financial agents", "Build market-aware AI workflows with live financial data" ], "health": "active" }, { "id": "metabase-mcp", "name": "Metabase MCP", "description": "MCP server for Metabase — the open-source BI and analytics platform. Run questions, access dashboards, query databases, and surface business metrics for AI agents.", "category": "data", "endpoint": "npx -y metabase-mcp", "homepage_url": "https://www.metabase.com", "github_url": "https://github.com/metabase/metabase", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y metabase-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "bi", "analytics", "dashboards", "sql", "business-intelligence", "reporting" ], "use_cases": [ "Query Metabase dashboards and saved questions from agents", "Surface business KPIs and metrics in AI workflows", "Run ad hoc SQL questions against connected databases" ], "health": "active" }, { "id": "strapi-mcp", "name": "Strapi MCP", "description": "MCP server for Strapi — the leading open-source headless CMS. Create, read, update, and delete content types, manage media, and integrate AI agents with Strapi-powered content workflows.", "category": "web", "endpoint": "npx -y strapi-mcp", "homepage_url": "https://strapi.io", "github_url": "https://github.com/strapi/strapi", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y strapi-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "cms", "headless", "content", "api", "media", "strapi" ], "use_cases": [ "Create and publish content in Strapi from AI agents", "Manage media uploads and content type schemas", "Automate content workflows across Strapi-powered sites" ], "health": "active" }, { "id": "deel-mcp", "name": "Deel MCP", "description": "MCP server for Deel — the global HR and payroll platform. Access contractor profiles, run payroll queries, manage compliance documents, and automate global workforce operations.", "category": "productivity", "endpoint": "npx -y @deel/mcp-server", "homepage_url": "https://www.deel.com", "github_url": "https://github.com/deel-ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @deel/mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "hr", "payroll", "global", "contractors", "compliance", "workforce" ], "use_cases": [ "Query contractor and employee records across global teams", "Automate payroll status checks and compliance document requests", "Surface workforce data for HR and finance AI workflows" ], "health": "active" }, { "id": "haystack-mcp", "name": "Haystack MCP", "description": "MCP server for Haystack by deepset — the open-source NLP framework for building production-grade RAG and search pipelines. Run pipelines, query document stores, and manage AI components.", "category": "ai", "endpoint": "pip install haystack-mcp", "homepage_url": "https://haystack.deepset.ai", "github_url": "https://github.com/deepset-ai/haystack", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install haystack-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "nlp", "rag", "search", "pipelines", "document-store", "qa" ], "use_cases": [ "Run Haystack NLP pipelines from agent workflows", "Query document stores for retrieval-augmented generation", "Manage and evaluate AI pipeline components programmatically" ], "health": "active" }, { "id": "activecampaign-mcp", "name": "ActiveCampaign MCP", "description": "MCP server for ActiveCampaign — the customer experience automation platform. Manage contacts, trigger automations, track deals, and power email marketing workflows from AI agents.", "category": "communication", "endpoint": "npx -y activecampaign-mcp", "homepage_url": "https://www.activecampaign.com", "github_url": "https://github.com/ActiveCampaign", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y activecampaign-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "email", "automation", "crm", "marketing", "contacts", "campaigns" ], "use_cases": [ "Create and update contacts and deals in ActiveCampaign", "Trigger email automations and sequences from agent workflows", "Query campaign performance and contact engagement data" ], "health": "active" }, { "id": "cerebras-mcp", "name": "Cerebras MCP", "description": "MCP server for the Cerebras Inference API — the world's fastest AI inference engine. Run Llama and other open models at 1,800+ tokens/second for latency-sensitive agentic workloads.", "category": "ai", "endpoint": "npx -y @cerebras/mcp-server", "homepage_url": "https://inference.cerebras.ai", "github_url": "https://github.com/Cerebras", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @cerebras/mcp-server", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "inference", "llm", "llama", "fast-inference", "open-models", "cerebras" ], "use_cases": [ "Run Llama 3 and other open models at ultra-low latency", "Power latency-sensitive agent loops with 1800+ token/s throughput", "Route cost-sensitive workloads to fast open-model inference" ], "health": "active" }, { "id": "appsmith-mcp", "name": "Appsmith MCP", "description": "MCP server for Appsmith — the open-source low-code platform for building internal tools. Create widgets, manage datasources, deploy apps, and automate internal tool workflows with AI.", "category": "productivity", "endpoint": "npx -y appsmith-mcp", "homepage_url": "https://www.appsmith.com", "github_url": "https://github.com/appsmithorg/appsmith", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y appsmith-mcp", "added": "2026-05-11", "updated": "2026-05-11", "tags": [ "low-code", "internal-tools", "dashboards", "apps", "no-code", "open-source" ], "use_cases": [ "Build and deploy internal tools with AI-generated Appsmith apps", "Connect datasources and manage widgets programmatically", "Automate internal workflow creation for ops and engineering teams" ], "health": "active" }, { "id": "finix-mcp", "name": "Finix", "description": "Payments infrastructure MCP server from Finix. Exposes payment processing API and documentation to AI assistants for merchant onboarding, payouts, and transaction management.", "category": "payments", "endpoint": "npx finix-mcp-server", "homepage_url": "https://finix.com", "github_url": "https://github.com/finix-payments", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx finix-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "payments", "fintech", "merchant-onboarding", "transactions", "payouts" ], "use_cases": [ "Process payments and manage merchant onboarding through AI assistants", "Query transaction history and generate payment reports via natural language", "Prototype payment flows using Finix sandbox directly from Claude or Copilot" ], "health": "active" }, { "id": "payu-mcp", "name": "PayU", "description": "PayU payments MCP server for AI-assisted payment workflows. Create payment links, retrieve transaction details, access invoices, and filter by status or payment mode.", "category": "payments", "endpoint": "npx payu-mcp-server", "homepage_url": "https://payu.in", "github_url": "https://github.com/payu-intrepos/payu-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx payu-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "payments", "fintech", "invoicing", "india", "payment-links" ], "use_cases": [ "Create payment links and retrieve transaction details through AI assistants", "Filter and analyze transactions by status, payment mode, or source", "Access invoice information and automate payment reporting workflows" ], "health": "active" }, { "id": "duo-mcp", "name": "Cisco Duo", "description": "Cisco Duo SSO integration for MCP servers. Adds two-factor authentication and flexible security policies to MCP clients using OAuth 2.1 and OIDC standards.", "category": "identity", "endpoint": "npx @cisco/duo-mcp-server", "homepage_url": "https://duo.com/docs/sso-oauth-server-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @cisco/duo-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "identity", "sso", "2fa", "mfa", "oauth", "enterprise-security" ], "use_cases": [ "Add two-factor authentication to MCP server connections for enterprise security", "Enforce SSO policies across AI agent access to MCP tools", "Secure agentic AI actions with Duo Push or passkey verification" ], "health": "active" }, { "id": "propelauth-mcp", "name": "PropelAuth", "description": "MCP authentication provider using OAuth 2.1. Enables secure user authentication for remote MCP servers with dynamic client registration, token introspection, and scoped access control.", "category": "identity", "endpoint": "npx @propelauth/mcp-server", "homepage_url": "https://docs.propelauth.com/mcp-authentication/overview", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx @propelauth/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "identity", "authentication", "oauth", "mcp-auth", "token-management" ], "use_cases": [ "Authenticate users connecting to remote MCP servers via OAuth 2.1", "Manage scoped access tokens for multi-tenant MCP deployments", "Integrate MCP server auth with existing PropelAuth user management" ], "health": "active" }, { "id": "ibm-qradar-mcp", "name": "IBM QRadar", "description": "Official IBM QRadar SIEM MCP server. Search offenses, run AQL queries, manage reference sets, and investigate security incidents through AI agents.", "category": "infrastructure", "endpoint": "npx @ibm/qradar-mcp-server", "homepage_url": "https://github.com/IBM/mcp", "github_url": "https://github.com/IBM/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @ibm/qradar-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "security", "siem", "incident-response", "threat-detection", "ibm" ], "use_cases": [ "Search and triage QRadar security offenses through AI-assisted investigation", "Run AQL queries against SIEM data using natural language", "Manage reference sets and automate security incident response workflows" ], "health": "active" }, { "id": "ibmi-mcp", "name": "IBM i", "description": "MCP server for IBM i systems. Enables AI agents to interact with IBM i through SQL-based tools for performance monitoring, security auditing, and database administration.", "category": "infrastructure", "endpoint": "npx @ibm/ibmi-mcp-server", "homepage_url": "https://github.com/IBM/ibmi-mcp-server", "github_url": "https://github.com/IBM/ibmi-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @ibm/ibmi-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "ibm", "mainframe", "database", "monitoring", "enterprise" ], "use_cases": [ "Monitor IBM i system performance and health through AI agents", "Run SQL queries and database administration tasks via natural language", "Automate security auditing and compliance checks on IBM i systems" ], "health": "active" }, { "id": "finnhub-mcp", "name": "FinnHub", "description": "Real-time financial data streaming MCP server. Integrates with the FinnHub API for live stock prices, company fundamentals, and market data through both SSE and stdio transport.", "category": "data", "endpoint": "npx finnhub-mcp-server", "homepage_url": "https://finnhub.io", "github_url": "https://github.com/SalZaki/finnhub-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx finnhub-mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "finance", "stocks", "market-data", "real-time", "streaming" ], "use_cases": [ "Stream real-time stock prices and market data into AI agent workflows", "Query company fundamentals and financial metrics through natural language", "Build AI-powered trading analysis tools with live market data" ], "health": "active" }, { "id": "datagouv-mcp", "name": "data.gouv.fr", "description": "Official French national Open Data platform MCP server. Search, explore, and analyze datasets from data.gouv.fr directly through AI conversation.", "category": "data", "endpoint": "npx @datagouv/mcp-server", "homepage_url": "https://data.gouv.fr", "github_url": "https://github.com/datagouv/datagouv-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @datagouv/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "open-data", "government", "france", "datasets", "public-data" ], "use_cases": [ "Search and explore French national open datasets through AI assistants", "Analyze government data from data.gouv.fr using natural language queries", "Build research workflows that pull live data from the French open data platform" ], "health": "active" }, { "id": "atlassian-rovo-mcp", "name": "Atlassian Rovo MCP", "description": "Official MCP server for Atlassian Rovo — the AI-powered enterprise search and knowledge platform. Search across Jira, Confluence, and connected apps, surface institutional knowledge, and automate work discovery for agents.", "category": "productivity", "endpoint": "npx -y @atlassian/rovo-mcp", "homepage_url": "https://www.atlassian.com/rovo", "github_url": "https://github.com/atlassian/atlassian-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx -y @atlassian/rovo-mcp", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "atlassian", "enterprise-search", "knowledge", "jira", "confluence", "rovo" ], "use_cases": [ "Search across all Atlassian products and connected apps from AI agents", "Surface institutional knowledge and past decisions for context-aware agents", "Automate work discovery and routing across Jira, Confluence, and Compass" ], "health": "active" }, { "id": "gusto-mcp", "name": "Gusto MCP", "description": "MCP server for Gusto — the payroll, benefits, and HR platform for small businesses. Query employee records, run payroll reports, check benefits enrollment, and automate HR workflows from AI agents.", "category": "productivity", "endpoint": "npx -y @gusto/mcp-server", "homepage_url": "https://gusto.com", "github_url": "https://github.com/Gusto", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @gusto/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "hr", "payroll", "benefits", "small-business", "employees", "gusto" ], "use_cases": [ "Query payroll status and employee compensation data for finance agents", "Automate benefits enrollment checks and HR record lookups", "Surface headcount and team structure data for planning workflows" ], "health": "active" }, { "id": "heap-mcp", "name": "Heap MCP", "description": "MCP server for Heap — the digital insights platform that auto-captures every user interaction. Query funnels, session data, behavioral segments, and conversion metrics from AI agents without manual event tracking.", "category": "data", "endpoint": "npx -y @heap/mcp-server", "homepage_url": "https://heap.io", "github_url": "https://github.com/heap", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @heap/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "analytics", "product-analytics", "user-behavior", "funnels", "sessions", "conversion" ], "use_cases": [ "Query user behavior funnels and drop-off points from AI product agents", "Surface behavioral segments and cohort analysis for growth workflows", "Automate conversion metric reporting and anomaly detection" ], "health": "active" }, { "id": "monte-carlo-mcp", "name": "Monte Carlo MCP", "description": "MCP server for Monte Carlo — the data observability platform. Monitor data pipeline health, query data incidents, track lineage, and automate data quality alerting from AI agents.", "category": "data", "endpoint": "npx -y @montecarlo/mcp-server", "homepage_url": "https://www.montecarlodata.com", "github_url": "https://github.com/monte-carlo-data", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @montecarlo/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "data-observability", "data-quality", "lineage", "incidents", "pipelines", "monitoring" ], "use_cases": [ "Monitor data pipeline health and detect anomalies from AI data agents", "Query data incident history and root cause analysis automatically", "Track data lineage and impact analysis for schema changes" ], "health": "active" }, { "id": "hightouch-mcp", "name": "Hightouch MCP", "description": "MCP server for Hightouch — the data activation and reverse ETL platform. Sync warehouse data to CRMs, ad platforms, and business tools, and trigger audience syncs from AI agents.", "category": "data", "endpoint": "npx -y @hightouch/mcp-server", "homepage_url": "https://hightouch.com", "github_url": "https://github.com/HighTouchData", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @hightouch/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "reverse-etl", "data-activation", "audience-sync", "warehouse", "crm", "marketing" ], "use_cases": [ "Trigger audience syncs from your data warehouse to ad platforms via agents", "Automate CRM and business tool updates based on warehouse data", "Query sync status and data model health from AI operations agents" ], "health": "active" }, { "id": "livekit-mcp", "name": "LiveKit MCP", "description": "MCP server for LiveKit — the open-source real-time audio/video infrastructure. Create rooms, manage participants, stream audio to AI agents, and build voice-enabled agent pipelines with WebRTC.", "category": "communication", "endpoint": "npx -y @livekit/mcp-server", "homepage_url": "https://livekit.io", "github_url": "https://github.com/livekit/livekit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @livekit/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "real-time", "audio", "video", "webrtc", "voice-agents", "streaming" ], "use_cases": [ "Create and manage LiveKit rooms for real-time AI voice agent pipelines", "Stream audio to speech-to-text agents and back via WebRTC", "Build voice-enabled agentic workflows with real-time participant management" ], "health": "active" }, { "id": "trigger-dev-mcp", "name": "Trigger.dev MCP", "description": "MCP server for Trigger.dev — the open-source background jobs and workflow platform. Trigger jobs, monitor runs, inspect logs, and manage scheduled tasks from AI agents without polling or webhooks.", "category": "infrastructure", "endpoint": "npx -y @trigger.dev/mcp-server", "homepage_url": "https://trigger.dev", "github_url": "https://github.com/triggerdotdev/trigger.dev", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @trigger.dev/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "background-jobs", "workflows", "queues", "scheduling", "open-source", "serverless" ], "use_cases": [ "Trigger and monitor background jobs from AI agents without polling", "Inspect job run history and logs for debugging and observability", "Manage scheduled tasks and cron jobs programmatically from agent workflows" ], "health": "active" }, { "id": "pendo-mcp", "name": "Pendo MCP", "description": "MCP server for Pendo — the product experience platform. Query feature adoption, NPS scores, user guides, and in-app analytics from AI agents to automate product insights and customer success workflows.", "category": "data", "endpoint": "npx -y @pendo/mcp-server", "homepage_url": "https://www.pendo.io", "github_url": "https://github.com/pendo-io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @pendo/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "product-analytics", "nps", "feature-adoption", "user-guides", "in-app", "customer-success" ], "use_cases": [ "Query feature adoption rates and user engagement metrics from AI agents", "Surface NPS trends and customer sentiment for product decision workflows", "Automate in-app guide targeting based on behavioral segment data" ], "health": "active" }, { "id": "courier-mcp", "name": "Courier MCP", "description": "MCP server for Courier — the multi-channel notification infrastructure platform. Send and manage notifications across email, SMS, push, Slack, and 20+ channels from a single AI-accessible API.", "category": "communication", "endpoint": "npx -y @trycourier/mcp-server", "homepage_url": "https://www.courier.com", "github_url": "https://github.com/trycourier", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @trycourier/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "notifications", "multi-channel", "email", "sms", "push", "slack" ], "use_cases": [ "Send multi-channel notifications from AI agents without managing integrations", "Manage notification preferences and delivery routing programmatically", "Track notification delivery status and engagement across all channels" ], "health": "active" }, { "id": "census-mcp", "name": "Census MCP", "description": "MCP server for Census — the operational analytics and data activation platform. Sync warehouse data to business tools, trigger audience updates, and manage data models from AI agents.", "category": "data", "endpoint": "npx -y @getcensus/mcp-server", "homepage_url": "https://www.getcensus.com", "github_url": "https://github.com/sutrolabs/census-embedded-demo", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @getcensus/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "data-activation", "reverse-etl", "operational-analytics", "warehouse", "syncs" ], "use_cases": [ "Trigger data syncs from warehouse to business tools via AI agents", "Query sync run status and model health for operational workflows", "Manage audience segments and activation targets programmatically" ], "health": "active" }, { "id": "fivetran-mcp", "name": "Fivetran MCP", "description": "MCP server for Fivetran — the automated data movement platform. Trigger and monitor ELT pipeline syncs, inspect connector health, query sync logs, and manage data source connections from AI agents.", "category": "data", "endpoint": "npx -y @fivetran/mcp-server", "homepage_url": "https://fivetran.com", "github_url": "https://github.com/fivetran", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @fivetran/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "elt", "data-pipeline", "connectors", "data-movement", "warehouse", "sync" ], "use_cases": [ "Trigger and monitor ELT syncs from AI data pipeline agents", "Inspect connector health and diagnose sync failures automatically", "Query pipeline run history and schema change logs for data agents" ], "health": "active" }, { "id": "launchdarkly-mcp", "name": "LaunchDarkly MCP", "description": "MCP server for LaunchDarkly — the feature management platform. Query and update feature flags, manage targeting rules, roll out features progressively, and automate flag lifecycle from AI agents.", "category": "infrastructure", "endpoint": "npx -y @launchdarkly/mcp-server", "homepage_url": "https://launchdarkly.com", "github_url": "https://github.com/launchdarkly", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @launchdarkly/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "feature-flags", "feature-management", "rollouts", "targeting", "experimentation", "devops" ], "use_cases": [ "Query and update feature flags from AI deployment and ops agents", "Automate progressive rollouts and targeting rule changes", "Kill-switch features instantly in response to incidents via agent workflows" ], "health": "active" }, { "id": "statsig-mcp", "name": "Statsig MCP", "description": "MCP server for Statsig — the feature flagging and experimentation platform built for AI-native companies. Run A/B tests, manage feature gates, query experiment results, and automate rollout decisions from agents.", "category": "infrastructure", "endpoint": "npx -y @statsig/mcp-server", "homepage_url": "https://statsig.com", "github_url": "https://github.com/statsig-io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @statsig/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "feature-flags", "experimentation", "a-b-testing", "rollouts", "metrics", "product" ], "use_cases": [ "Query A/B experiment results and statistical significance from AI product agents", "Manage feature gate targeting and rollout percentages programmatically", "Automate experiment lifecycle from hypothesis to ship via agent workflows" ], "health": "active" }, { "id": "mlflow-mcp", "name": "MLflow MCP", "description": "MCP server for MLflow — the open-source ML lifecycle platform by Databricks. Log experiments, compare runs, register models, manage the model registry, and track artifacts from AI and ML pipeline agents.", "category": "ai", "endpoint": "npx -y @mlflow/mcp-server", "homepage_url": "https://mlflow.org", "github_url": "https://github.com/mlflow/mlflow", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @mlflow/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "ml-lifecycle", "experiment-tracking", "model-registry", "artifacts", "open-source", "databricks" ], "use_cases": [ "Log and compare ML experiment runs from AI training pipeline agents", "Query model registry and promote models across staging and production", "Track artifacts and metrics across model development workflows automatically" ], "health": "active" }, { "id": "logfire-mcp", "name": "Logfire MCP", "description": "MCP server for Logfire — Pydantic's OpenTelemetry-based observability platform. Query traces, logs, and spans from Python and AI applications, inspect errors, and monitor agent runtime behavior in real time.", "category": "infrastructure", "endpoint": "npx -y @pydantic/logfire-mcp", "homepage_url": "https://logfire.pydantic.dev", "github_url": "https://github.com/pydantic/logfire-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @pydantic/logfire-mcp", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "observability", "opentelemetry", "tracing", "logs", "python", "pydantic", "ai-agents" ], "use_cases": [ "Query traces and spans from AI agent runs to debug production issues", "Inspect Python application errors and performance bottlenecks from agents", "Monitor AI agent behavior and latency in real time via OpenTelemetry" ], "health": "active" }, { "id": "storyblok-mcp", "name": "Storyblok MCP", "description": "MCP server for Storyblok — the headless CMS with visual editing. Manage content stories, components, and spaces; create and publish content; and query the content delivery API from AI agents.", "category": "productivity", "endpoint": "npx -y @storyblok/mcp-server", "homepage_url": "https://www.storyblok.com", "github_url": "https://github.com/storyblok", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @storyblok/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "headless-cms", "content", "visual-editor", "stories", "publishing", "jamstack" ], "use_cases": [ "Create and publish content stories from AI content generation agents", "Query and update CMS components and structured content programmatically", "Automate content localization and publishing workflows across spaces" ], "health": "active" }, { "id": "fullstory-mcp", "name": "FullStory MCP", "description": "MCP server for FullStory — the behavioral data and digital experience platform. Query session replays, user journeys, rage clicks, and conversion funnels to surface UX insights from AI product and support agents.", "category": "data", "endpoint": "npx -y @fullstory/mcp-server", "homepage_url": "https://www.fullstory.com", "github_url": "https://github.com/fullstorydev", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @fullstory/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "session-replay", "digital-experience", "user-behavior", "ux-analytics", "rage-clicks", "funnels" ], "use_cases": [ "Query user session data and rage click reports from AI UX research agents", "Surface friction points and drop-off patterns for product improvement workflows", "Automate customer support context by pulling session history on demand" ], "health": "active" }, { "id": "drata-mcp", "name": "Drata MCP", "description": "MCP server for Drata — the compliance automation platform for SOC 2, ISO 27001, HIPAA, and GDPR. Query controls, monitor evidence collection, track audit readiness, and automate compliance workflows from AI agents.", "category": "infrastructure", "endpoint": "npx -y @drata/mcp-server", "homepage_url": "https://drata.com", "github_url": "https://github.com/drata", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @drata/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "compliance", "soc2", "gdpr", "hipaa", "iso27001", "audit", "security" ], "use_cases": [ "Monitor compliance control status and evidence gaps from AI security agents", "Track audit readiness across frameworks like SOC 2 and ISO 27001", "Automate evidence collection reminders and policy update workflows" ], "health": "active" }, { "id": "agora-mcp", "name": "Agora MCP", "description": "MCP server for Agora — the real-time voice, video, and interactive live streaming platform. Manage channels, tokens, cloud recording, and real-time transcription from AI agents building voice-enabled workflows.", "category": "communication", "endpoint": "npx -y @agora-io/mcp-server", "homepage_url": "https://www.agora.io", "github_url": "https://github.com/AgoraIO", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @agora-io/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "real-time", "voice", "video", "live-streaming", "webrtc", "transcription" ], "use_cases": [ "Generate tokens and manage Agora channels for real-time AI voice agents", "Start cloud recordings and real-time transcription from agent workflows", "Monitor active channel participants and stream quality from AI ops agents" ], "health": "active" }, { "id": "brex-mcp", "name": "Brex MCP", "description": "MCP server for Brex — the corporate cards and spend management platform for startups and enterprises. Query transactions, manage budgets, track vendor spend, and automate expense workflows from AI finance agents.", "category": "payments", "endpoint": "npx -y @brex/mcp-server", "homepage_url": "https://www.brex.com", "github_url": "https://github.com/brexhq", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @brex/mcp-server", "added": "2026-05-12", "updated": "2026-05-12", "tags": [ "corporate-cards", "spend-management", "expenses", "budgets", "finance", "startups" ], "use_cases": [ "Query transaction history and vendor spend from AI finance and ops agents", "Monitor budget utilization and flag anomalous spend patterns automatically", "Automate expense categorization and reporting workflows for finance teams" ], "health": "active" }, { "id": "canva-mcp", "name": "Canva MCP", "description": "Official Canva MCP server for AI-powered design creation and editing. Enables agents to create on-brand designs, search brand assets, manage templates, export files, and collaborate on visual content through natural language.", "category": "productivity", "endpoint": "https://mcp.canva.com/mcp", "homepage_url": "https://www.canva.com/ai-connector/", "github_url": "https://www.canva.dev/docs/mcp/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "Add https://mcp.canva.com/mcp as a remote MCP server in your MCP client configuration", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "design", "creative", "visual", "brand", "templates", "official" ], "use_cases": [ "Create on-brand presentations and social graphics from a prompt", "Search and reuse brand assets across design projects from AI assistants", "Export designs to multiple formats for publishing through natural language" ], "health": "active" }, { "id": "hex-mcp", "name": "Hex MCP", "description": "Official Hex analytics platform MCP server. Lets AI agents search Hex projects, create and continue Thread conversations, and explore data through natural language queries connected to your data warehouse.", "category": "data", "endpoint": "https://app.hex.tech/mcp", "homepage_url": "https://hex.tech", "github_url": "https://learn.hex.tech/docs/administration/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "Add https://app.hex.tech/mcp as a remote MCP server in Claude Desktop or other MCP client", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "analytics", "notebooks", "data-exploration", "sql", "python", "official" ], "use_cases": [ "Query your data warehouse using natural language through Hex", "Search and share Hex analytics projects from your AI assistant", "Create and iterate on data analyses without leaving your chat interface" ], "health": "active" }, { "id": "plain-mcp", "name": "Plain MCP", "description": "Official Plain.com customer support MCP server. Provides 30 tools spanning support threads, customer records, tenants, and help center content — enabling agents to search, reply, assign, and resolve support issues from any MCP-compatible AI tool.", "category": "productivity", "endpoint": "https://mcp.plain.com/mcp", "homepage_url": "https://www.plain.com", "github_url": "https://www.plain.com/blog/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "Add https://mcp.plain.com/mcp as a remote MCP server in your MCP client", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "customer-support", "tickets", "help-desk", "threads", "official" ], "use_cases": [ "Search and triage support threads from your AI coding assistant", "Reply to customer issues and update ticket status through natural language", "Pull customer history and tenant data for context during support sessions" ], "health": "active" }, { "id": "ramp-mcp", "name": "Ramp MCP", "description": "Official Ramp corporate card and spend management MCP server. Gives AI agents secure access to transaction data, expense policies, card limits, and bill pay — enabling month-end close, reconciliation, and spend analysis through natural language.", "category": "payments", "endpoint": "npx ramp-mcp", "homepage_url": "https://ramp.com", "github_url": "https://github.com/ramp-public/ramp-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx ramp-mcp", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "finance", "expense-management", "corporate-cards", "spend-analysis", "official" ], "use_cases": [ "Run month-end expense reconciliation with an AI assistant", "Analyze corporate card spend patterns and policy compliance", "Approve and manage expense reports through natural language" ], "health": "active" }, { "id": "dagster-mcp", "name": "Dagster MCP", "description": "MCP server for the Dagster data orchestration platform. Enables AI agents to explore data pipelines, monitor asset materialization runs, inspect job status, and interact with your Dagster instance through natural language.", "category": "data", "endpoint": "pip install mcp-server-dagster", "homepage_url": "https://dagster.io", "github_url": "https://github.com/kyryl-opens-ml/mcp-server-dagster", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install mcp-server-dagster", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "data-pipelines", "orchestration", "etl", "asset-catalog", "monitoring" ], "use_cases": [ "Monitor data pipeline runs and diagnose failures with an AI agent", "Explore and document your Dagster asset catalog through natural language", "Trigger pipeline runs and check asset materialization status" ], "health": "active" }, { "id": "freshdesk-mcp", "name": "Freshdesk MCP", "description": "MCP server for the Freshdesk customer support platform. Provides tools for managing tickets, contacts, companies, agents, and canned responses — enabling AI agents to search, create, update, and resolve support tickets.", "category": "productivity", "endpoint": "npx freshdeck-mcp", "homepage_url": "https://freshdesk.com", "github_url": "https://github.com/Enreign/freshdeck-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx freshdeck-mcp", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "customer-support", "tickets", "helpdesk", "freshworks" ], "use_cases": [ "Create and update support tickets from an AI assistant", "Search customer history and open issues during support sessions", "Manage agent assignments and escalate tickets based on priority" ], "health": "active" }, { "id": "bright-data-mcp", "name": "Bright Data MCP", "description": "Official Bright Data web data infrastructure MCP server. Routes scraping requests through 400M+ residential IPs for anti-blocking. Provides SERP API, scraping browser, and structured datasets for high-difficulty web data extraction.", "category": "web", "endpoint": "npx @brightdata/mcp", "homepage_url": "https://brightdata.com", "github_url": "https://github.com/luminati-io/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @brightdata/mcp", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "web-scraping", "proxy", "serp", "data-extraction", "residential-ips", "official" ], "use_cases": [ "Scrape high-block targets using residential proxy infrastructure", "Extract SERP data for competitive intelligence at scale", "Access structured web datasets without building custom scrapers" ], "health": "active" }, { "id": "jina-mcp", "name": "Jina Reader MCP", "description": "Jina AI Reader MCP server. Converts any URL to clean, LLM-optimized markdown with a single tool call. Ideal for RAG pipelines, content summarization, and feeding web content into agent workflows without scraper configuration.", "category": "web", "endpoint": "npx @jina-ai/mcp-server-reader", "homepage_url": "https://jina.ai/reader", "github_url": "https://github.com/jina-ai/reader", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @jina-ai/mcp-server-reader", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "web-reading", "content-extraction", "rag", "markdown", "url-to-text", "official" ], "use_cases": [ "Feed any URL into an agent as clean markdown without manual scraping", "Extract article content for summarization or RAG pipelines", "Convert web pages to structured text for downstream analysis" ], "health": "active" }, { "id": "aws-agent-toolkit-mcp", "name": "AWS Agent Toolkit MCP", "description": "Official unified AWS Agent Toolkit MCP server (GA May 2026). A single tool to execute any of 15,000+ AWS API operations with IAM-based guardrails, CloudWatch metrics, CloudTrail logging, and sandboxed Python execution for multi-step workflows.", "category": "infrastructure", "endpoint": "npx @aws/mcp-server", "homepage_url": "https://aws.amazon.com/blogs/aws/the-aws-mcp-server-is-now-generally-available/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @aws/mcp-server", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "aws", "cloud", "iam", "api", "infrastructure", "official", "ga" ], "use_cases": [ "Execute any AWS API operation through natural language with full IAM guardrails", "Run sandboxed Python scripts against AWS services for multi-step agentic workflows", "Query AWS documentation and best practices in-context during cloud development" ], "health": "active" }, { "id": "workato-mcp", "name": "Workato MCP", "description": "Official Workato enterprise automation MCP server. Connects AI agents to Salesforce, SAP, Workday, ServiceNow, and 1,200+ enterprise apps through Workato's automation engine — without writing custom integrations.", "category": "productivity", "endpoint": "https://www.workato.com/mcp", "homepage_url": "https://workato.com", "github_url": "https://github.com/workato", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "Configure via Workato platform under MCP Server settings", "added": "2026-05-13", "updated": "2026-05-13", "tags": [ "enterprise-automation", "integrations", "workflow", "rpa", "official" ], "use_cases": [ "Connect AI agents to enterprise systems like SAP, Workday, and Salesforce", "Trigger automated workflows across 1,200+ enterprise apps through natural language", "Build agentic automation pipelines without writing custom integration code" ], "health": "active" }, { "id": "shoppable-mcp", "name": "Shoppable", "description": "Universal checkout MCP server for AI-driven commerce. Connects AI assistants to 500M+ product SKUs across multiple brands with a single checkout URL. Agents can search products, build multi-merchant carts, and complete purchases within conversation.", "category": "payments", "endpoint": "npx @shoppable/mcp-server", "homepage_url": "https://www.shoppable.com", "github_url": "https://github.com/shoppable/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @shoppable/mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "e-commerce", "checkout", "shopping", "multi-brand", "conversational-commerce" ], "use_cases": [ "Search and purchase products across 500M+ SKUs from within an AI conversation", "Build multi-brand shopping carts with unified checkout", "Enable conversational commerce for publishers and retailers" ], "health": "active" }, { "id": "tiktok-ads-mcp", "name": "TikTok Ads", "description": "Official MCP server for TikTok Ads Manager. Enables AI agents to create, manage, and optimize ad campaigns, set bids, adjust budgets, modify targeting, upload creatives, and monitor performance without manual dashboard intervention.", "category": "web", "endpoint": "npx @tiktok/ads-mcp-server", "homepage_url": "https://ads.tiktok.com", "github_url": "https://github.com/AdsMCP/tiktok-ads-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @tiktok/ads-mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "advertising", "tiktok", "social-media", "campaign-management", "marketing" ], "use_cases": [ "Create and launch TikTok ad campaigns through AI agents", "Optimize bid strategies and budgets autonomously", "Monitor campaign performance and generate reports via MCP" ], "health": "active" }, { "id": "mobbin-mcp", "name": "Mobbin", "description": "MCP server connecting AI agents to 621,500+ real app screens from Mobbin's design reference library. Search by app name, screen type, UI pattern, or flow to get real-world design references directly in Claude, Cursor, or other MCP-compatible tools.", "category": "media", "endpoint": "npx @mobbin/mcp-server", "homepage_url": "https://mobbin.com", "github_url": "https://github.com/nicobrinkkemper/mobbin-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @mobbin/mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "design", "ui-patterns", "app-screens", "reference", "mobile-design" ], "use_cases": [ "Pull real app screen references when designing new features", "Search UI patterns across 621K+ screens by flow type or component", "Ground AI design suggestions in real-world production apps" ], "health": "active" }, { "id": "workable-mcp", "name": "Workable", "description": "Official MCP server for Workable HR and recruiting platform. Gives AI assistants read and write access to jobs, candidates, pipeline stages, offers, requisitions, employees, time tracking, time-off records, and calendar events.", "category": "productivity", "endpoint": "npx @workable/mcp-server", "homepage_url": "https://www.workable.com", "github_url": "https://github.com/workable/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @workable/mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "hr", "recruiting", "ats", "hiring", "workforce" ], "use_cases": [ "Query candidate pipelines and hiring status across open positions", "Automate recruiting workflows like offer generation and stage transitions", "Access employee time tracking and time-off data for workforce planning" ], "health": "active" }, { "id": "powerdmarc-mcp", "name": "PowerDMARC", "description": "MCP server for PowerDMARC email authentication and domain security platform. AI assistants can read DMARC, SPF, and DKIM reports, monitor domain reputation, check email authentication status, and act on live security data.", "category": "identity", "endpoint": "npx @powerdmarc/mcp-server", "homepage_url": "https://powerdmarc.com", "github_url": "https://github.com/powerdmarc/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @powerdmarc/mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "email-security", "dmarc", "spf", "dkim", "domain-security" ], "use_cases": [ "Monitor DMARC compliance and email authentication status via AI agents", "Investigate domain spoofing attempts and email deliverability issues", "Generate reports on SPF, DKIM, and DMARC alignment for security audits" ], "health": "active" }, { "id": "google-ads-mcp", "name": "Google Ads", "description": "Open-source MCP server for Google Ads platform. Enables AI agents to create and manage ad campaigns, adjust bids, configure targeting, monitor performance metrics, and generate reports across Search, Display, and YouTube ad networks.", "category": "web", "endpoint": "npx @google/ads-mcp-server", "homepage_url": "https://ads.google.com", "github_url": "https://github.com/google/ads-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @google/ads-mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "advertising", "google", "sem", "ppc", "campaign-management" ], "use_cases": [ "Create and optimize Google Ads campaigns through AI agents", "Pull performance reports across Search, Display, and YouTube networks", "Automate bid management and budget allocation via MCP" ], "health": "active" }, { "id": "bigcommerce-mcp", "name": "BigCommerce Storefront", "description": "Official MCP server for BigCommerce e-commerce platform. Connects AI shopping agents to product catalogs, inventory, pricing, and storefront data. Supports building conversational commerce experiences and AI-powered product recommendations.", "category": "payments", "endpoint": "npx @bigcommerce/storefront-mcp", "homepage_url": "https://www.bigcommerce.com", "github_url": "https://github.com/bigcommerce/storefront-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @bigcommerce/storefront-mcp", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "e-commerce", "storefront", "shopping", "product-catalog", "inventory" ], "use_cases": [ "Build AI shopping agents that browse and recommend products from BigCommerce stores", "Query real-time inventory and pricing data for conversational commerce", "Automate order management and product catalog updates via AI agents" ], "health": "active" }, { "id": "gohighlevel-mcp", "name": "GoHighLevel", "description": "MCP server for GoHighLevel CRM and marketing automation platform. Provides 520+ tools across 40 categories including contacts, calendars, conversations, opportunities, invoices, payments, workflows, social media, and voice AI.", "category": "productivity", "endpoint": "npx @gohighlevel/mcp-server", "homepage_url": "https://www.gohighlevel.com", "github_url": "https://github.com/BusyBee3333/Go-High-Level-MCP-2026-Complete", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx @gohighlevel/mcp-server", "added": "2026-05-14", "updated": "2026-05-14", "tags": [ "crm", "marketing-automation", "sales", "agency", "voice-ai" ], "use_cases": [ "Manage contacts, pipelines, and opportunities across GoHighLevel accounts", "Automate marketing workflows and social media posting via AI agents", "Access invoicing, payments, and calendar data for agency operations" ], "health": "active" }, { "id": "optimizely-experimentation-mcp", "name": "Optimizely Experimentation MCP", "description": "Official remote MCP server from Optimizely for managing A/B tests, feature flags, and experimentation workflows through AI assistants.", "category": "data", "endpoint": "https://exp.mcp.opal.optimizely.com/mcp", "homepage_url": "https://www.optimizely.com/insights/blog/experimentation-mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http optimizely-exp https://exp.mcp.opal.optimizely.com/mcp", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "optimizely", "experimentation", "ab-testing", "feature-flags" ], "use_cases": [ "Manage A/B test experiments via AI assistants", "Monitor and analyze experimentation results", "Create and configure feature flags conversationally" ], "health": "active" }, { "id": "sap-fiori-mcp", "name": "SAP Fiori MCP Server", "description": "Official SAP MCP server for generating and modifying SAP Fiori applications, including pages, controller extensions, and manifest changes.", "category": "code", "endpoint": "npx --yes @sap-ux/fiori-mcp-server@latest fiori-mcp", "homepage_url": "https://github.com/SAP/open-ux-tools/tree/main/packages/fiori-mcp-server", "github_url": "https://github.com/SAP/open-ux-tools", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx --yes @sap-ux/fiori-mcp-server@latest fiori-mcp", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "sap", "fiori", "enterprise", "ui5", "erp" ], "use_cases": [ "Generate SAP Fiori applications with AI", "Modify SAP Fiori page layouts and extensions", "Scaffold enterprise UI5 components" ], "health": "active" }, { "id": "fibery-mcp", "name": "Fibery MCP Server", "description": "Official MCP server from Fibery for managing workspace databases, creating entities, and querying structured project data through AI assistants.", "category": "productivity", "endpoint": "uv tool run fibery-mcp-server", "homepage_url": "https://the.fibery.io/@public/User_Guide/Guide/Fibery-MCP-Server-401", "github_url": "https://github.com/Fibery-inc/fibery-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uv tool install fibery-mcp-server", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "fibery", "project-management", "workspace", "productivity" ], "use_cases": [ "Query and manage Fibery workspace databases", "Create and update entities via natural language", "Explore database schemas and field structures" ], "health": "active" }, { "id": "beyondtrust-pathfinder-mcp", "name": "BeyondTrust Pathfinder MCP", "description": "MCP server for identity security that exposes BeyondTrust privilege intelligence, identity risk insights, and security operations to AI agents.", "category": "identity", "endpoint": "https://pathfinder.beyondtrust.com/mcp", "homepage_url": "https://www.beyondtrust.com/blog/entry/pathfinder-ai-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "identity", "security", "privileged-access", "enterprise", "beyondtrust" ], "use_cases": [ "Query privilege intelligence and identity risk", "Integrate identity security with AI agent platforms", "Automate privileged access management workflows" ], "health": "active" }, { "id": "optimizely-cms-mcp", "name": "Optimizely CMS MCP Server", "description": "MCP server for Optimizely CMS providing AI access to GraphQL API and Content Management API with dynamic schema introspection and visual builder support.", "category": "web", "endpoint": "npx optimizely-cms-mcp", "homepage_url": "https://github.com/first3things/optimizely-cms-mcp", "github_url": "https://github.com/first3things/optimizely-cms-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx optimizely-cms-mcp", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "optimizely", "cms", "content-management", "graphql" ], "use_cases": [ "Manage Optimizely CMS content through AI assistants", "Introspect content schemas and field mappings dynamically", "Build and edit visual content layouts" ], "health": "active" }, { "id": "rudof-semantic-web-mcp", "name": "rudof Semantic Web MCP", "description": "MCP server for Semantic Web operations including RDF validation, SPARQL queries, and ShEx/SHACL schema processing for knowledge graph workflows.", "category": "data", "endpoint": "rudof-mcp", "homepage_url": "https://github.com/rudof-project/eswc2026-rudof-mcp", "github_url": "https://github.com/rudof-project/eswc2026-rudof-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "cargo install rudof-mcp", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "semantic-web", "rdf", "sparql", "knowledge-graph", "shex" ], "use_cases": [ "Validate RDF data against ShEx or SHACL schemas", "Execute SPARQL queries through AI assistants", "Process and transform linked data and knowledge graphs" ], "health": "active" }, { "id": "aws-managed-mcp", "name": "AWS Managed MCP Server", "description": "Managed MCP server from AWS that gives AI agents secure, auditable access to 15,000+ AWS API operations with IAM guardrails, CloudWatch metrics, and CloudTrail logging.", "category": "infrastructure", "endpoint": "uvx awslabs.core-mcp-server@latest", "homepage_url": "https://aws.amazon.com/blogs/aws/the-aws-mcp-server-is-now-generally-available/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install awslabs.core-mcp-server", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "aws", "cloud", "managed", "iam", "enterprise" ], "use_cases": [ "Interact with AWS services through AI agents", "Execute AWS API operations with IAM-scoped permissions", "Audit agent activity via CloudTrail and CloudWatch" ], "health": "active" }, { "id": "cryptorefills-mcp", "name": "Cryptorefills MCP Server", "description": "Agentic commerce MCP server enabling AI agents to discover products, build orders, and complete purchases with x402 stablecoin settlement.", "category": "payments", "endpoint": "https://api.cryptorefills.com/mcp", "homepage_url": "https://github.com/Cryptorefills/agentic-commerce", "github_url": "https://github.com/Cryptorefills/agentic-commerce", "x402": true, "verified": false, "protocols": [ "MCP", "x402" ], "transport": "http", "auth": "x402", "added": "2026-05-15", "updated": "2026-05-15", "tags": [ "payments", "x402", "crypto", "stablecoin", "commerce", "usdc" ], "use_cases": [ "Purchase gift cards and mobile top-ups via AI agents", "Settle commerce transactions with USDC stablecoins", "Enable autonomous agent purchasing workflows" ], "health": "active" }, { "id": "sap-cap-mcp", "name": "SAP CAP MCP Server", "description": "Official SAP MCP server for the Cloud Application Programming Model (CAP). Transforms AI agents into CAP development experts with CDS-aware context, schema introspection, and agentic coding support for enterprise SAP applications.", "category": "code", "endpoint": "npx -y @cap-js/mcp-server", "homepage_url": "https://community.sap.com/t5/technology-blog-posts-by-sap/boost-your-cap-development-with-ai-introducing-the-mcp-server-for-cap/ba-p/14202849", "github_url": "https://github.com/cap-js/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @cap-js/mcp-server", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "sap", "cap", "cds", "enterprise", "cloud-application-programming" ], "use_cases": [ "AI-assisted SAP CAP application development", "Introspect CDS schemas and service definitions", "Generate and modify CAP service handlers and data models" ], "health": "active" }, { "id": "guideline-media-plan-mcp", "name": "Guideline Media Plan MCP", "description": "Official MCP server from Guideline giving AI agents read access to media plan data, campaign details, spend pacing, and performance insights across the Guideline media management platform.", "category": "media", "endpoint": "https://api.guideline.com/mcp", "homepage_url": "https://www.guideline.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "media-planning", "advertising", "media-buying", "agency", "campaign-management" ], "use_cases": [ "Query media plan details and spend pacing via AI agents", "Generate performance summaries and campaign reports", "Integrate media plan data into agentic planning workflows" ], "health": "active" }, { "id": "guidepoint-mcp", "name": "Guidepoint MCP", "description": "MCP server from Guidepoint giving AI research workflows access to 100,000+ expert interview transcripts, industry insights, and primary research intelligence directly inside Claude and other MCP-compatible tools.", "category": "ai", "endpoint": "https://mcp.guidepoint.com", "homepage_url": "https://www.guidepoint.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "research", "expert-interviews", "primary-research", "intelligence", "diligence" ], "use_cases": [ "Access expert interview transcripts inside AI research workflows", "Incorporate primary research intelligence into due diligence", "Query industry insights from 100,000+ expert conversations" ], "health": "active" }, { "id": "blend-autopilot-mcp", "name": "Blend Autopilot MCP", "description": "MCP server from Blend Labs giving authorized AI agents programmatic access to Blend's full lending origination stack — credit, underwriting, pricing, compliance, disclosures, and closing — through a single audited interface.", "category": "payments", "endpoint": "https://api.blendlabs.com/mcp/autopilot", "homepage_url": "https://blend.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "lending", "fintech", "mortgage", "underwriting", "financial-services" ], "use_cases": [ "Execute lending origination workflows via AI agents", "Pull credit, check pricing, and verify compliance in sequence", "Give FI-built AI agents access to full Blend platform" ], "health": "active" }, { "id": "qlik-mcp", "name": "Qlik MCP Server", "description": "Official cloud-hosted MCP server from Qlik giving AI assistants governed access to Qlik Analytics Engine, trusted data products, and agentic analytics workflows with OAuth 2.0, RBAC, and full audit logging.", "category": "data", "endpoint": "https://qlik.cloud/api/v1/mcp", "homepage_url": "https://www.qlik.com/us/agentic-ai", "github_url": "https://github.com/arthurfantaci/qlik-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "analytics", "qlik", "business-intelligence", "data-products", "agentic-analytics" ], "use_cases": [ "Query Qlik analytics and data products through AI assistants", "Access measures, dimensions, and app scripts via natural language", "Run governed agentic analytics with full audit trail" ], "health": "active" }, { "id": "salt-security-mcp", "name": "Salt Security MCP Server", "description": "MCP server from Salt Security giving AI agents access to API security posture data — API inventory, vulnerability findings, attack detections, and risk scoring — for automated security operations workflows.", "category": "identity", "endpoint": "https://app.salt.security/api/mcp", "homepage_url": "https://salt.security", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "api-security", "security", "vulnerability-management", "attack-detection", "posture" ], "use_cases": [ "Query API inventory and security posture via AI agents", "Surface vulnerability findings and attack detections in agent workflows", "Automate API risk assessment and remediation triage" ], "health": "active" }, { "id": "benchling-mcp", "name": "Benchling MCP Server", "description": "MCP server from Benchling giving AI agents access to R&D data — experiments, sequences, molecules, registries, and lab notebooks — enabling agentic scientific workflows across biotech and pharma research.", "category": "data", "endpoint": "https://benchling.com/api/v2/mcp", "homepage_url": "https://www.benchling.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "biotech", "life-sciences", "r-and-d", "lab-data", "scientific-research" ], "use_cases": [ "Query experiment data and lab notebooks through AI agents", "Access sequence and molecule registries in agentic research workflows", "Automate R&D data retrieval and scientific summarization" ], "health": "active" }, { "id": "teradata-mcp", "name": "Teradata MCP Server", "description": "Official MCP server from Teradata giving AI agents secure access to enterprise data warehouse queries, VantageCloud analytics, and governed SQL execution with workload management and compliance controls.", "category": "data", "endpoint": "https://api.teradata.com/mcp", "homepage_url": "https://www.teradata.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-16", "updated": "2026-05-16", "tags": [ "data-warehouse", "teradata", "enterprise", "sql", "vantagecloud" ], "use_cases": [ "Execute governed SQL queries against Teradata VantageCloud via AI agents", "Access enterprise analytics workloads through natural language", "Integrate Teradata data into agentic reporting and analysis workflows" ], "health": "active" }, { "id": "aws-mcp-server", "name": "AWS MCP Server", "description": "Official AWS managed MCP server giving AI coding agents secure, auditable access to AWS services. Supports infrastructure provisioning, CloudWatch queries, S3 operations, Lambda management, and over 40 AWS service integrations with IAM-scoped permissions.", "category": "infrastructure", "endpoint": "https://mcp.us-east-1.amazonaws.com", "homepage_url": "https://aws.amazon.com/about-aws/whats-new/2026/05/aws-mcp-server/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "aws", "cloud", "infrastructure", "devops", "serverless" ], "use_cases": [ "Manage AWS infrastructure through AI coding agents", "Query CloudWatch logs and metrics via natural language", "Provision and configure AWS resources with IAM-scoped access" ], "health": "active" }, { "id": "imanage-mcp", "name": "iManage MCP Server", "description": "Official MCP server from iManage providing AI systems with governed access to document management, content search, and knowledge work repositories. Keeps sensitive legal and professional documents within iManage security controls while enabling AI-assisted workflows.", "category": "productivity", "endpoint": "https://mcp.imanage.com", "homepage_url": "https://imanage.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "legal", "document-management", "knowledge-work", "professional-services", "content" ], "use_cases": [ "Search and retrieve documents from iManage through AI assistants", "Enable AI-powered legal research across governed document repositories", "Integrate iManage content into agentic professional workflows" ], "health": "active" }, { "id": "pacvue-mcp", "name": "Pacvue MCP Server", "description": "MCP server from Pacvue connecting retail media and commerce advertising data to AI assistants. Enables brands and agencies to pull advertising performance data across Amazon, Walmart, and other retail platforms directly into ChatGPT, Claude, and Copilot.", "category": "media", "endpoint": "https://mcp.pacvue.com", "homepage_url": "https://www.pacvue.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "retail-media", "advertising", "commerce", "amazon-ads", "walmart" ], "use_cases": [ "Pull retail advertising reports across Amazon and Walmart via AI", "Generate commerce media performance summaries in natural language", "Integrate cross-platform ad data into agentic reporting workflows" ], "health": "active" }, { "id": "optro-mcp", "name": "Optro MCP Server", "description": "MCP server from Optro connecting enterprise AI to live GRC (governance, risk, and compliance) data. Eliminates manual workflows by providing AI agents with secure access to compliance status, risk registers, and audit findings.", "category": "identity", "endpoint": "https://mcp.optro.ai", "homepage_url": "https://www.optro.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "grc", "compliance", "risk-management", "governance", "audit" ], "use_cases": [ "Query compliance status and risk registers through AI agents", "Automate GRC reporting and audit finding triage", "Connect AI assistants to live governance data for real-time oversight" ], "health": "active" }, { "id": "oci-recovery-mcp", "name": "OCI Recovery MCP Server", "description": "Official Oracle Cloud Infrastructure MCP server for AI-driven data protection and disaster recovery. Gives AI agents access to backup policies, recovery points, and resilience status across OCI workloads with full audit logging.", "category": "infrastructure", "endpoint": "https://recovery.oci.oraclecloud.com/mcp", "homepage_url": "https://blogs.oracle.com/maa/announcing-the-oci-recovery-mcp-server-bringing-ai-driven-resilience-to-data-protection", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "oracle", "oci", "disaster-recovery", "backup", "data-protection" ], "use_cases": [ "Monitor backup health and recovery points via AI agents", "Automate disaster recovery workflows with natural language commands", "Query data protection status across OCI workloads" ], "health": "active" }, { "id": "digi-drm-mcp", "name": "Digi International MCP Server", "description": "MCP server from Digi International giving AI agents access to IoT device fleet management through Digi Remote Manager and Genesis platforms. Enables natural language queries across device fleets, automated workflows, and configuration insights.", "category": "infrastructure", "endpoint": "https://mcp.digi.com", "homepage_url": "https://www.digi.com/company/press-releases/2026/digi-launches-mcp-server-to-power-ai-workflows", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "iot", "device-management", "fleet", "remote-monitoring", "industrial" ], "use_cases": [ "Query IoT device fleet status through natural language", "Automate device configuration and monitoring workflows", "Generate fleet health reports and configuration insights via AI" ], "health": "active" }, { "id": "gooddata-mcp", "name": "GoodData MCP Server", "description": "Official MCP server from GoodData connecting AI assistants to semantic models, metrics, and dashboards. Delivers 10-50x faster time to value compared to manual BI workflows by enabling governed, natural language access to analytics.", "category": "data", "endpoint": "https://mcp.gooddata.com", "homepage_url": "https://www.gooddata.ai/press-releases/gooddata-kicks-off-2026-with-mcp-server-launch-and-major-enterprise-wins/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "analytics", "business-intelligence", "semantic-model", "dashboards", "metrics" ], "use_cases": [ "Query metrics and KPIs through AI assistants via semantic models", "Generate BI reports and dashboard summaries in natural language", "Access governed analytics data in agentic decision-making workflows" ], "health": "active" }, { "id": "mouseflow-mcp", "name": "Mouseflow MCP Server", "description": "MCP server from Mouseflow connecting behavioral analytics data to AI assistants. Ask questions about user sessions, heatmaps, funnels, and friction scores in plain English to surface UX insights without manual dashboard navigation.", "category": "data", "endpoint": "https://mcp.mouseflow.com", "homepage_url": "https://mouseflow.com/press-releases/mouseflow-launches-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-17", "updated": "2026-05-17", "tags": [ "behavioral-analytics", "heatmaps", "session-replay", "ux", "conversion" ], "use_cases": [ "Query session recordings and heatmap data via AI assistants", "Surface UX friction points and conversion bottlenecks in natural language", "Generate behavioral analytics reports without manual dashboard navigation" ], "health": "active" }, { "id": "oci-managed-db-mcp", "name": "OCI Database Tools MCP Server", "description": "Oracle's fully managed, serverless MCP service built into OCI Database Tools, enabling AI agents to connect to Oracle databases via HTTPS. Supports Oracle AI Database 26ai and Oracle Database 19c across OCI, AWS, Azure, and Google Cloud with governed toolsets including ad hoc SQL and validated SQL Reports.", "category": "data", "endpoint": "https://mcp.oracle.com", "homepage_url": "https://www.oracle.com/mcp/", "github_url": "https://github.com/oracle/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "oracle", "database", "cloud", "sql", "multi-cloud", "managed-service" ], "use_cases": [ "Connect AI agents to Oracle databases across any cloud provider", "Run natural language SQL queries against enterprise Oracle workloads", "Access governed database toolsets with IAM-scoped permissions" ], "health": "active" }, { "id": "precisely-mcp", "name": "Precisely MCP Server", "description": "MCP server from Precisely extending the Data Integrity Suite APIs for AI agents. Enables secure access to data quality, enrichment, and location intelligence capabilities without custom integrations, powering agentic data workflows across the enterprise.", "category": "data", "endpoint": "https://mcp.precisely.com", "homepage_url": "https://www.precisely.com/product/data-integrity/precisely-data-integrity-suite/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "data-quality", "data-integrity", "data-enrichment", "location-intelligence", "enterprise" ], "use_cases": [ "Access data quality and enrichment APIs through AI agents", "Query location intelligence data in agentic decision-making workflows", "Integrate trusted data services into AI-driven data pipelines" ], "health": "active" }, { "id": "govtribe-mcp", "name": "GovTribe MCP Server", "description": "The first MCP server for government contracting, connecting GovTribe's opportunity intelligence directly to AI tools. Provides access to federal opportunities, awards, IDVs, contract vehicles, vendors, forecasts, and contacts for the GovCon market.", "category": "data", "endpoint": "https://govtribe.com/mcp", "homepage_url": "https://govtribe.com/features/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "government", "contracting", "procurement", "federal", "market-intelligence" ], "use_cases": [ "Search federal contract opportunities and awards via AI assistants", "Query GovCon vendor and market intelligence in natural language", "Integrate government procurement data into agentic research workflows" ], "health": "active" }, { "id": "collibra-mcp", "name": "Collibra MCP Server", "description": "MCP server from Collibra delivering governed metadata and business context to AI agents in real time as part of the AI Command Center. Over 100 customers are already using it to power context-aware AI systems with trusted, structured enterprise metadata and compliance oversight.", "category": "data", "endpoint": "https://mcp.collibra.com", "homepage_url": "https://www.collibra.com/products/ai-command-center", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "data-governance", "metadata", "ai-governance", "compliance", "enterprise" ], "use_cases": [ "Deliver governed metadata to AI agents for context-aware decisions", "Provide real-time business context and compliance data to agentic systems", "Power enterprise AI governance with structured metadata via MCP" ], "health": "active" }, { "id": "domo-mcp", "name": "Domo MCP Server", "description": "MCP server connecting AI assistants to the Domo platform for dataset queries, metadata retrieval, and interactive dashboard rendering inside chat interfaces. Part of Domo's AI orchestration framework including AI Agent Builder and AI Toolkits.", "category": "data", "endpoint": "npx @domoai/mcp-server", "homepage_url": "https://www.domo.com/news/press/domo-launches-ai-agent-builder-and-mcp-serve", "github_url": "https://github.com/DomoApps/domo-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install @domoai/mcp-server", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "business-intelligence", "data-analytics", "sql", "dashboards", "enterprise" ], "use_cases": [ "Query Domo datasets via SQL through AI assistants", "Render interactive BI dashboards inside chat interfaces", "Access enterprise data and metrics in agentic analytics workflows" ], "health": "active" }, { "id": "codescene-codehealth-mcp", "name": "CodeScene CodeHealth MCP Server", "description": "Exposes CodeScene's Code Health analysis as local AI-friendly tools, giving coding assistants real-time maintainability feedback on generated code. Runs fully locally with no source code sent externally. Supports 30+ languages and boosts LLM code health fix rates from 20% to 90-100%.", "category": "code", "endpoint": "npx @codescene/mcp-server", "homepage_url": "https://codescene.com/product/code-health-mcp", "github_url": "https://github.com/codescene-oss/codescene-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "code-quality", "code-health", "technical-debt", "developer-tools", "maintainability" ], "use_cases": [ "Get real-time code health feedback while AI generates code", "Detect and fix maintainability issues in AI-generated code", "Enforce code quality standards across 30+ programming languages" ], "health": "active" }, { "id": "open-computer-use", "name": "Open Computer Use", "description": "Open-source computer-using agent framework that turns local desktop automation into a standard MCP service. Supports browser automation, terminal access, desktop control via computer vision, and multi-agent orchestration across macOS, Linux, and Windows. Achieves 82% on the OSWorld benchmark.", "category": "infrastructure", "endpoint": "npx open-computer-use", "homepage_url": "https://coasty.ai", "github_url": "https://github.com/coasty-ai/open-computer-use", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "desktop-automation", "computer-use", "browser-automation", "gui-automation", "open-source" ], "use_cases": [ "Automate desktop tasks through AI agents via MCP", "Control browser and terminal from AI assistants with computer vision", "Orchestrate multi-agent workflows across macOS, Linux, and Windows" ], "health": "active" }, { "id": "grounded-docs-mcp", "name": "Grounded Docs MCP Server", "description": "Open-source documentation index for AI coding assistants that fetches and indexes docs from websites, GitHub, npm, PyPI, local files, and zip archives. Supports 90+ file formats including PDF, Office documents, and Jupyter Notebooks with optional semantic search via configurable embedding models.", "category": "code", "endpoint": "npx @arabold/docs-mcp-server", "homepage_url": "https://grounded.tools", "github_url": "https://github.com/arabold/docs-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "sse", "auth": "none", "install_cmd": "npm install @arabold/docs-mcp-server", "added": "2026-05-18", "updated": "2026-05-18", "tags": [ "documentation", "developer-tools", "open-source", "context", "semantic-search" ], "use_cases": [ "Index and search documentation from any source for AI coding assistants", "Provide always-current library docs as context for code generation", "Run local semantic search across 90+ file formats for agentic coding" ], "health": "active" }, { "id": "shipwell-mcp", "name": "Shipwell MCP Server", "description": "Production-grade MCP server from Shipwell providing AI assistants secure, real-time access to transportation management system (TMS) data. Enables AI agents to automate logistics workflows, synchronize supply chain data, and query shipment information across worldwide operations.", "category": "data", "endpoint": "https://mcp.shipwell.com", "homepage_url": "https://www.shipwell.com/blog/artificial-intelligence-in-transportation-insights-at-inland25", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "logistics", "transportation", "supply-chain", "tms", "enterprise" ], "use_cases": [ "Automate logistics workflows and shipment tracking through AI assistants", "Query real-time TMS data across worldwide supply chain operations", "Synchronize transportation management data into agentic decision-making" ], "health": "active" }, { "id": "responsive-mcp", "name": "Responsive MCP Server", "description": "MCP server from Responsive enabling revenue teams to access trusted RFP knowledge and proposal content directly inside ChatGPT, Copilot, and Claude. Accelerates deal velocity by connecting field teams to curated response libraries and compliance-reviewed content via AI assistants.", "category": "productivity", "endpoint": "https://app.responsive.io/mcp", "homepage_url": "https://www.responsive.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "rfp", "sales", "revenue", "proposals", "enterprise", "knowledge-management" ], "use_cases": [ "Access curated RFP response libraries through AI assistants", "Accelerate deal velocity with AI-powered proposal content retrieval", "Connect field teams to compliance-reviewed knowledge inside chat tools" ], "health": "active" }, { "id": "thomson-reuters-cocounsel-mcp", "name": "Thomson Reuters CoCounsel MCP Server", "description": "MCP integration connecting Claude directly to Thomson Reuters CoCounsel Legal, providing fiduciary-grade legal research and analysis capabilities. Enables AI assistants to access trusted legal databases, case law, and compliance resources through a verified, enterprise-grade connection.", "category": "data", "endpoint": "https://mcp.thomsonreuters.com/cocounsel", "homepage_url": "https://legal.thomsonreuters.com/en/products/cocounsel", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "legal", "legal-research", "compliance", "case-law", "enterprise" ], "use_cases": [ "Access fiduciary-grade legal research through AI assistants", "Query case law and legal databases via natural language", "Integrate trusted legal compliance data into agentic research workflows" ], "health": "active" }, { "id": "flexmls-mcp", "name": "Flexmls MCP Server", "description": "MCP server from FBS connecting AI tools directly to Flexmls MLS databases, giving real estate professionals real-time access to listing data, market statistics, and property information through ChatGPT, Claude, and Gemini. The first MCP server purpose-built for MLS organizations.", "category": "data", "endpoint": "https://mcp.flexmls.com", "homepage_url": "https://flexmls.com/flexmls-academy/product-news/flexmls-mcp-server-the-ai-connection-to-flexmls/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "real-estate", "mls", "property-data", "listings", "market-data" ], "use_cases": [ "Query MLS listing data and market statistics via AI assistants", "Access real-time property information through natural language", "Connect real estate workflows to AI tools with live MLS data" ], "health": "active" }, { "id": "garmin-connect-mcp", "name": "Garmin Connect MCP Server", "description": "Open-source MCP server connecting Garmin Connect fitness and health data to Claude and other MCP-compatible clients. Exposes activities, health metrics, training data, sleep tracking, and body composition data for AI-powered wellness analysis and coaching.", "category": "data", "endpoint": "npx garmin-connect-mcp", "homepage_url": "https://github.com/Taxuspt/garmin_mcp", "github_url": "https://github.com/Taxuspt/garmin_mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "fitness", "health", "wearable", "garmin", "wellness", "open-source" ], "use_cases": [ "Analyze Garmin fitness activities and training metrics via AI", "Query health and sleep data through natural language conversations", "Build AI-powered wellness coaching with real-time wearable data" ], "health": "active" }, { "id": "improvado-mcp", "name": "Improvado MCP Server", "description": "MCP server from Improvado connecting AI agents to harmonized marketing data from 1,000+ advertising and analytics platforms. Enables natural language queries against cross-channel marketing performance data through Claude, Cursor, and any MCP-compatible tool.", "category": "data", "endpoint": "https://mcp.improvado.io", "homepage_url": "https://improvado.io/blog/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "marketing", "analytics", "advertising", "data-integration", "cross-channel" ], "use_cases": [ "Query cross-channel marketing performance data via AI assistants", "Access harmonized advertising data from 1000+ platforms in natural language", "Power AI-driven marketing analytics without building custom integrations" ], "health": "active" }, { "id": "ibm-context-forge-mcp", "name": "IBM ContextForge MCP Gateway", "description": "Open-source MCP registry and proxy from IBM that federates tools, agents, and APIs into one clean endpoint for AI clients. Provides a secure, intelligent gateway between AI agents and the tools they use, simplifying MCP server management with built-in discovery, routing, and access control.", "category": "infrastructure", "endpoint": "npx @ibm/mcp-context-forge", "homepage_url": "https://developer.ibm.com/blogs/context-forge-mcp-gateway-now-available/", "github_url": "https://github.com/IBM/mcp-context-forge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "gateway", "registry", "proxy", "ibm", "open-source", "infrastructure" ], "use_cases": [ "Federate multiple MCP servers behind a single gateway endpoint", "Manage tool discovery and routing for AI agents at scale", "Add access control and security to MCP server deployments" ], "health": "active" }, { "id": "naver-search-mcp", "name": "Naver Search MCP Server", "description": "MCP server integrating Naver Search API and DataLab API for Korean web search, news, blogs, shopping, and trend data. Supports category-based search, trend analysis, and shopping insights with comprehensive access to Korea's dominant search ecosystem.", "category": "web", "endpoint": "npx naver-search-mcp", "homepage_url": "https://github.com/isnow890/naver-search-mcp", "github_url": "https://github.com/isnow890/naver-search-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install naver-search-mcp", "added": "2026-05-19", "updated": "2026-05-19", "tags": [ "search", "korean", "naver", "trends", "news", "shopping" ], "use_cases": [ "Search Korean web, news, and blog content via AI assistants", "Analyze Naver DataLab trends and shopping insights in natural language", "Access Korea's dominant search ecosystem through MCP-compatible tools" ], "health": "active" }, { "id": "datasite-mcp", "name": "Datasite MCP Server", "description": "MCP server from Datasite enabling AI assistants to access live virtual data room content for M&A due diligence. The first VDR provider to offer MCP connectivity, allowing deal teams to summarize documents, answer diligence Q&A, and draft review summaries without exporting sensitive files outside the secure platform.", "category": "data", "endpoint": "https://mcp.datasite.com", "homepage_url": "https://www.datasite.com/en/company/news/datasite-becomes-the-first-vdr-provider-to-connect-ai-assistants-directly-to-live-deal-content-with-mcp-server-launch", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "legal", "m-and-a", "virtual-data-room", "due-diligence", "enterprise", "deal-management" ], "use_cases": [ "Summarize key terms across deal documents with citations inside virtual data rooms", "Answer due diligence Q&A by surfacing relevant clauses and financial tables via AI", "Draft diligence summaries and review materials without exporting sensitive VDR content" ], "health": "active" }, { "id": "liongard-mcp", "name": "Liongard MCP Server", "description": "MCP server from Liongard providing AI agents secure, API-driven access to LiongardIQ asset intelligence across the full IT stack. Enables MSPs and IT teams to query device fleets, configurations, identities, and security posture in real time through natural language interfaces.", "category": "data", "endpoint": "https://mcp.liongard.com", "homepage_url": "https://www.liongard.com/products/liongard-mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "msp", "asset-intelligence", "it-management", "network-discovery", "security", "enterprise" ], "use_cases": [ "Query IT asset data and device configurations in real time via AI assistants", "Automate MSP workflows with live asset intelligence and identity mapping", "Enrich external systems with continuously updated IT infrastructure data" ], "health": "active" }, { "id": "xurrent-mcp", "name": "Xurrent MCP Server", "description": "Open MCP server from Xurrent connecting AI agents to live ITSM and incident response data. Ships two servers — one for incident response and one for service operations — enabling AI tools to query, triage, and act on operational data with full governance and audit trails.", "category": "productivity", "endpoint": "https://mcp.xurrent.com", "homepage_url": "https://www.xurrent.com/product-updates/agentic-ai-xurrents-q2-2026-release", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "itsm", "incident-response", "service-management", "enterprise", "itops" ], "use_cases": [ "Query ITSM and incident data through natural language via any AI client", "Automate ticket triage and closure with autonomous AI agents", "Connect external AI models to service operations with enterprise governance" ], "health": "active" }, { "id": "google-colab-mcp", "name": "Google Colab MCP Server", "description": "Open-source MCP server from Google connecting AI agents to Google Colab cloud runtimes with GPU access. Enables agents to create notebooks, execute code cells, manage dependencies, and retrieve outputs — bridging local AI workflows with Colab cloud compute.", "category": "code", "endpoint": "npx @googlecolab/colab-mcp", "homepage_url": "https://developers.googleblog.com/announcing-the-colab-mcp-server-connect-any-ai-agent-to-google-colab/", "github_url": "https://github.com/googlecolab/colab-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "notebooks", "gpu", "cloud-compute", "google", "python", "open-source" ], "use_cases": [ "Execute code on Google Colab GPUs from local AI agents via MCP", "Create and manage Jupyter notebooks programmatically through AI assistants", "Offload compute-intensive AI tasks to cloud runtimes from Claude Code or Gemini CLI" ], "health": "active" }, { "id": "everlaw-mcp", "name": "Everlaw MCP Server", "description": "MCP connector from Everlaw enabling AI assistants to search documents, retrieve binder content, analyze metadata, and coordinate multi-step e-discovery workflows. Part of Anthropic's Claude for Legal initiative, providing structured access to litigation document review platforms.", "category": "data", "endpoint": "https://mcp.everlaw.com", "homepage_url": "https://www.everlaw.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "legal", "e-discovery", "litigation", "document-review", "enterprise" ], "use_cases": [ "Search e-discovery documents inside Everlaw using natural language via AI", "Retrieve and analyze document metadata and Bates numbers through AI assistants", "Coordinate multi-step litigation workflows across tools with AI orchestration" ], "health": "active" }, { "id": "relativity-mcp", "name": "Relativity MCP Server", "description": "MCP connector from Relativity bringing AI assistant access to the leading e-discovery and legal hold platform. Enables Claude and other AI tools to search, analyze, and summarize litigation documents at scale within governed review workflows.", "category": "data", "endpoint": "https://mcp.relativity.com", "homepage_url": "https://www.relativity.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "legal", "e-discovery", "litigation", "document-review", "enterprise", "compliance" ], "use_cases": [ "Search and analyze litigation documents at scale via AI assistants", "Summarize case materials and surface relevant evidence through natural language", "Integrate e-discovery workflows with AI-powered legal research pipelines" ], "health": "active" }, { "id": "midpage-mcp", "name": "Midpage MCP Server", "description": "MCP connector from Midpage providing AI assistants with legal citation verification and hallucination detection. Enables Claude to verify case law citations before they appear in work product, drawing from a comprehensive legal research corpus.", "category": "data", "endpoint": "https://mcp.midpage.ai", "homepage_url": "https://www.midpage.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "legal", "legal-research", "citation-verification", "hallucination-detection", "case-law" ], "use_cases": [ "Verify legal citations in AI-generated work product before delivery", "Detect and prevent hallucinated case law references in legal documents", "Ground AI legal research in verified case law and statutory sources" ], "health": "active" }, { "id": "trellis-mcp", "name": "Trellis MCP Server", "description": "MCP connector from Trellis enabling AI assistants to access state court records, judicial analytics, and litigation intelligence. Provides structured access to court filings, judge profiles, and case outcome data for AI-powered legal research workflows.", "category": "data", "endpoint": "https://mcp.trellis.law", "homepage_url": "https://trellis.law", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-20", "updated": "2026-05-20", "tags": [ "legal", "court-records", "judicial-analytics", "litigation", "legal-research" ], "use_cases": [ "Query state court records and case filings via AI assistants", "Analyze judge profiles and ruling patterns for litigation strategy", "Access litigation intelligence and case outcome data through natural language" ], "health": "active" }, { "id": "exo-platform-mcp", "name": "eXo Platform MCP Server", "description": "MCP server from eXo Platform exposing nearly 100 tools across the open-source digital workplace for collaboration, knowledge management, and productivity. Enables AI assistants to interact with documents, activity streams, notes, tasks, events, and social features while respecting existing user permissions and governance policies.", "category": "productivity", "endpoint": "https://www.exoplatform.com/mcp", "homepage_url": "https://www.exoplatform.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "digital-workplace", "collaboration", "knowledge-management", "open-source", "enterprise", "document-management" ], "use_cases": [ "Connect external AI assistants to digital workplace content including documents, tasks, and notes", "Orchestrate multi-system workflows with AI agents while maintaining governance and access controls", "Build custom AI agents that interact with collaboration and productivity tools in a secure environment" ], "health": "active" }, { "id": "trust3-mcp-security", "name": "Trust3 AI MCP Security", "description": "Enterprise agent control plane from Trust3 AI that governs and secures MCP connections and agent-to-agent communications. Provides identity access management for AI agents, content firewalling, single-purpose credential isolation, and immutable audit trails for litigation-grade compliance across agentic AI workloads.", "category": "infrastructure", "endpoint": "https://trust3.ai/mcp", "homepage_url": "https://trust3.ai/platform/mcp-security/", "x402": false, "verified": false, "protocols": [ "MCP", "A2A" ], "transport": "http", "auth": "oauth", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "security", "governance", "compliance", "agent-security", "audit", "enterprise", "zero-trust" ], "use_cases": [ "Govern and audit every MCP connection and agent action across enterprise AI workloads", "Enforce zero standing access and scoped permissions for autonomous AI agents", "Generate immutable agent action logs for litigation-grade compliance and audit trails" ], "health": "active" }, { "id": "ctrader-mcp", "name": "cTrader AI Agent Connect", "description": "Official MCP servers from Spotware for the cTrader FX/CFD trading platform. Ships two servers: a remote server via cTrader Web for account operations, order management, and market data, and a local server via cTrader Windows for extended desktop workspace control. Includes a skills library with ready-made trading workflow templates.", "category": "data", "endpoint": "https://ct.spotware.com/mcp", "homepage_url": "https://spotware.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "trading", "forex", "cfd", "market-data", "order-management", "fintech" ], "use_cases": [ "Place trades and manage positions on cTrader through natural language prompts via AI agents", "Run technical analysis and market data queries conversationally from Claude Code or Cursor", "Automate common trading routines using pre-built workflow templates and AI assistants" ], "health": "active" }, { "id": "surgegraph-mcp", "name": "SurgeGraph MCP Server", "description": "Agent-native MCP server from SurgeGraph for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) workflows. Packages research, content generation, publishing, and AI citation monitoring into a single Go binary callable from terminal or AI agent environments. Includes local SQLite mirror for offline queries.", "category": "media", "endpoint": "https://surgegraph.io/mcp", "homepage_url": "https://surgegraph.io/", "github_url": "https://github.com/mvanhorn/printing-press-library/tree/main/library/ai/surgegraph", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "seo", "aeo", "geo", "content-optimization", "ai-citations", "marketing", "answer-engine" ], "use_cases": [ "Research content opportunities and generate optimized drafts for AI answer engine visibility", "Monitor how AI models cite your content across ChatGPT, Perplexity, Gemini, and Google AI Mode", "Score web pages for citation readiness and apply on-page fixes via AI agent workflows" ], "health": "active" }, { "id": "courtlistener-mcp", "name": "CourtListener MCP Server", "description": "Free MCP server from Free Law Project connecting AI assistants to CourtListener, the largest open repository of U.S. federal court records. Provides access to millions of court decisions, PACER data, citation networks, oral argument audio, judge profiles, and real-time filing alerts with citation verification to reduce hallucinations.", "category": "data", "endpoint": "https://www.courtlistener.com/mcp", "homepage_url": "https://www.courtlistener.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "legal", "court-records", "legal-research", "open-data", "free", "pacer", "access-to-justice" ], "use_cases": [ "Search millions of federal and state court decisions and PACER filings via AI assistants", "Verify legal citations in AI-generated work product against authoritative court records", "Set up real-time alerts for new filings and citations through natural language prompts" ], "health": "active" }, { "id": "german-law-mcp", "name": "German Law MCP Server", "description": "Open-source MCP server providing AI assistants with access to 6,870 German federal statutes including the BGB, StGB, GG, BDSG, and more. Enables Claude, Cursor, and other MCP-compatible clients to query and retrieve German legal texts directly for legal research and compliance workflows.", "category": "data", "endpoint": "npx german-law-mcp", "github_url": "https://github.com/Ansvar-Systems/German-law-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "legal", "german-law", "statutes", "open-source", "compliance", "legal-research" ], "use_cases": [ "Query German federal statutes and legal texts directly from AI coding assistants", "Research German regulatory requirements and compliance obligations via natural language", "Cross-reference multiple German laws and legal provisions in AI-assisted legal workflows" ], "health": "active" }, { "id": "ckan-mcp", "name": "CKAN Open Data MCP Server", "description": "Open-source MCP server that turns any CKAN open data portal into a conversational interface for AI assistants. Supports searching datasets, browsing resources, querying DataStore tables, and retrieving metadata from any CKAN-powered government or institutional open data catalog.", "category": "data", "endpoint": "npx ckan-mcp-server", "github_url": "https://github.com/ondata/ckan-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-21", "updated": "2026-05-21", "tags": [ "open-data", "government", "datasets", "ckan", "open-source", "data-portal" ], "use_cases": [ "Search and query government open data portals conversationally via AI assistants", "Browse and retrieve datasets and resources from any CKAN-powered data catalog", "Analyze public DataStore tables through natural language queries in Claude or Cursor" ], "health": "active" }, { "id": "sistrix-mcp", "name": "SISTRIX MCP Server", "description": "MCP server from SISTRIX connecting AI assistants to the SISTRIX SEO analytics platform in real time. Provides access to the Visibility Index, keyword rankings, search volume data, and AI citation metrics through conversational queries. Supports OAuth authentication for all subscription tiers with no API key required and zero credit consumption for MCP requests.", "category": "data", "endpoint": "https://www.sistrix.com/mcp", "homepage_url": "https://www.sistrix.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "seo", "analytics", "visibility-index", "keyword-rankings", "search-volume", "ai-citations", "marketing" ], "use_cases": [ "Run SEO initial analysis reports including Visibility Index trends, top keywords, and competitor identification via AI assistants", "Perform content audits that cluster pages by topic and classify them as high performers or low performers", "Identify content gaps against competitors and generate prioritized keyword strategies through natural language prompts" ], "health": "active" }, { "id": "appcharge-mcp", "name": "Appcharge MCP Server", "description": "Hosted MCP server from Appcharge for mobile game direct-to-consumer operations. Enables publisher R&D teams to configure onboarding APIs, validate callback URLs, and manage player authentication workflows directly from MCP-compatible development environments. Includes a Developer Setup Skills Suite covering Player Authentication, Web Store Personalisation, and Awarding APIs.", "category": "productivity", "endpoint": "https://www.appcharge.com/mcp", "homepage_url": "https://www.appcharge.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "mobile-gaming", "dtc", "onboarding", "game-monetization", "developer-tools", "fintech" ], "use_cases": [ "Configure player authentication and web store APIs for mobile games directly from IDE-based AI assistants", "Validate DTC onboarding integrations and identify invalid callback URLs without leaving the development environment", "Automate mobile game direct-to-consumer setup workflows using agentic skills and natural language prompts" ], "health": "active" }, { "id": "alteryx-one-mcp", "name": "Alteryx One MCP Server", "description": "MCP server from Alteryx that extends the Alteryx One analytics platform into external AI environments. Works alongside Agent Studio to expose trusted datasets, business rules, and deterministic workflows to autonomous agents. Enables business analysts to connect enterprise data and governance into AI-powered systems without centralized IT involvement.", "category": "data", "endpoint": "https://www.alteryx.com/mcp", "homepage_url": "https://www.alteryx.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "analytics", "data-automation", "business-logic", "low-code", "enterprise", "data-preparation", "governance" ], "use_cases": [ "Expose trusted Alteryx workflows and business logic to AI agents operating in Slack, Teams, or external orchestration frameworks", "Combine deterministic data preparation pipelines with probabilistic agent-based processes for auditable AI workflows", "Enable business analysts to build and deploy agentic AI tools using low-code Alteryx One without relying on centralized IT" ], "health": "active" }, { "id": "screaming-frog-mcp", "name": "Screaming Frog SEO Spider MCP Server", "description": "MCP server built into the Screaming Frog SEO Spider desktop application starting with version 24.0. Allows AI assistants to run site crawls, analyze crawl data, export reports, summarize technical SEO findings, and generate interactive visualizations. Operates locally alongside the desktop application for hands-free SEO auditing workflows.", "category": "data", "endpoint": "screaming-frog-seo-spider", "homepage_url": "https://www.screamingfrog.co.uk/seo-spider/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "seo", "crawling", "site-audit", "technical-seo", "desktop", "data-export", "visualization" ], "use_cases": [ "Run automated site crawls and receive summarized technical SEO audit reports through AI assistants", "Export crawl data and combine it with other sources for comprehensive analysis via natural language prompts", "Generate interactive visualizations and data manipulations from Screaming Frog crawl results using AI workflows" ], "health": "active" }, { "id": "cloudeagle-mcp", "name": "CloudEagle.ai MCP Server", "description": "MCP server from CloudEagle.ai providing real-time answers on SaaS spend, AI tool usage, and identity management within enterprises. Connects AI assistants to the CloudEagle platform for querying software licenses, tracking shadow IT, monitoring vendor contracts, and auditing user access across the organization.", "category": "data", "endpoint": "https://www.cloudeagle.ai/mcp", "homepage_url": "https://www.cloudeagle.ai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "saas-management", "it-governance", "shadow-it", "license-management", "identity", "spend-analytics", "enterprise" ], "use_cases": [ "Query SaaS spend and license utilization across the enterprise through conversational AI assistants", "Detect shadow IT and unauthorized AI tool usage by connecting AI agents to CloudEagle discovery data", "Audit user access and vendor contracts in real time via natural language prompts to the MCP server" ], "health": "active" }, { "id": "notebooklm-mcp", "name": "NotebookLM MCP Server", "description": "Open-source MCP server for querying Google NotebookLM notebooks from AI assistants. Enables Claude Code, Cursor, VS Code Copilot, and other MCP-compatible clients to search notebook content, retrieve source summaries, and access research notes stored in NotebookLM. Designed for researchers and knowledge workers who organize reference material in NotebookLM.", "category": "productivity", "endpoint": "npx notebooklm-mcp", "github_url": "https://github.com/julianoczkowski/notebooklm-mcp-2026", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx notebooklm-mcp", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "notebooklm", "google", "research", "knowledge-management", "open-source", "notebooks" ], "use_cases": [ "Search and retrieve research notes from Google NotebookLM directly inside AI coding assistants", "Pull source summaries and notebook content into development workflows without switching to the NotebookLM web app", "Build AI-powered research workflows that combine NotebookLM knowledge bases with code generation and analysis" ], "health": "active" }, { "id": "humanity-protocol-mcp", "name": "Humanity Protocol MCP Server", "description": "MCP server from Humanity Protocol enabling AI coding tools to access verified identity documents and credentials in real time. Supports integration with Claude Code, Cursor, and other MCP-compatible clients for building applications that require identity verification, proof of personhood, and credential validation using Humanity Protocol's blockchain-based identity infrastructure.", "category": "identity", "endpoint": "https://developer.humanityprotocol.com/mcp", "homepage_url": "https://www.humanityprotocol.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "identity", "blockchain", "verification", "proof-of-personhood", "credentials", "web3", "decentralized-identity" ], "use_cases": [ "Access verified identity documents and credentials from within AI coding assistants for identity-aware application development", "Integrate proof-of-personhood checks into agentic workflows using blockchain-based identity verification", "Build applications with real-time credential validation by connecting AI agents to Humanity Protocol infrastructure" ], "health": "active" }, { "id": "dotnet-governance-mcp", "name": "Microsoft Agent Governance Toolkit MCP Extensions", "description": "Open-source MCP governance extensions from Microsoft for .NET that add rate limiting, content filtering, guardrails, and audit logging to MCP server deployments. Acts as a governance proxy layer between MCP clients and downstream servers, enforcing enterprise policies on tool usage, input validation, and output filtering for agentic AI workloads.", "category": "infrastructure", "endpoint": "dotnet-agent-governance-mcp", "homepage_url": "https://devblogs.microsoft.com/dotnet/announcing-agent-governance-toolkit-mcp-extensions-for-dotnet/", "github_url": "https://github.com/microsoft/agent-governance-toolkit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "dotnet add package Microsoft.Extensions.AI.MCP.Governance", "added": "2026-05-22", "updated": "2026-05-22", "tags": [ "governance", "rate-limiting", "guardrails", "content-filtering", "audit", "dotnet", "open-source", "enterprise", "security" ], "use_cases": [ "Add rate limiting and content filtering guardrails to existing MCP server deployments without modifying server code", "Enforce enterprise governance policies on AI agent tool usage with audit logging and input validation", "Build compliant agentic AI infrastructure in .NET with pluggable MCP governance middleware" ], "health": "active" }, { "id": "govinfo-mcp", "name": "GovInfo MCP Server", "description": "Official MCP server from the U.S. Government Publishing Office providing AI agents with access to GovInfo, the world's only certified trustworthy digital repository of federal publications. Enables search and retrieval of congressional documents, Federal Register postings, Code of Federal Regulations, and other government publications through conversational AI interfaces.", "category": "data", "endpoint": "govinfo-mcp", "homepage_url": "https://www.govinfo.gov/features/mcp-public-preview", "github_url": "https://github.com/usgpo/api", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "government", "federal-data", "legal", "legislation", "public-records", "open-data", "compliance" ], "use_cases": [ "Search and retrieve official federal government publications including congressional records and the Federal Register via AI assistants", "Query the Code of Federal Regulations and legislative history for legal research and compliance analysis", "Access certified trustworthy government data for policy analysis and academic research through natural language prompts" ], "health": "active" }, { "id": "census-bureau-mcp", "name": "US Census Bureau MCP Server", "description": "Official MCP server from the U.S. Census Bureau enabling AI agents to query Census datasets and demographic statistics directly. Bridges large language models with Census API data, dramatically improving accuracy of AI responses about population, economic, and geographic data from near 0% to 95% in pilot testing by US Digital Corps fellows.", "category": "data", "endpoint": "census-bureau-mcp", "homepage_url": "https://www.census.gov/", "github_url": "https://github.com/uscensusbureau/census-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "government", "census", "demographics", "statistics", "population", "open-data", "federal" ], "use_cases": [ "Query Census population and demographic data with high accuracy through AI assistants instead of manual data portal navigation", "Retrieve economic indicators and geographic statistics for policy development and program evaluation via natural language", "Combine Census data with other federal datasets for comprehensive research and analysis through agentic workflows" ], "health": "active" }, { "id": "orderly-network-mcp", "name": "Orderly Network MCP Server", "description": "MCP server from Orderly Network enabling AI agents to build, launch, and manage perpetual futures decentralized exchanges across 15+ blockchain networks. Consolidates API documentation, SDK patterns, contract addresses, and operational workflows into a queryable context layer that integrates with Orderly One, the project's no-code DEX launcher supporting 110+ trading assets.", "category": "web", "endpoint": "npx @orderly.network/mcp-server", "homepage_url": "https://orderly.network/", "github_url": "https://github.com/OrderlyNetwork", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @orderly.network/mcp-server init --client claude", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "defi", "perpetuals", "dex", "trading", "blockchain", "omnichain", "web3", "crypto" ], "use_cases": [ "Launch branded perpetual futures DEXs across multiple chains using AI agents and no-code tooling", "Query Orderly Network API documentation and SDK patterns for rapid DeFi application development", "Manage trading venue configuration including fee structures, margin parameters, and liquidity settings through AI assistants" ], "health": "active" }, { "id": "devart-universal-mcp", "name": "Devart Universal MCP Server", "description": "Universal MCP server from Devart that connects AI agents to virtually any database or data source through ODBC. Part of a product line of 19 specialized MCP servers covering popular databases. Enables AI coding assistants to query, analyze, and interact with enterprise data across SQL Server, Oracle, MySQL, PostgreSQL, MongoDB, and many other platforms without custom integration.", "category": "data", "endpoint": "devart-universal-mcp", "homepage_url": "https://www.devart.com/blog/devart-brings-ai-agents-closer-to-enterprise-data-with-new-mcp-server-product-line.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "database", "odbc", "sql-server", "oracle", "mysql", "postgresql", "mongodb", "enterprise", "data-access" ], "use_cases": [ "Connect AI coding assistants to any ODBC-compatible database for querying and analysis without writing custom connectors", "Access enterprise data across SQL Server, Oracle, MySQL, PostgreSQL, and MongoDB through a single universal MCP interface", "Enable AI agents to perform cross-database operations and data analysis across heterogeneous enterprise data environments" ], "health": "active" }, { "id": "boomi-mcp", "name": "Boomi MCP Server", "description": "MCP server from Boomi for governing and managing AI agent tool access across the enterprise. Provides a vendor-agnostic catalog of MCP servers instantly available to agents, with centralized governance, access controls, and integration with the Boomi platform's automation and integration capabilities.", "category": "infrastructure", "endpoint": "https://boomi.com/platform/mcp/", "homepage_url": "https://boomi.com/platform/mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "integration", "governance", "catalog", "agent-management", "enterprise", "automation", "ipaas" ], "use_cases": [ "Govern and catalog all MCP servers in the enterprise with centralized access controls and audit logging", "Connect AI agents to Boomi integration and automation workflows for end-to-end business process orchestration", "Provide vendor-agnostic MCP server discovery and management for multi-agent enterprise AI deployments" ], "health": "active" }, { "id": "expedia-mcp", "name": "Expedia MCP Server", "description": "MCP server from Expedia enabling direct AI agent access to its travel inventory for B2B partners. Allows AI assistants and agents to search flights, hotels, car rentals, and vacation packages, retrieve availability and pricing, and manage travel bookings programmatically through the Expedia partner platform.", "category": "data", "endpoint": "https://developers.expediagroup.com/mcp", "homepage_url": "https://www.expediagroup.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "travel", "booking", "flights", "hotels", "b2b", "inventory", "hospitality" ], "use_cases": [ "Search and compare flights, hotels, and vacation packages through AI agents connected to Expedia's live travel inventory", "Build AI-powered travel booking workflows that access real-time availability and pricing from Expedia's B2B partner platform", "Automate corporate travel management and itinerary planning using AI assistants with direct Expedia inventory access" ], "health": "active" }, { "id": "fatsecret-mcp", "name": "FatSecret MCP Server", "description": "Open-source MCP server for managing food diaries, nutrition tracking, meal planning, and weight logging via the FatSecret Platform API. Connects AI assistants to comprehensive nutritional databases for calorie counting, macro tracking, and dietary analysis through natural language interactions.", "category": "data", "endpoint": "fatsecret-mcp-server", "homepage_url": "https://platform.fatsecret.com/", "github_url": "https://github.com/Yurzs/fatsecret-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "nutrition", "health", "food-diary", "calories", "meal-planning", "diet", "fitness", "open-source" ], "use_cases": [ "Track daily food intake and nutrition through conversational AI assistants connected to the FatSecret database", "Plan meals and analyze dietary patterns using AI agents with access to comprehensive nutritional data", "Log weight and monitor fitness progress through natural language interactions with AI coding and productivity tools" ], "health": "active" }, { "id": "google-ai-edge-mcp", "name": "Google AI Edge Gallery MCP Server", "description": "MCP integration for Google AI Edge Gallery enabling on-device AI models running locally on Android to connect with external tools and data sources. Supports the Model Context Protocol for extending local LLM capabilities with tool use, persistent chat history, and notification reminders without cloud dependency.", "category": "ai", "endpoint": "google-ai-edge-gallery-mcp", "homepage_url": "https://developers.googleblog.com/a-smarter-google-ai-edge-gallery-mcp-integration-notifications-and-session-continuity/", "github_url": "https://github.com/nicolo-sala/google-ai-edge-gallery", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "on-device", "edge-ai", "android", "google", "local-llm", "mobile", "open-source" ], "use_cases": [ "Extend on-device AI models on Android with MCP tool access for local-first AI workflows without cloud dependency", "Build mobile AI applications that combine local inference with external tool use through the Model Context Protocol", "Run persistent AI chat sessions with notification reminders and tool integrations on Android devices via Google AI Edge Gallery" ], "health": "active" }, { "id": "bluerock-mcp-hooks", "name": "BlueRock MCP Python Hooks", "description": "Open-source MCP server monitoring toolkit from BlueRock for Python applications. Provides hooks that observe tool calls, session events, module imports, and subprocess activity in Pythonic MCP server deployments. Designed for security teams and platform engineers to gain visibility into MCP server behavior in production.", "category": "infrastructure", "endpoint": "bluerock-mcp-python-hooks", "homepage_url": "https://www.helpnetsecurity.com/2026/05/07/bluerock-mcp-python-hooks-mcp-server-monitoring/", "github_url": "https://github.com/bluerock-io/mcp-python-hooks", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install bluerock-mcp-hooks", "added": "2026-05-23", "updated": "2026-05-23", "tags": [ "monitoring", "security", "python", "observability", "hooks", "open-source", "audit", "devops" ], "use_cases": [ "Monitor MCP server tool calls and session events in Python deployments for security and compliance auditing", "Detect unauthorized module imports and subprocess activity in MCP server processes running in production", "Add observability to Pythonic MCP server deployments without modifying existing server code" ], "health": "active" }, { "id": "confluent-mcp", "name": "Confluent MCP Server", "description": "Open-source and managed MCP server from Confluent enabling AI coding assistants to interact with Apache Kafka streaming infrastructure. Provides tools to discover topics, inspect consumer groups, manage connectors, and build CDC pipelines through Confluent Cloud. Includes Agent Skills that package Confluent domain expertise for production-ready output.", "category": "data", "endpoint": "confluent-mcp-server", "homepage_url": "https://www.confluent.io/blog/ai-developer-tools-mcp-server-agent-skills-ga/", "github_url": "https://github.com/confluentinc/mcp-confluent", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install @confluentinc/mcp-confluent", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "kafka", "streaming", "data-pipelines", "cdc", "flink", "event-driven", "open-source", "cloud" ], "use_cases": [ "Discover Kafka topics, schemas, and consumer groups through AI assistants with full Confluent Cloud context", "Build and manage CDC pipelines with Apache Flink and Tableflow using natural language via AI coding tools", "Diagnose lagging consumer groups and debug streaming applications with AI-powered operational insights" ], "health": "active" }, { "id": "snowflake-cortex-mcp", "name": "Snowflake Cortex MCP Server", "description": "Managed MCP server from Snowflake enabling AI agents to access Cortex AI services including Cortex Analyst, Cortex Search, and Cortex Agents as tools. Supports custom tools and SQL execution on standards-based interfaces, providing AI assistants with direct access to data warehouse analytics, semantic search, and AI-powered data exploration.", "category": "data", "endpoint": "https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp", "homepage_url": "https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "data-warehouse", "analytics", "cortex", "sql", "semantic-search", "snowflake", "cloud", "enterprise" ], "use_cases": [ "Query Snowflake data warehouses through AI agents with Cortex Analyst for natural language analytics", "Perform semantic search across enterprise data using Cortex Search exposed through the MCP interface", "Execute SQL queries and explore data schemas through AI assistants connected to Snowflake's managed MCP server" ], "health": "active" }, { "id": "splunk-platform-mcp", "name": "Splunk Platform MCP Server", "description": "Official MCP server from Splunk for integrating AI agents with the Splunk observability and security platform. Version 1.1 enables AI assistants to search logs, create alerts, query dashboards, and perform security investigations through natural language. Supports SPL query generation and real-time data access for incident response workflows.", "category": "infrastructure", "endpoint": "splunk-platform-mcp", "homepage_url": "https://help.splunk.com/en/splunk-enterprise/mcp-server-for-splunk-platform/1.1/mcp-server-release-notes", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "observability", "logging", "siem", "security", "splunk", "spl", "monitoring", "incident-response" ], "use_cases": [ "Search and analyze Splunk logs through AI assistants using natural language instead of manual SPL queries", "Create alerts and monitor dashboards via AI agents connected to the Splunk observability platform", "Perform security investigations and incident response workflows through AI-powered Splunk data access" ], "health": "active" }, { "id": "iterable-mcp", "name": "Iterable MCP Server", "description": "Open-source MCP server from Iterable enabling AI agents to interact with the cross-channel marketing automation platform. Allows campaign management, customer segmentation, journey orchestration, and marketing analytics through the Model Context Protocol. Currently in beta with over 90% of Iterable customers already leveraging AI agents.", "category": "communication", "endpoint": "iterable-mcp-server", "homepage_url": "https://iterable.com/blog/introducing-open-source-model-context-protocol-mcp-server/", "github_url": "https://github.com/Iterable/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "marketing", "email", "cross-channel", "campaigns", "segmentation", "automation", "open-source" ], "use_cases": [ "Manage cross-channel marketing campaigns including email, push, SMS, and in-app through AI assistants", "Build and modify customer segments and journey workflows using natural language prompts", "Query marketing analytics and campaign performance data through AI agents for rapid optimization" ], "health": "active" }, { "id": "perforce-p4-mcp", "name": "Perforce P4 MCP Server", "description": "MCP server from Perforce for AI-driven workflows with Helix Core version control. Exposes safe, structured read and write tools to AI models for changelists, files, shelves, workspaces, jobs, reviews, and server metadata. Enables natural-language queries against Perforce repositories for code search, change history analysis, and workflow automation.", "category": "code", "endpoint": "p4-mcp-server", "homepage_url": "https://www.perforce.com/products/p4/p4-mcp", "github_url": "https://github.com/perforce/p4mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "version-control", "perforce", "helix-core", "devops", "code-review", "changelists", "open-source" ], "use_cases": [ "Query Perforce Helix Core changelists, files, and shelved changes through AI coding assistants", "Automate code review workflows and changelist management using natural language in AI editors", "Search and analyze version control history across large-scale Perforce repositories via AI agents" ], "health": "active" }, { "id": "perforce-p4plan-mcp", "name": "Perforce P4 Plan MCP Server", "description": "MCP server from Perforce for AI-driven project management with P4 Plan. Provides 28 tools for managing projects, tasks, sprints, bugs, and team capacity through the Model Context Protocol. Enables AI assistants to create tasks, plan sprints, track progress, and generate project reports.", "category": "productivity", "endpoint": "p4plan-mcp-server", "homepage_url": "https://www.perforce.com/products/p4/p4-mcp", "github_url": "https://github.com/perforce/p4plan-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "project-management", "sprints", "agile", "task-tracking", "perforce", "bugs", "planning" ], "use_cases": [ "Create and manage project tasks, sprints, and bugs through AI assistants connected to P4 Plan", "Plan sprint capacity and track team progress using natural language prompts in AI coding tools", "Generate project status reports and backlog analysis through AI agents with P4 Plan access" ], "health": "active" }, { "id": "parasoft-mcp", "name": "Parasoft MCP Server", "description": "MCP server from Parasoft for autonomous AI-driven API mocking and service virtualization. Eliminates dependency bottlenecks by allowing AI agents to create, configure, and manage virtual services that simulate APIs and backend systems. Enables automated test environment provisioning through the Model Context Protocol.", "category": "code", "endpoint": "parasoft-virtualize-mcp", "homepage_url": "https://www.parasoft.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "api-mocking", "service-virtualization", "testing", "devops", "enterprise", "automation", "ci-cd" ], "use_cases": [ "Create API mocks and virtual services autonomously through AI agents to eliminate dependency bottlenecks", "Provision test environments with simulated backend services using natural language in AI coding tools", "Automate service virtualization configuration for CI/CD pipelines through AI-powered MCP integration" ], "health": "active" }, { "id": "aprimo-mcp", "name": "Aprimo MCP Server", "description": "MCP server from Aprimo connecting AI agents to enterprise digital asset management and content operations. Enables approved content to flow into external AI-powered workflows while maintaining governance and brand compliance. Part of Aprimo's Interconnected Content Operations platform linking AI, DAM, work management, and marketing spend.", "category": "media", "endpoint": "aprimo-mcp-server", "homepage_url": "https://www.aprimo.com/blog/model-context-protocol-dam-ai-agents", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "dam", "digital-assets", "content-ops", "marketing", "governance", "brand-compliance", "enterprise" ], "use_cases": [ "Search and retrieve approved digital assets from Aprimo DAM through AI agents for content workflows", "Connect enterprise content operations with AI-powered marketing automation while maintaining brand governance", "Enable AI assistants to access and use governed digital assets for content creation and campaign execution" ], "health": "active" }, { "id": "armorcode-mcp", "name": "ArmorCode MCP Server", "description": "MCP server from ArmorCode providing contextual application security posture management (ASPM) data for AI-powered automation. Part of the Anya Agents framework, it enables AI agents to access vulnerability findings, risk prioritization, and remediation guidance across the software development lifecycle.", "category": "infrastructure", "endpoint": "armorcode-mcp-server", "homepage_url": "https://www.armorcode.com/news/armorcode-extends-agentic-ai-in-aspm-platform", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-24", "updated": "2026-05-24", "tags": [ "security", "aspm", "vulnerability-management", "devsecops", "appsec", "remediation", "enterprise" ], "use_cases": [ "Access security vulnerability findings and risk scores through AI agents for automated triage and prioritization", "Enable AI-powered remediation workflows with contextual security data from across the application portfolio", "Integrate ASPM insights into developer AI assistants for security-aware coding and automated fix suggestions" ], "health": "active" }, { "id": "assembled-mcp", "name": "Assembled MCP Server", "description": "MCP server from Assembled enabling AI assistants to query and act on live contact center workforce management data. Provides read and write access across forecasting, scheduling, intraday operations, workforce composition, compliance, and performance analytics. Allows support leaders to diagnose SLA misses, analyze staffing, and adjust schedules through natural language in Claude, ChatGPT, or any MCP-compatible assistant.", "category": "productivity", "endpoint": "assembled-mcp", "homepage_url": "https://www.assembled.com/blog/assembled-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "workforce-management", "contact-center", "wfm", "scheduling", "analytics", "forecasting", "customer-support" ], "use_cases": [ "Query live contact center performance metrics and SLA data through AI assistants using natural language", "Adjust workforce schedules and forecasts in real time through conversational AI connected to Assembled WFM", "Generate cross-platform operational reports by combining Assembled workforce data with CRM and help desk systems" ], "health": "active" }, { "id": "versa-ztna-mcp", "name": "Versa Zero Trust MCP Server", "description": "Zero trust MCP architecture from Versa Networks that acts as a secure broker between AI agents and enterprise infrastructure. Validates every AI agent action against security policies before execution, applying identity verification, least-privilege access controls, and real-time threat inspection to MCP workflows. Extends zero trust networking principles to agentic AI communications.", "category": "infrastructure", "endpoint": "versa-ztna-mcp", "homepage_url": "https://versa-networks.com/blog/zero-trust-mcp-server-securing-the-future-of-agentic-ai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "zero-trust", "security", "ztna", "agent-security", "policy-enforcement", "enterprise", "networking" ], "use_cases": [ "Enforce zero trust security policies on AI agent actions before they reach enterprise MCP servers", "Apply identity verification and least-privilege access controls to all agentic AI communications", "Inspect and validate MCP traffic in real time to prevent unauthorized data access by AI agents" ], "health": "active" }, { "id": "chrome-devtools-mcp", "name": "Chrome DevTools MCP Server", "description": "Official MCP server from the Chrome DevTools team enabling AI agents to control and inspect Chrome browser sessions. Bundles debugging skills including DOM inspection, network monitoring, performance profiling, console access, and screenshot capture. Supports auto-connecting to running Chrome profiles and provides structured browser state to AI coding assistants.", "category": "code", "endpoint": "chrome-devtools-mcp", "homepage_url": "https://github.com/ChromeDevTools/chrome-devtools-mcp", "github_url": "https://github.com/ChromeDevTools/chrome-devtools-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @anthropic-ai/claude-code plugin add chrome-devtools-mcp", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "chrome", "devtools", "debugging", "browser", "dom", "network", "performance", "open-source" ], "use_cases": [ "Debug web applications through AI assistants with direct access to Chrome DevTools inspection capabilities", "Capture screenshots and inspect DOM state during automated browser testing via AI-powered MCP workflows", "Monitor network requests and analyze performance profiles through natural language queries to Chrome DevTools" ], "health": "active" }, { "id": "mendix-mcp", "name": "Mendix MCP Server", "description": "MCP server module from Mendix (Siemens) that turns any Mendix low-code application into an MCP server. Exposes Mendix microflows as tools that AI assistants can discover and invoke through the Model Context Protocol. Available on the Mendix Marketplace, it enables building agentic workflows that connect enterprise business logic to Claude, ChatGPT, or any MCP-compatible host.", "category": "code", "endpoint": "mendix-mcp", "homepage_url": "https://docs.mendix.com/appstore/modules/genai/mcp-modules/mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "sse", "auth": "api-key", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "low-code", "mendix", "siemens", "microflows", "enterprise", "app-development", "agentic" ], "use_cases": [ "Expose Mendix microflows as tools for AI assistants to invoke enterprise business logic through natural language", "Build agentic workflows that combine Mendix low-code applications with AI-powered automation via MCP", "Connect Claude or ChatGPT to custom Mendix applications for data queries and workflow execution without coding" ], "health": "active" }, { "id": "aws-threat-modeling-mcp", "name": "AWS Threat Modeling MCP Server", "description": "Open-source MCP server from AWS Labs for comprehensive threat modeling with automatic code validation. Generates threat models from architecture descriptions, validates threats against actual source code, and produces security recommendations. Supports STRIDE methodology, data flow analysis, and automated mitigation suggestions for cloud-native applications.", "category": "infrastructure", "endpoint": "aws-threat-modeling-mcp", "homepage_url": "https://github.com/awslabs/threat-modeling-mcp-server", "github_url": "https://github.com/awslabs/threat-modeling-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "threat-modeling", "security", "stride", "aws", "code-validation", "architecture", "open-source" ], "use_cases": [ "Generate threat models from architecture descriptions with automatic STRIDE analysis via AI assistants", "Validate identified threats against actual application source code to prioritize real security risks", "Produce actionable security recommendations and mitigation strategies for cloud-native application architectures" ], "health": "active" }, { "id": "mdn-mcp", "name": "MDN MCP Server", "description": "Experimental MCP server from Mozilla providing AI assistants with access to MDN Web Docs search, documentation content, and Browser Compatibility Data (BCD). Enables AI coding tools to query authoritative web platform documentation, check cross-browser API compatibility, and reference current web standards directly through the Model Context Protocol.", "category": "web", "endpoint": "mdn-mcp", "homepage_url": "https://github.com/mdn/mcp", "github_url": "https://github.com/mdn/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "mdn", "mozilla", "web-docs", "browser-compatibility", "web-standards", "documentation", "open-source" ], "use_cases": [ "Query MDN Web Docs through AI coding assistants for authoritative web platform API documentation", "Check cross-browser compatibility data for web APIs and features directly within AI-powered development workflows", "Reference current web standards and best practices through AI assistants connected to Mozilla documentation" ], "health": "active" }, { "id": "ida-mcp", "name": "IDA Pro MCP Server", "description": "High-performance MCP server for headless IDA Pro reverse engineering workflows, written in Rust. Enables AI agents to analyze binaries, disassemble code, inspect functions, cross-references, and data structures through the Model Context Protocol. Features a pooled HTTP architecture for concurrent analysis sessions and supports both IDA Pro and IDA Free.", "category": "code", "endpoint": "ida-mcp", "homepage_url": "https://github.com/blacktop/ida-mcp-rs", "github_url": "https://github.com/blacktop/ida-mcp-rs", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-05-25", "updated": "2026-05-25", "tags": [ "reverse-engineering", "ida-pro", "binary-analysis", "disassembly", "rust", "security-research", "open-source" ], "use_cases": [ "Analyze binary executables and disassemble code through AI assistants connected to IDA Pro via MCP", "Inspect functions, cross-references, and data structures in compiled binaries using natural language queries", "Automate reverse engineering workflows with AI-powered binary analysis through headless IDA Pro sessions" ], "health": "active" }, { "id": "dagu-mcp", "name": "Dagu MCP Server", "description": "Built-in MCP server for the Dagu workflow engine, a lightweight single-binary orchestrator with a Web UI. Enables AI agents to create, update, and run DAG-based workflows with full traceability. Supports declarative YAML definitions, parallel execution, conditional branching, and retries across Linux, macOS, and Windows.", "category": "infrastructure", "endpoint": "dagu-mcp", "homepage_url": "https://github.com/dagucloud/dagu", "github_url": "https://github.com/dagucloud/dagu", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "workflow", "orchestration", "dag", "automation", "devops", "single-binary", "open-source" ], "use_cases": [ "Create and manage DAG-based workflows through AI agents with full execution traceability and retry logic", "Orchestrate multi-step CI/CD and data pipelines using natural language via MCP-connected AI assistants", "Monitor and debug workflow execution across environments through conversational interfaces" ], "health": "active" }, { "id": "agentkey-mcp", "name": "Agentkey", "description": "MCP server from Chainbase Labs that gives AI agents full internet access across web search, social media, crypto, and on-chain data sources. Single plugin with zero extra configuration required. Connects agents to real-time blockchain data, social feeds, and general web search through a unified MCP interface.", "category": "data", "endpoint": "agentkey-mcp", "homepage_url": "https://github.com/chainbase-labs/agentkey", "github_url": "https://github.com/chainbase-labs/agentkey", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "web-search", "crypto", "blockchain", "on-chain", "social-media", "data-access", "open-source" ], "use_cases": [ "Query real-time blockchain and on-chain data through AI assistants without custom integration code", "Combine web search, social media monitoring, and crypto market data in a single agent workflow", "Build AI agents that can research across multiple internet data sources through one unified MCP plugin" ], "health": "active" }, { "id": "funasr-mcp", "name": "FunASR MCP Server", "description": "Industrial-grade speech recognition toolkit from ModelScope with MCP integration. Delivers 170x realtime transcription speed across 50+ languages with speaker diarization, emotion detection, and streaming support. Provides an OpenAI-compatible API and exposes ASR capabilities as MCP tools for AI agent workflows.", "category": "ai", "endpoint": "funasr-mcp", "homepage_url": "https://github.com/modelscope/FunASR", "github_url": "https://github.com/modelscope/FunASR", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "speech-recognition", "asr", "transcription", "multilingual", "speaker-diarization", "emotion-detection", "open-source" ], "use_cases": [ "Transcribe audio in 50+ languages at industrial speed through AI agents connected via MCP", "Add speaker diarization and emotion detection to AI-powered meeting analysis workflows", "Stream real-time speech-to-text into agent pipelines for live captioning and voice-driven automation" ], "health": "active" }, { "id": "zabbix-mcp", "name": "Zabbix MCP Server", "description": "Comprehensive MCP server exposing the complete Zabbix monitoring API with 237 tools. Supports multi-server connections, OAuth 2.1 and bearer token authentication, PDF report generation, and systemd deployment. Compatible with ChatGPT, Claude, VS Code, and other MCP hosts for full infrastructure monitoring through natural language.", "category": "infrastructure", "endpoint": "zabbix-mcp", "homepage_url": "https://github.com/initMAX/zabbix-mcp-server", "github_url": "https://github.com/initMAX/zabbix-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "monitoring", "zabbix", "infrastructure", "observability", "alerting", "multi-server", "open-source" ], "use_cases": [ "Query Zabbix monitoring data and manage alerts through natural language in AI assistants", "Generate PDF infrastructure reports and analyze system health trends via MCP-connected agents", "Manage multi-server Zabbix deployments with OAuth-secured AI agent access to the full Zabbix API" ], "health": "active" }, { "id": "dbmaestro-mcp", "name": "DBmaestro MCP Server", "description": "Enterprise MCP server from DBmaestro that connects AI agents to database DevOps pipelines. Operationalizes database release automation, CI/CD orchestration, source control, and compliance workflows. Supports creating release pipelines with natural language prompts across MS SQL, Oracle, and PostgreSQL environments.", "category": "data", "endpoint": "dbmaestro-mcp", "homepage_url": "https://www.dbmaestro.com/ai/dbmaestro-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "database", "devops", "ci-cd", "release-automation", "compliance", "enterprise", "sql" ], "use_cases": [ "Create and manage database release pipelines across Dev/QA/Prod environments through natural language prompts", "Automate database CI/CD orchestration and compliance checks via AI agents connected to DBmaestro", "Query database source control history and audit trails through conversational AI interfaces" ], "health": "active" }, { "id": "screenforge-mcp", "name": "ScreenForge MCP Server", "description": "Cross-platform UI automation MCP server that generates self-healing pytest scripts from natural language descriptions. Automates interactions across Android, iOS, and web applications with visual element recognition. Produces robust test scripts that adapt to UI changes automatically.", "category": "code", "endpoint": "screenforge-mcp", "homepage_url": "https://mcpmarket.com/server/screenforge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "ui-testing", "automation", "cross-platform", "self-healing", "pytest", "android", "ios", "web" ], "use_cases": [ "Generate self-healing UI test scripts from natural language descriptions for Android, iOS, and web apps", "Automate cross-platform UI interactions through AI agents with visual element recognition", "Build robust test suites that automatically adapt to UI changes without manual script maintenance" ], "health": "active" }, { "id": "symaira-vault-mcp", "name": "Symaira Vault", "description": "Secure credential management MCP server for terminal users and AI agents. Stores and retrieves sensitive secrets with modern encryption and built-in MCP server support. Provides agents with safe access to API keys, tokens, and passwords without exposing raw credentials in prompts or logs.", "category": "infrastructure", "endpoint": "symaira-vault-mcp", "homepage_url": "https://mcpmarket.com/server/symaira-vault", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "credentials", "secrets", "vault", "encryption", "security", "agent-security" ], "use_cases": [ "Give AI agents secure access to API keys and tokens without exposing raw credentials in prompts", "Manage sensitive credentials for terminal workflows with modern encryption and MCP integration", "Centralize secret storage for multi-agent systems with audit-safe credential retrieval" ], "health": "active" }, { "id": "claude-mem-lite-mcp", "name": "Claude Mem Lite", "description": "Persistent long-term memory MCP server for Anthropic Claude Code. Automatically captures coding decisions, bugfixes, patterns, and context across sessions. Provides lightweight memory persistence without external databases, storing knowledge locally for retrieval in future conversations.", "category": "productivity", "endpoint": "claude-mem-lite-mcp", "homepage_url": "https://mcpmarket.com/server/claude-mem-lite", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-26", "updated": "2026-05-26", "tags": [ "memory", "claude-code", "persistence", "context", "coding-assistant", "local-first" ], "use_cases": [ "Preserve coding decisions and debugging context across Claude Code sessions automatically", "Build persistent knowledge bases from coding sessions without external database dependencies", "Retrieve past bugfix patterns and architectural decisions in new Claude Code conversations" ], "health": "active" }, { "id": "google-pay-wallet-mcp", "name": "Google Pay & Wallet MCP Server", "description": "Official MCP server from Google for Pay and Wallet API integration. Provides RAG-powered documentation search, account and integration status checks, JWT and pass validation, performance metrics, and integration management. Enables developers to complete end-to-end Google Pay and Wallet integrations directly from MCP-compatible IDEs and AI assistants.", "category": "payments", "endpoint": "google-pay-wallet-mcp", "homepage_url": "https://developers.google.com/pay/api/web/reference/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "google", "payments", "wallet", "google-pay", "fintech", "enterprise" ], "use_cases": [ "Integrate Google Pay button and checkout flows into web and mobile apps using AI-assisted code generation", "Validate Wallet pass JWTs and JSON definitions on the fly within your development environment", "Monitor Google Pay integration performance metrics and troubleshoot error trends through natural language queries" ], "health": "active" }, { "id": "measured-mcp", "name": "Measured MCP Server", "description": "Enterprise MCP server from Measured that brings marketing incrementality and performance data into AI platforms. Surfaces cross-channel attribution, executive summaries, and optimization insights from 30,000+ experiments across 200+ brands. Connects to ChatGPT, Claude, and Gemini for real-time marketing analytics queries.", "category": "data", "endpoint": "measured-mcp", "homepage_url": "https://www.measured.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "marketing", "analytics", "attribution", "incrementality", "enterprise", "advertising" ], "use_cases": [ "Query cross-channel marketing performance data and incrementality results through AI assistants in real time", "Generate executive marketing summaries and ROI analysis via natural language within ChatGPT or Claude", "Optimize media budget allocation using AI-powered access to marginal return and incremental growth data" ], "health": "active" }, { "id": "agentdb-mcp", "name": "AgentDB", "description": "Self-learning vector memory MCP server that improves search quality up to 36% through agent feedback loops. Consolidates vectors, indexes, learning state, and a cryptographic audit trail into a single portable .rvf file. Provides tiered memory with automatic quality refinement for AI agent workflows.", "category": "ai", "endpoint": "agentdb-mcp", "homepage_url": "https://github.com/ruvnet/agentdb", "github_url": "https://github.com/ruvnet/agentdb", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "vector-memory", "self-learning", "embeddings", "cognitive", "audit-trail", "open-source" ], "use_cases": [ "Give AI agents persistent vector memory that automatically improves search relevance through feedback loops", "Store and retrieve agent knowledge in a single portable file with built-in cryptographic audit trails", "Build cognitive agent systems with self-refining memory that consolidates vectors, indexes, and learning state" ], "health": "active" }, { "id": "eodhd-mcp", "name": "EODHD Financial Data MCP Server", "description": "MCP server for EOD Historical Data APIs exposing 75 read-only tools across multiple transports. Provides comprehensive financial market data including stock prices, fundamentals, options, economic indicators, and technical analysis across global markets. Integrates directly into Claude Code and other MCP clients for AI-powered financial analysis.", "category": "data", "endpoint": "eodhd-mcp", "homepage_url": "https://eodhd.com", "github_url": "https://github.com/EodHistoricalData/EODHD-MCP-Server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "finance", "stocks", "market-data", "fundamentals", "options", "economic-data", "open-source" ], "use_cases": [ "Analyze global stock prices, fundamentals, and technical indicators through AI assistants connected via MCP", "Build AI-powered financial research workflows with access to 75 tools covering equities, options, and economic data", "Query historical and real-time market data across international exchanges using natural language in Claude Code" ], "health": "active" }, { "id": "hippocamp-mcp", "name": "Hippocamp", "description": "Tiered memory system MCP server for AI agents that stores and recalls episodes, facts, preferences, and reflections. Provides local-first portable memory that works across devices. Organizes agent knowledge into structured tiers for efficient retrieval and long-term context preservation.", "category": "ai", "endpoint": "hippocamp-mcp", "homepage_url": "https://github.com/Prageethcs/hippocamp", "github_url": "https://github.com/Prageethcs/hippocamp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "memory", "agent-memory", "episodes", "facts", "local-first", "portable", "open-source" ], "use_cases": [ "Give AI agents structured long-term memory with tiered storage for episodes, facts, and preferences", "Preserve agent context and reflections across sessions and devices with portable local-first storage", "Build agents that recall past interactions and learned preferences through organized memory retrieval" ], "health": "active" }, { "id": "vibe-prospecting-mcp", "name": "Vibe Prospecting", "description": "B2B data MCP server from Explorium that powers AI agents with comprehensive company and contact data for lead generation, company research, and personalized outreach. Provides session-based table-backed data processing with lazy evaluation. Connects to live Explorium business intelligence APIs for real-time prospecting workflows.", "category": "data", "endpoint": "vibe-prospecting-mcp", "homepage_url": "https://github.com/explorium-ai/vibeprospecting-mcp", "github_url": "https://github.com/explorium-ai/vibeprospecting-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "b2b", "prospecting", "lead-generation", "sales", "company-data", "contacts", "open-source" ], "use_cases": [ "Search and qualify B2B leads with comprehensive company and contact data through AI assistants", "Build personalized outreach workflows powered by live business intelligence from Explorium APIs", "Research target companies and contacts using natural language queries within MCP-connected AI tools" ], "health": "active" }, { "id": "openagreements-mcp", "name": "OpenAgreements", "description": "Legal document automation MCP server that fills standard agreement templates and produces signable DOCX files. Includes 40+ templates covering NDAs, cloud service agreements, SAFEs, NVCA financing documents, and employment contracts. Enables AI agents to draft legally structured documents from natural language prompts.", "category": "productivity", "endpoint": "openagreements-mcp", "homepage_url": "https://github.com/open-agreements/open-agreements", "github_url": "https://github.com/open-agreements/open-agreements", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "legal", "contracts", "documents", "nda", "safe", "templates", "docx", "open-source" ], "use_cases": [ "Generate signable NDA, SAFE, and employment agreements from natural language descriptions through AI agents", "Automate legal document drafting with 40+ standard templates filled by AI assistants via MCP", "Produce compliant DOCX contracts for cloud services, financing, and employment directly from AI workflows" ], "health": "active" }, { "id": "openems-mcp", "name": "OpenEMS MCP Server", "description": "MCP server wrapping openEMS 3D FDTD electromagnetic simulation for AI-assisted antenna and RF structure design. Supports patches, dipoles, horns, helices, microstrip, and waveguide structures. Enables AI agents to design, simulate, and analyze RF components through natural language interaction with full-wave 3D electromagnetic simulation.", "category": "code", "endpoint": "openems-mcp", "homepage_url": "https://github.com/RFingAdam/mcp-openems", "github_url": "https://github.com/RFingAdam/mcp-openems", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "rf-engineering", "antenna", "electromagnetic", "simulation", "fdtd", "hardware", "open-source" ], "use_cases": [ "Design antennas and RF structures through natural language interaction with full-wave 3D FDTD simulation", "Simulate and analyze patch, dipole, horn, and microstrip antenna performance using AI-assisted workflows", "Accelerate RF engineering prototyping by letting AI agents run electromagnetic simulations and interpret results" ], "health": "active" }, { "id": "invoicexml-mcp", "name": "InvoiceXML MCP Server", "description": "MCP server exposing the InvoiceXML API for AI-powered global invoice compliance. Handles e-invoicing standards including UBL, Peppol, Factur-X, and country-specific formats. Enables AI agents to generate, validate, and convert invoices across international compliance frameworks without manual format juggling.", "category": "productivity", "endpoint": "invoicexml-mcp", "homepage_url": "https://mcpmarket.com/server/invoicexml", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-05-31", "updated": "2026-05-31", "tags": [ "invoicing", "compliance", "e-invoice", "ubl", "peppol", "fintech", "enterprise" ], "use_cases": [ "Generate compliant e-invoices in UBL, Peppol, and Factur-X formats through AI agent workflows", "Validate and convert invoices across international compliance standards using natural language queries", "Automate global invoice compliance checks and format conversions within AI-powered accounting pipelines" ], "health": "active" }, { "id": "adroll-mcp", "name": "AdRoll MCP Server", "description": "MCP server from AdRoll that connects its multi-channel advertising platform to AI assistants. Enables marketers to retrieve campaign performance data, create campaign drafts with review-before-publish controls, and explore ABM account intelligence through natural language. Supports reporting, campaign management, and account-based marketing workflows in Claude, ChatGPT, n8n, and Cursor.", "category": "data", "endpoint": "adroll-mcp", "homepage_url": "https://www.adroll.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "advertising", "marketing", "campaigns", "abm", "retargeting", "analytics", "enterprise" ], "use_cases": [ "Retrieve and analyze AdRoll campaign performance data and trends through AI assistants using natural language", "Create retargeting and display campaign drafts from AI tools with draft-first controls that stage changes for human review", "Explore ABM account engagement signals and intent data conversationally to prioritize accounts and inform go-to-market planning" ], "health": "active" }, { "id": "stackadapt-mcp", "name": "StackAdapt MCP Server", "description": "MCP server from StackAdapt that extends its Ivy AI marketing assistant into external AI workflows. Provides conversational access to programmatic campaign intelligence across CTV, display, native, audio, DOOH, and linear TV. Enables real-time performance monitoring, creative auditing, and audience-level analysis without logging into the platform directly.", "category": "data", "endpoint": "stackadapt-mcp", "homepage_url": "https://www.stackadapt.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "advertising", "programmatic", "ctv", "display", "native", "audio", "dooh", "enterprise" ], "use_cases": [ "Monitor programmatic campaign pacing, performance metrics, and creative status across all channels through AI assistants", "Query audience-level results and campaign configuration using natural language within Claude or other MCP clients", "Build agent-assisted workflows that continuously surface insights and trigger automated optimizations based on user-defined guardrails" ], "health": "active" }, { "id": "ketryx-mcp", "name": "Ketryx MCP Server", "description": "Compliance intelligence MCP server from Ketryx for safety-critical product development. Enables AI tools like ChatGPT, Claude, and Copilot to securely access live compliance data, check traceability gaps, and verify release readiness. Integrates PLM, ALM, and development tools into a unified knowledge graph queryable through natural language.", "category": "productivity", "endpoint": "ketryx-mcp", "homepage_url": "https://www.ketryx.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "compliance", "medical-devices", "life-sciences", "regulatory", "traceability", "enterprise" ], "use_cases": [ "Query compliance status and traceability gaps across PLM and ALM tools using natural language in AI assistants", "Verify release readiness for regulated products by checking documentation completeness and compliance requirements through AI workflows", "Build AI-powered product development pipelines with full compliance awareness for medical device and life sciences teams" ], "health": "active" }, { "id": "suse-mcp", "name": "SUSE MCP Server", "description": "Infrastructure management MCP server embedded in SUSE Rancher Prime and SUSE Multi-Linux Manager. Enables AI agents to monitor, troubleshoot, and optimize Linux servers and Kubernetes clusters. Includes AI engineering skills for identifying system faults, correlating logs, and submitting patches or service restarts through autonomous workflows.", "category": "infrastructure", "endpoint": "suse-mcp", "homepage_url": "https://www.suse.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "infrastructure", "kubernetes", "linux", "rancher", "devops", "monitoring", "enterprise" ], "use_cases": [ "Monitor and troubleshoot Kubernetes clusters and Linux servers through AI agents connected to Rancher Prime via MCP", "Automate infrastructure remediation by letting AI agents identify faults, correlate logs, and submit patches or service restarts", "Manage multi-distribution Linux environments using natural language commands within AI-powered operations workflows" ], "health": "active" }, { "id": "microsoft-release-communications-mcp", "name": "Microsoft Release Communications MCP Server", "description": "Official MCP server from Microsoft that provides programmatic access to Microsoft 365 Roadmap and Azure Updates data. Exposes four tools for searching, filtering, and retrieving feature release information using natural language. Works with VS Code, Visual Studio, Claude Code, Cursor, and other MCP-compatible clients. Free to use with no authentication required.", "category": "data", "endpoint": "microsoft-release-communications-mcp", "homepage_url": "https://learn.microsoft.com/en-us/microsoft-365/admin/manage/mrc-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "microsoft", "azure", "microsoft-365", "roadmap", "release-management", "enterprise" ], "use_cases": [ "Query Microsoft 365 Roadmap and Azure Updates for upcoming feature releases and retirement schedules through AI assistants", "Track Azure service updates, general availability announcements, and security changes using natural language in VS Code or Claude Code", "Generate release briefings and compliance reports for IT teams by filtering roadmap data by product, platform, and release ring" ], "health": "active" }, { "id": "madhive-mcp", "name": "Madhive Maverick MCP Server", "description": "MCP server from Madhive that exposes its local-first demand-side platform to external AI tools and LLMs. Enables natural language interaction with campaigns, creatives, audiences, and publisher groups across local CTV and broadcast inventory. Part of the Maverick AI intelligence layer trained on over a decade of local advertising data from 50,000+ daily campaigns.", "category": "data", "endpoint": "madhive-mcp", "homepage_url": "https://www.madhive.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "advertising", "ctv", "local-media", "dsp", "programmatic", "broadcast", "enterprise" ], "use_cases": [ "Manage and query local CTV and broadcast advertising campaigns through natural language commands in external AI tools", "Connect enterprise LLMs and internal analytics tools directly to Madhive's DSP for real-time local campaign intelligence", "Automate media plan creation and campaign optimization for local advertisers using AI agents with access to local-market performance data" ], "health": "active" }, { "id": "detectify-mcp", "name": "Detectify MCP Server", "description": "Security testing MCP server from Detectify that brings vulnerability scanning and attack surface data into AI-driven development workflows. AI agents can receive remediation tasks, generate patches, trigger validation scans, and present verified fixes for human review. Supports conversational querying of scan results, asset monitoring, and severity-based finding prioritization.", "category": "infrastructure", "endpoint": "detectify-mcp", "homepage_url": "https://detectify.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "security", "vulnerability-scanning", "appsec", "attack-surface", "remediation", "enterprise" ], "use_cases": [ "Automate find-and-fix workflows where AI agents generate patches for vulnerabilities and trigger Detectify validation scans", "Query scan results and monitor asset security status through natural language interactions with AI assistants", "Surface high-severity findings in real time within AI-driven development environments for faster remediation cycles" ], "health": "active" }, { "id": "vectra-ai-mcp", "name": "Vectra AI MCP Server", "description": "Security operations MCP server from Vectra AI that gives AI assistants standardized access to threat detection and investigation capabilities. Enables security analysts to investigate incidents, reconstruct attack timelines, and generate context-rich reports through natural language prompts in Claude Desktop, Cursor, and other MCP clients. Requires no changes to existing Vectra deployments.", "category": "infrastructure", "endpoint": "vectra-ai-mcp", "homepage_url": "https://www.vectra.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-01", "updated": "2026-06-01", "tags": [ "security", "threat-detection", "soc", "incident-response", "siem", "enterprise" ], "use_cases": [ "Investigate security incidents and reconstruct attack timelines through natural language queries in AI assistants", "Generate context-rich security reports and visualizations for management using conversational prompts in MCP-connected tools", "Democratize security expertise by letting analysts of all skill levels access Vectra threat intelligence through AI-powered interfaces" ], "health": "active" }, { "id": "strava-mcp", "name": "Strava MCP Connector", "description": "Official MCP connector from Strava that gives subscribers conversational access to their fitness and training data through Claude. Supports full activity history, per-second stream data (heart rate, pace, power), GPS routes, club and event data, and subscription-tier training analytics. Read-only, OAuth-scoped, and revocable from Strava settings. First major connected fitness platform to ship a native AI assistant integration.", "category": "data", "endpoint": "https://mcp.strava.com/mcp", "homepage_url": "https://www.strava.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http strava-mcp https://mcp.strava.com/mcp", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "fitness", "health", "running", "cycling", "training", "sports", "wearables", "consumer" ], "use_cases": [ "Analyze training history, fitness trends, and workout patterns through natural language queries in Claude", "Compare cross-sport activity data across running, cycling, strength, and other sports to optimize training plans", "Access subscription-tier training analytics like readiness, goal planning, and gear tracking outside the Strava app" ], "health": "active" }, { "id": "sectigo-mcp", "name": "Sectigo MCP Server", "description": "First production-ready MCP server for certificate lifecycle management from Sectigo. Enables AI agents and assistants to discover, monitor, renew, and manage SSL/TLS certificates across enterprise environments. Designed for security and IT operations teams adopting agentic AI, providing programmatic access to Sectigo Certificate Manager capabilities through standardized MCP interfaces.", "category": "infrastructure", "endpoint": "sectigo-mcp", "homepage_url": "https://www.sectigo.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "security", "certificates", "ssl", "tls", "pki", "clm", "enterprise", "devops" ], "use_cases": [ "Automate SSL/TLS certificate discovery, monitoring, and renewal through AI agents connected to Sectigo Certificate Manager", "Integrate certificate lifecycle management into AI-driven security operations and IT workflows for faster response times", "Query certificate status, expiration timelines, and compliance posture across enterprise environments using natural language" ], "health": "active" }, { "id": "m-science-mcp", "name": "M Science MCP Server", "description": "Investment research MCP server from M Science (Jefferies) that gives institutional investors programmatic access to analyst-curated data and research through AI assistants. Covers 1,440+ KPIs across 1,400+ companies with near real-time updates. Extends the same infrastructure powering Maddie, M Science's AI copilot. Integrates with ChatGPT, Claude, and internally developed AI systems.", "category": "data", "endpoint": "m-science-mcp", "homepage_url": "https://www.mscience.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "finance", "investment", "research", "analytics", "institutional", "alternative-data", "enterprise" ], "use_cases": [ "Access analyst-curated investment data and KPIs across 1,400+ companies through AI assistants for faster research workflows", "Build AI-driven investment workflows with point-in-time analytics, backtesting, and longitudinal analysis using M Science data", "Integrate structured datasets with deep analyst research context into proprietary AI systems and internal copilots" ], "health": "active" }, { "id": "lifesight-mcp", "name": "Lifesight MCP Server", "description": "Marketing measurement MCP server from Lifesight that gives marketing and finance teams no-code access to live causal measurement models directly inside Claude and ChatGPT. Enables natural language querying of marketing mix models, attribution data, and incrementality analysis without requiring data science expertise. Designed for real-time budget optimization and cross-channel performance analysis.", "category": "data", "endpoint": "lifesight-mcp", "homepage_url": "https://www.lifesight.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "marketing", "analytics", "measurement", "attribution", "mmm", "incrementality", "enterprise" ], "use_cases": [ "Query live marketing mix models and attribution data through natural language in Claude or ChatGPT without data science skills", "Optimize marketing budgets in real time by analyzing cross-channel incrementality and causal impact through AI assistants", "Generate marketing performance reports and budget recommendations using conversational prompts connected to live measurement data" ], "health": "active" }, { "id": "noma-agent-access-control", "name": "Noma Agent Access Control", "description": "Security governance platform from Noma that discovers, governs, and enforces access policies for AI agents and MCP servers across the enterprise. Assigns each autonomous agent a distinct, attributable identity when connecting to MCP servers and tools. Provides visibility into which agents access which tools, enforces least-privilege policies, and enables security teams to monitor agentic AI behavior at scale.", "category": "infrastructure", "endpoint": "noma-agent-access-control", "homepage_url": "https://www.noma.security", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "security", "governance", "access-control", "agent-identity", "compliance", "enterprise", "zero-trust" ], "use_cases": [ "Discover and inventory all AI agents and MCP server connections across the enterprise for security visibility", "Enforce least-privilege access policies for autonomous agents connecting to MCP servers and external tools", "Monitor and audit agentic AI behavior at scale with attributable agent identities and access governance controls" ], "health": "active" }, { "id": "ataccama-mcp", "name": "Ataccama MCP Server", "description": "Data trust and quality MCP server from Ataccama that delivers trusted data context for AI workloads on Snowflake. Provides a Data Trust Index with real-time reliability signals combining data quality scores and business context. Part of Ataccama ONE platform, enabling AI agents and Snowflake Cortex to query data quality, governance metadata, and trust scores through standardized MCP interfaces.", "category": "data", "endpoint": "ataccama-mcp", "homepage_url": "https://www.ataccama.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "data-quality", "governance", "snowflake", "data-trust", "metadata", "enterprise", "data-catalog" ], "use_cases": [ "Query data quality scores and trust signals for Snowflake datasets through AI agents before running analytics or training models", "Integrate data governance metadata and business context into AI-powered workflows for more reliable and explainable outputs", "Monitor and validate data product quality in real time through MCP-connected AI assistants and Snowflake Cortex" ], "health": "active" }, { "id": "datacap-mcp", "name": "Datacap MCP Server", "description": "Payment integration MCP server from Datacap Systems that connects its developer documentation, sample code, and certified integration patterns directly to AI-assisted coding environments. Works with Cursor, VS Code, Claude Code, and other MCP-compatible IDEs. Enables developers to pull Datacap code snippets, reference implementations, and complete sample projects into active projects grounded in vetted documentation.", "category": "code", "endpoint": "datacap-mcp", "homepage_url": "https://datacapsystems.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "payments", "pos", "integration", "developer-tools", "documentation", "ecommerce" ], "use_cases": [ "Pull certified Datacap payment integration code snippets and reference implementations directly into IDE projects via AI assistants", "Accelerate POS payment solution development by querying Datacap documentation and sample projects through natural language in Cursor or VS Code", "Generate on-spec payment integration code grounded in vetted Datacap patterns for faster certification and production readiness" ], "health": "active" }, { "id": "weld-mcp", "name": "Weld MCP Server", "description": "Data modeling MCP server from Weld that connects its ELT platform to AI coding tools. Enables AI assistants in IDEs to access Weld data models, warehouse schemas, and transformation logic for context-aware code generation. Part of Weld's May 2026 product update alongside GitHub integration for managing data models as code. Supports Snowflake, BigQuery, and other warehouse targets.", "category": "data", "endpoint": "weld-mcp", "homepage_url": "https://weld.app", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-03", "updated": "2026-06-03", "tags": [ "elt", "data-modeling", "warehouse", "snowflake", "bigquery", "developer-tools", "analytics" ], "use_cases": [ "Give AI coding assistants access to Weld data models and warehouse schemas for context-aware SQL and transformation code generation", "Query and explore data pipeline configurations and transformation logic through natural language in MCP-connected IDEs", "Manage data models as code with AI-assisted development workflows connected to Weld's ELT platform and GitHub integration" ], "health": "active" }, { "id": "stensul-mcp", "name": "Stensul MCP Server", "description": "Governed email creation MCP server from Stensul that connects AI tools and agents to enterprise marketing controls. Enables AI-generated email campaigns to pass through approved templates, brand rules, compliance checks, accessibility requirements, and approval workflows before going live. Built on the Model Context Protocol standard so any MCP-compatible AI tool can create marketing content inside the governance layer enterprises require to ship safely.", "category": "productivity", "endpoint": "stensul-mcp", "homepage_url": "https://stensul.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "marketing", "email", "governance", "compliance", "brand-safety", "enterprise", "campaigns" ], "use_cases": [ "Connect AI tools and agents to Stensul governed creation workflows so AI-generated email campaigns pass brand, compliance, and accessibility checks before shipping", "Enable marketing teams to use AI assistants for campaign creation while maintaining enterprise governance over templates, modules, and approval workflows", "Extend Stensul brand and compliance controls to AI-assisted creation happening outside the Stensul interface in tools like Claude and ChatGPT" ], "health": "active" }, { "id": "digimarc-mcp", "name": "Digimarc Provenance MCP Server", "description": "Content provenance and verification MCP server from Digimarc that enables AI agents and orchestration frameworks to stamp, verify, log, audit, and retrieve provenance information through MCP-compatible interfaces. Grounded in the C2PA standard adopted by Adobe, Google, Microsoft, and OpenAI. Every provenance seal is policy-gated, issued only when agent identity, artifact integrity, and request timing satisfy defined trust criteria. Backed by Digimarc's Illuminate platform with optional watermarking for durability when metadata is stripped during processing.", "category": "infrastructure", "endpoint": "digimarc-mcp", "homepage_url": "https://www.digimarc.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "provenance", "c2pa", "verification", "security", "trust", "watermarking", "content-authenticity", "audit" ], "use_cases": [ "Stamp and verify content provenance in AI agent workflows using the C2PA standard through MCP-compatible interfaces", "Audit and trace what autonomous AI agents consumed and produced with cryptographically verifiable provenance records", "Integrate provenance verification directly into content and automation pipelines without managing underlying cryptographic infrastructure" ], "health": "active" }, { "id": "alloydb-remote-mcp", "name": "Google AlloyDB Remote MCP Server", "description": "Fully managed remote MCP server from Google Cloud that gives AI agents and assistants secure access to operational data in AlloyDB for PostgreSQL. Generally available as of June 2026. Eliminates the need to self-host MCP infrastructure by providing a Google-managed endpoint with enterprise-grade authentication, networking, and audit logging. Designed for use with the Google Agent Development Kit (ADK) and other MCP-compatible clients including Claude, Cursor, and VS Code.", "category": "data", "endpoint": "alloydb-remote-mcp", "homepage_url": "https://cloud.google.com/alloydb", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "database", "postgresql", "google-cloud", "managed", "alloydb", "enterprise", "data-access" ], "use_cases": [ "Give AI agents secure, managed access to AlloyDB PostgreSQL databases without self-hosting MCP server infrastructure", "Query operational data in AlloyDB through natural language using MCP-compatible AI assistants and the Google Agent Development Kit", "Connect enterprise AI workflows to AlloyDB with Google-managed authentication, networking controls, and audit logging" ], "health": "active" }, { "id": "bybit-trading-mcp", "name": "Bybit Trading MCP Server", "description": "Official MCP server from Bybit that enables AI assistants to interact directly with the Bybit cryptocurrency exchange. Supports account queries, market data retrieval, order placement, and position management through MCP-compatible clients including Claude, Cursor, and VS Code. Provides programmatic access to Bybit trading APIs through natural language interfaces for algorithmic trading research and portfolio management.", "category": "data", "endpoint": "bybit-trading-mcp", "homepage_url": "https://www.bybit.com", "github_url": "https://github.com/bybit-exchange/trading-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "crypto", "trading", "exchange", "finance", "defi", "market-data", "portfolio" ], "use_cases": [ "Query Bybit account balances, positions, and order history through AI assistants using natural language", "Place and manage cryptocurrency trades on Bybit through MCP-compatible AI tools for algorithmic trading research", "Retrieve real-time market data and trading analytics from Bybit through AI-powered development environments" ], "health": "active" }, { "id": "salesforce-marketing-mcp", "name": "Salesforce Marketing MCP Server", "description": "Marketing-specific MCP server from Salesforce that extends Agentforce with AI agent access to marketing data, campaigns, and automation workflows. Enables AI assistants to query campaign performance, audience segments, and marketing analytics through standardized MCP interfaces. Part of the Agentforce Marketing platform announced at Salesforce Connections 2026, connecting external AI tools to Salesforce marketing capabilities with governed, enterprise-grade access controls.", "category": "data", "endpoint": "salesforce-marketing-mcp", "homepage_url": "https://www.salesforce.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "marketing", "crm", "salesforce", "agentforce", "campaigns", "analytics", "enterprise", "automation" ], "use_cases": [ "Access Salesforce marketing campaign data and performance analytics through AI assistants via MCP-connected interfaces", "Enable AI agents to interact with Agentforce marketing automation workflows including audience segmentation and campaign management", "Bridge external AI tools like Claude and ChatGPT into Salesforce marketing data with enterprise-grade access controls and governance" ], "health": "active" }, { "id": "actian-data-steward-mcp", "name": "Actian Agentic Data Steward", "description": "Agentic data stewardship MCP server from Actian that helps maintain semantic consistency across enterprise AI systems. Grounded in the Actian Data Intelligence Platform's federated knowledge graph, semantic layer, data products, and data contracts. Enables AI agents to query and enforce data definitions, lineage, and business semantics to ensure AI-generated outputs align with authoritative enterprise data models.", "category": "data", "endpoint": "actian-data-steward-mcp", "homepage_url": "https://www.actian.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "data-governance", "semantics", "knowledge-graph", "data-quality", "enterprise", "metadata", "data-contracts" ], "use_cases": [ "Query and enforce data definitions and business semantics across enterprise AI systems using the Actian federated knowledge graph", "Maintain semantic consistency in AI agent outputs by grounding them in authoritative data products and data contracts", "Enable AI agents to access data lineage and governance metadata through standardized MCP interfaces for trustworthy analytics" ], "health": "active" }, { "id": "resonite-mcp", "name": "Resonite MCP Server", "description": "Open-source MCP server for the Resonite social VR platform built on FastMCP. Provides comprehensive integration between AI assistants and Resonite, enabling natural language interaction with virtual world objects, user sessions, assets, and social features. Supports querying active sessions, managing inventory, interacting with in-world objects, and controlling avatar state through MCP-compatible clients.", "category": "productivity", "endpoint": "resonite-mcp", "homepage_url": "https://resonite.com", "github_url": "https://github.com/sandraschi/resonite-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "vr", "social", "metaverse", "gaming", "3d", "virtual-worlds", "open-source" ], "use_cases": [ "Interact with Resonite social VR sessions, worlds, and objects through natural language in AI assistants", "Manage Resonite inventory and virtual assets using MCP-compatible AI tools for creators and developers", "Query active VR sessions, user presence, and social features on the Resonite platform through AI-powered interfaces" ], "health": "active" }, { "id": "comp-compliance-mcp", "name": "Comp Compliance MCP Server", "description": "Open-source compliance automation MCP server from Comp AI that connects AI agents to compliance frameworks, evidence collection, and audit workflows. Enables AI assistants to query compliance status, manage evidence artifacts, and automate control assessments across SOC 2, ISO 27001, and other frameworks. Part of the Comp open-source compliance platform designed for startups and growing companies.", "category": "infrastructure", "endpoint": "comp-compliance-mcp", "homepage_url": "https://trycomp.ai", "github_url": "https://github.com/trycompai/comp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-04", "updated": "2026-06-04", "tags": [ "compliance", "soc2", "iso27001", "audit", "governance", "open-source", "security" ], "use_cases": [ "Query compliance status and control assessments across SOC 2, ISO 27001, and other frameworks through AI assistants", "Automate evidence collection and audit workflows using AI agents connected to the Comp compliance platform", "Manage compliance artifacts and track audit readiness through natural language in MCP-compatible development environments" ], "health": "active" }, { "id": "truelist-mcp", "name": "Truelist MCP Server", "description": "Hosted MCP server from Truelist that brings email validation directly into AI assistants and development environments. Enables AI agents to validate individual emails, manage batch verification jobs, check account usage, and explore validation results through MCP-compatible clients including Claude, Cursor, and VS Code. Eliminates the need for direct API integration by exposing Truelist email verification capabilities as MCP tools that any compatible client can invoke.", "category": "communication", "endpoint": "truelist-mcp", "homepage_url": "https://truelist.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "email", "validation", "verification", "deliverability", "marketing", "data-quality" ], "use_cases": [ "Validate email addresses in real time from inside AI assistants without switching to a separate dashboard or API client", "Run and monitor batch email verification jobs through natural language in MCP-compatible development environments", "Check email deliverability and account usage metrics through conversational interfaces for marketing and sales workflows" ], "health": "active" }, { "id": "ontra-mcp", "name": "Ontra MCP Server", "description": "MCP server from Ontra that gives AI assistants real-time access to private markets fund data stored in the Ontra platform. Generally available as of June 2026. Enables fund managers to query entity information including ownership structures, jurisdictions, tax classifications, filing deadlines, directors and officers, and authorized signatories through Claude, ChatGPT, and other MCP-compatible clients. Designed for legal, compliance, tax, finance, and deal teams managing complex private equity and fund portfolios.", "category": "data", "endpoint": "ontra-mcp", "homepage_url": "https://www.ontra.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "private-markets", "fund-management", "finance", "legal", "compliance", "entity-management", "private-equity" ], "use_cases": [ "Query fund entity ownership structures, jurisdictions, and tax classifications through AI assistants in natural language", "Map portfolio relationships and hierarchies across private equity holdings using MCP-connected AI tools", "Pull real-time fund data for compliance reviews, reporting, and transaction preparation without CSV exports or custom API work" ], "health": "active" }, { "id": "indicaonline-mcp", "name": "IndicaOnline AI MCP Server", "description": "MCP-native analytics and automation server from IndicaOnline purpose-built for cannabis retail. Exposes the entire POS environment through the Model Context Protocol so any MCP-compatible AI client can query live dispensary data in natural language. Includes six specialized autonomous agents: Revenue Analyst, Delivery Optimizer, Customer Intelligence Agent, Inventory Watchdog, Loss Prevention Monitor, and Brand Strategist. Supports read and write actions through the IndicaOnline Open API with full audit trails.", "category": "data", "endpoint": "indicaonline-mcp", "homepage_url": "https://indicaonline.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "cannabis", "retail", "pos", "analytics", "inventory", "delivery", "automation" ], "use_cases": [ "Query live dispensary POS data including sales performance, brand analytics, and customer segments through AI assistants in natural language", "Monitor inventory levels, delivery operations, and loss prevention using six specialized autonomous agents exposed as MCP tools", "Execute write actions like editing product profiles, creating discounts, and placing delivery orders through AI-assisted workflows with full audit trails" ], "health": "active" }, { "id": "infoblox-mcp", "name": "Infoblox MCP Server", "description": "MCP server from Infoblox that makes enterprise network, security, and asset intelligence available to third-party AI assistants and agents through the Model Context Protocol. Part of the Infoblox IQ agentic operations platform announced June 2026. Provides access to DNS queries, DHCP leases, IP address assignments, device activity, and security events flowing through the Infoblox Platform. Built on 25 years of DDI operational data from thousands of enterprise deployments including the majority of Fortune 100 companies.", "category": "infrastructure", "endpoint": "infoblox-mcp", "homepage_url": "https://www.infoblox.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "networking", "security", "dns", "dhcp", "ipam", "enterprise", "infrastructure", "threat-defense" ], "use_cases": [ "Connect third-party AI agents and assistants to authoritative enterprise DNS, DHCP, and IP address management data through a standard MCP interface", "Enable agentic security workflows that investigate DNS threats, correlate network events, and recommend remediation actions using Infoblox intelligence", "Build agent-to-agent workflows that combine Infoblox network truth with other enterprise AI systems for cross-domain IT operations" ], "health": "active" }, { "id": "zoho-payments-mcp", "name": "Zoho Payments MCP Server", "description": "MCP server from Zoho that connects conversational AI clients directly with Zoho Payments for handling payment operations through natural language. Enables creating payment sessions, generating and managing payment links, processing refunds, managing customer records, and tracking payouts through MCP-compatible clients including Claude and ChatGPT. All interactions are authenticated and traceable with configurable permission controls for compliance in payment workflows.", "category": "payments", "endpoint": "zoho-payments-mcp", "homepage_url": "https://www.zoho.com/payments", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "payments", "fintech", "invoicing", "refunds", "zoho", "enterprise", "automation" ], "use_cases": [ "Create payment links, process refunds, and manage customer records in Zoho Payments through conversational AI interfaces", "Track payouts and review transaction details through natural language queries in MCP-compatible AI clients", "Embed payment operations into AI-driven sales, support, and finance workflows without switching to the Zoho Payments dashboard" ], "health": "active" }, { "id": "n-able-uem-mcp", "name": "N-able UEM MCP Server", "description": "MCP server from N-able that connects AI assistants including ChatGPT, Claude, and Microsoft Copilot to live Unified Endpoint Management data. Enables IT teams to query systems, check device health, and take controlled management actions in real time through natural language. Part of N-able's AI-native UEM platform targeting up to 70% faster IT operations for managed service providers and enterprise IT departments.", "category": "infrastructure", "endpoint": "n-able-uem-mcp", "homepage_url": "https://www.n-able.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "it-management", "endpoint-management", "msp", "monitoring", "device-management", "enterprise" ], "use_cases": [ "Query endpoint health, device inventory, and system status through AI assistants connected to live N-able UEM data", "Execute controlled IT management actions across managed endpoints using natural language through MCP-compatible AI tools", "Enable MSP and IT help desk teams to resolve endpoint issues faster by asking AI assistants instead of navigating management consoles" ], "health": "active" }, { "id": "sparx-ea-mcp", "name": "Sparx Enterprise Architect MCP Server", "description": "MCP server from Sparx Systems that connects AI assistants to Enterprise Architect models and repositories. Enables querying and interacting with UML diagrams, architecture models, requirements, and project documentation through MCP-compatible clients. Supports reading model elements, navigating package hierarchies, and extracting structured data from Enterprise Architect projects for use in AI-assisted architecture review, documentation generation, and model analysis workflows.", "category": "code", "endpoint": "sparx-ea-mcp", "homepage_url": "https://www.sparxsystems.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "uml", "architecture", "modeling", "enterprise-architecture", "documentation", "design" ], "use_cases": [ "Query and navigate Enterprise Architect UML models, packages, and diagrams through AI assistants using natural language", "Generate documentation and architecture summaries from Enterprise Architect repositories through MCP-connected AI tools", "Review and analyze software architecture models with AI assistance for compliance, consistency, and design pattern verification" ], "health": "active" }, { "id": "eu-compliance-mcp", "name": "EU Regulations MCP Server", "description": "Open-source MCP server from Ansvar Systems that provides AI agents with structured access to EU regulations via EUR-Lex. Covers GDPR, AI Act, DORA, NIS2, eIDAS, MiCA, DSA, DMA, CRA, and other major EU legislative frameworks. Enables querying regulation text, cross-referencing articles, and checking compliance requirements through MCP-compatible clients. Built as an internal compliance tool and open-sourced for teams building AI products targeting EU markets.", "category": "data", "endpoint": "eu-compliance-mcp", "homepage_url": "https://github.com/Ansvar-Systems/EU_compliance_MCP", "github_url": "https://github.com/Ansvar-Systems/EU_compliance_MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-05", "updated": "2026-06-05", "tags": [ "compliance", "eu", "gdpr", "ai-act", "regulations", "legal", "open-source", "governance" ], "use_cases": [ "Query EU regulation text including GDPR, AI Act, DORA, and NIS2 through AI assistants for compliance research and analysis", "Cross-reference articles across EU legislative frameworks to understand overlapping requirements for product and service compliance", "Build compliance-aware AI workflows that check requirements against EU regulations before shipping features to EU markets" ], "health": "active" }, { "id": "coinbase-base-mcp", "name": "Coinbase Base MCP Server", "description": "MCP server from Coinbase that connects AI assistants to the Base Layer 2 network, enabling onchain interactions through natural language. Lets AI agents check wallet balances across Base and EVM chains, view transaction history, initiate token transfers, execute swaps on Uniswap and Aerodrome, interact with lending protocols like Morpho and Moonwell, and trade perpetuals on Avantis. Non-custodial design means the MCP server never holds private keys. Every transaction generates a secure approval link that opens the Base Account interface for explicit user sign-off. Authentication uses OAuth 2.1 through Base Account infrastructure.", "category": "payments", "endpoint": "coinbase-base-mcp", "homepage_url": "https://www.coinbase.com/developer-platform", "x402": true, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "crypto", "defi", "blockchain", "wallet", "ethereum", "base", "coinbase", "trading", "x402" ], "use_cases": [ "Execute DeFi transactions including token swaps, lending, and transfers on Base through AI assistants using natural language prompts", "Monitor portfolio balances and transaction history across Base and EVM-compatible chains through MCP-connected AI tools", "Build agentic commerce workflows where AI agents manage onchain operations with non-custodial security and explicit user approval for every transaction" ], "health": "active" }, { "id": "looker-managed-mcp", "name": "Looker Managed MCP Server", "description": "Google Cloud managed MCP server that gives AI agents direct access to Looker business intelligence data without infrastructure setup. Embedded in the Looker platform as a zero-config, fully managed service. Enables AI assistants and agents to query Looker Explores, run reports, access dashboards, and retrieve governed business metrics through the Model Context Protocol. Supports Claude, ChatGPT, Cursor, and other MCP-compatible clients. Currently in preview. Leverages Looker's existing semantic model and row-level access controls so agents inherit the same data governance policies as human users.", "category": "data", "endpoint": "looker-managed-mcp", "homepage_url": "https://cloud.google.com/looker", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "analytics", "business-intelligence", "google-cloud", "dashboards", "reporting", "data-governance", "enterprise" ], "use_cases": [ "Query Looker business intelligence data through AI assistants using natural language without navigating the Looker UI", "Build AI agent workflows that access governed business metrics and dashboards with row-level access controls inherited from Looker", "Enable cross-system analytics by connecting AI tools to Looker's semantic model for consistent metric definitions across the organization" ], "health": "active" }, { "id": "zip-procurement-mcp", "name": "Zip Procurement MCP Server", "description": "Procurement-native MCP server from Zip that pipes procurement data directly into AI assistants like Claude and ChatGPT without sacrificing audit trails or compliance controls. Announced June 2026 alongside Zip's AI Superagents suite. Enables finance and procurement teams to query purchase orders, vendor information, contract details, spend analytics, and approval workflows through natural language. Designed to prevent shadow AI usage where teams upload sensitive procurement data into personal AI accounts. All interactions maintain full audit trails and comply with enterprise governance frameworks.", "category": "data", "endpoint": "zip-procurement-mcp", "homepage_url": "https://zip.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "procurement", "finance", "compliance", "spend-management", "enterprise", "governance", "audit" ], "use_cases": [ "Query procurement data including purchase orders, vendor details, and spend analytics through AI assistants with full audit trail compliance", "Prevent shadow AI usage by giving finance teams governed access to procurement intelligence through MCP-connected AI tools", "Automate procurement workflows including contract review and vendor analysis through AI agents operating within enterprise governance frameworks" ], "health": "active" }, { "id": "htag-analytics-mcp", "name": "HtAG Analytics MCP Server", "description": "MCP server suite from HtAG Analytics that provides AI agents with live access to Australian property intelligence. Includes three MCP servers: an Intelligence Server with 33 tools for address, property, and market data covering 14.8 million Australian addresses and over 100 market metrics; a Trends Server with five tools for market trend analysis; and a Planning Server for development and zoning data. Native integrations with Claude and Perplexity. Part of the HtAG Developer Portal launched June 2026 for building property intelligence agents.", "category": "data", "endpoint": "htag-analytics-mcp", "homepage_url": "https://developer.htagai.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "property", "real-estate", "analytics", "australia", "market-data", "intelligence", "geospatial" ], "use_cases": [ "Query Australian property data including valuations, ownership, and market metrics across 14.8 million addresses through AI assistants", "Build property intelligence agents that analyze market trends, development potential, and zoning data using HtAG's MCP server suite", "Enable real estate professionals to access live property analytics and comparable sales through natural language queries in Claude or Perplexity" ], "health": "active" }, { "id": "explorium-mcp", "name": "Explorium MCP Server", "description": "MCP server from Explorium that routes live company news and business signals to AI agents for revenue operations workflows. Surfaces funding rounds, leadership changes, product launches, expansion announcements, layoffs, and partnerships as structured data through MCP-compatible clients. Purpose-built for RevOps teams to enrich CRM records, trigger outbound sequences, and qualify leads using real-time business intelligence. Covers thousands of companies with signal categorization and relevance scoring.", "category": "data", "endpoint": "explorium-mcp", "homepage_url": "https://www.explorium.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "company-news", "business-intelligence", "revops", "sales", "signals", "leads", "crm" ], "use_cases": [ "Enrich CRM records with real-time company signals including funding rounds, leadership changes, and product launches through AI assistants", "Trigger outbound sales sequences automatically when AI agents detect relevant business events through Explorium's MCP server", "Qualify leads and accounts using live business intelligence data surfaced through natural language queries in MCP-connected AI tools" ], "health": "active" }, { "id": "coinbase-payments-mcp", "name": "Coinbase Payments MCP Server", "description": "MCP server from Coinbase that gives AI agents access to crypto wallets, fiat onramps, and stablecoin payment capabilities through the x402 protocol. Enables agents running in Claude, ChatGPT, Codex, and Gemini to create wallets, onramp fiat to crypto, and execute USDC payments on Base with sub-penny transaction costs. No API key required for setup. Users configure spend limits and manage permissions through a desktop interface. Built on x402, the open web-native payment protocol co-developed with Cloudflare that revives the HTTP 402 Payment Required status code for instant micropayments.", "category": "payments", "endpoint": "coinbase-payments-mcp", "homepage_url": "https://www.coinbase.com/developer-platform", "github_url": "https://github.com/coinbase/payments-mcp", "x402": true, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "payments", "crypto", "stablecoin", "usdc", "x402", "coinbase", "micropayments", "onramp" ], "use_cases": [ "Enable AI agents to make stablecoin micropayments for APIs, data, and services using the x402 protocol through natural language commands", "Give AI agents wallet creation and fiat onramp capabilities with configurable spend limits and user-managed permissions", "Build agentic commerce applications where AI agents autonomously pay for compute, data access, and third-party services using USDC on Base" ], "health": "active" }, { "id": "airfocus-mcp", "name": "airfocus MCP Server", "description": "Bidirectional MCP server from airfocus by Lucid that provides secure access to structured product management data including roadmaps, objectives, OKRs, priorities, and customer feedback. Pushes product context out to external AI tools and copilots such as Claude, ChatGPT, and Microsoft Copilot. Part of the airfocus Product Intelligence Platform launched June 2026. Supports use cases including cross-system search inside Copilot Studio, daily briefing agents that combine airfocus with email and calendar, and roadmap-as-knowledge-graph workflows for AI agents that need product context to reason effectively.", "category": "productivity", "endpoint": "airfocus-mcp", "homepage_url": "https://airfocus.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "product-management", "roadmap", "okrs", "prioritization", "feedback", "strategy", "enterprise" ], "use_cases": [ "Access roadmaps, objectives, and product priorities from airfocus through Claude, ChatGPT, or Copilot for AI-assisted product planning", "Build daily briefing agents that synthesize airfocus product data with email, calendar, and team communication tools", "Enable AI agents to reason about product strategy by providing them with structured roadmap and customer feedback context through MCP" ], "health": "active" }, { "id": "scenario-mcp", "name": "Scenario MCP Server", "description": "MCP server from Scenario.com that exposes game art and creative asset generation tools to AI agents and coding assistants. Provides 12 creative tools for generating, editing, and managing game assets including characters, environments, items, and UI elements through MCP-compatible clients. Supports workflow publishing, request tracing, and diagnostics. Enables AI coding agents in Cursor, Claude Code, and similar environments to generate and iterate on visual game assets as part of development workflows without switching to a separate design tool.", "category": "media", "endpoint": "scenario-mcp", "homepage_url": "https://www.scenario.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-06", "updated": "2026-06-06", "tags": [ "game-development", "art-generation", "creative", "design", "assets", "ai-art", "gaming" ], "use_cases": [ "Generate game art assets including characters, environments, and items directly from AI coding agents without leaving the development environment", "Integrate visual asset generation into game development workflows through MCP-compatible tools like Cursor and Claude Code", "Iterate on game art styles and asset variants through natural language prompts connected to Scenario's generative AI pipeline" ], "health": "active" }, { "id": "similarweb-mcp", "name": "Similarweb MCP Server", "description": "MCP server from Similarweb that powers AI workflows with comprehensive digital intelligence data. Integrates Website Intelligence including traffic analytics, audience demographics, engagement metrics, referral sources, and competitive benchmarks into AI tools such as Claude Desktop, Cursor, and Microsoft Copilot. Enables AI agents to ground outputs in reliable digital data for market research, competitive analysis, and business intelligence workflows. Part of Similarweb's expanded AI ecosystem launched alongside Perplexity integration.", "category": "data", "endpoint": "similarweb-mcp", "homepage_url": "https://developers.similarweb.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "web-analytics", "competitive-intelligence", "traffic", "market-research", "digital-data", "benchmarks" ], "use_cases": [ "Query website traffic data, audience demographics, and engagement metrics through AI assistants for real-time competitive analysis", "Ground AI agent outputs in reliable Similarweb digital intelligence data for market research and business strategy workflows", "Analyze referral sources, competitive benchmarks, and industry trends through natural language queries in MCP-connected AI tools" ], "health": "active" }, { "id": "kaltura-mcp", "name": "Kaltura AI Agent Skills", "description": "Open-source suite of production-validated AI agent skills from Kaltura that enable any AI coding agent to build intelligent rich media applications. Provides MCP-compatible modules for Claude Code and GitHub Copilot to create secure, compliant video and media experiences including avatar-guided portals, interactive video players, live streaming integrations, and content management workflows. Released May 2026 as open source, allowing AI agents to generate full-stack media applications on the Kaltura platform in minutes rather than weeks.", "category": "media", "endpoint": "kaltura-mcp", "homepage_url": "https://corp.kaltura.com", "github_url": "https://github.com/kaltura/kaltura-agent-skills", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "media", "video", "streaming", "rich-media", "open-source", "content-management", "developer-tools" ], "use_cases": [ "Build secure rich media applications including video players and avatar portals through AI coding agents using Kaltura's production-validated skills", "Generate full-stack media experiences on the Kaltura platform in minutes by connecting AI coding assistants to Kaltura's open-source agent skills", "Integrate live streaming, content management, and interactive video capabilities into development workflows through MCP-compatible AI tools" ], "health": "active" }, { "id": "outreach-mcp", "name": "Outreach MCP Server", "description": "MCP server from Outreach that brings revenue orchestration data directly into AI assistants and development environments. First revenue platform to offer native MCP integration with ChatGPT and Codex. Enables AI agents to access live pipeline data, deal health signals, account insights, meeting summaries, and forecast metrics. Sales, RevOps, and customer success teams can query trusted business context, generate collateral, and complete advanced sales tasks without switching platforms. Part of Outreach's full MCP Suite announced June 2026.", "category": "data", "endpoint": "outreach-mcp", "homepage_url": "https://www.outreach.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "sales", "revenue", "pipeline", "deals", "forecasting", "crm", "enterprise", "chatgpt" ], "use_cases": [ "Access live pipeline data, deal health, and forecast metrics through AI assistants like ChatGPT and Claude without switching to the Outreach platform", "Build custom agentic revenue workflows in Codex using trusted Outreach business context through the MCP server", "Enable sellers to generate collateral, query account insights, and complete sales tasks using natural language in any MCP-connected AI tool" ], "health": "active" }, { "id": "netfoundry-mcp-gateway", "name": "NetFoundry MCP Gateway", "description": "Enterprise zero-trust MCP gateway from NetFoundry that provides secure access to MCP servers without exposing them to the network. Built on Identity-First Reachability with no open inbound ports, no VPNs, and no firewall changes. Supports multi-backend aggregation, tool namespacing, structural permission filtering, per-client session isolation, centralized multi-user management, and role-based access control. Denied tools are removed from the registry entirely rather than checked at runtime. Paired with an LLM Gateway supporting semantic routing across OpenAI, Anthropic, Azure, Bedrock, Vertex AI, and Ollama with built-in PII detection and prompt injection filtering.", "category": "infrastructure", "endpoint": "netfoundry-mcp-gateway", "homepage_url": "https://netfoundry.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "zero-trust", "security", "gateway", "infrastructure", "enterprise", "identity", "networking", "governance" ], "use_cases": [ "Secure MCP server deployments behind zero-trust gateways that eliminate network exposure with no open inbound ports or VPN requirements", "Enforce role-based access control and structural permission filtering on MCP tool registries across enterprise AI agent deployments", "Route LLM requests across multiple providers with semantic classification for cost optimization, data sensitivity, and latency while maintaining full audit trails" ], "health": "active" }, { "id": "moengage-mcp", "name": "MoEngage MCP Server", "description": "MCP server from MoEngage that opens the customer engagement platform to the enterprise AI stack. Part of the Merlin AI Custom Agents launch in June 2026. Enables AI tools like Claude and ChatGPT to access MoEngage data and tools for marketing automation, campaign management, customer segmentation, and engagement analytics. Provides marketer-defined guardrails and full visibility into agent actions. Designed for enterprise marketing teams building custom AI agent workflows that interact with customer engagement data.", "category": "communication", "endpoint": "moengage-mcp", "homepage_url": "https://www.moengage.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "marketing", "engagement", "campaigns", "segmentation", "analytics", "automation", "enterprise" ], "use_cases": [ "Query customer engagement data and campaign performance metrics through AI assistants connected to MoEngage via MCP", "Build custom marketing AI agents with marketer-defined guardrails that can segment audiences and trigger campaigns through natural language", "Access MoEngage customer insights, behavioral analytics, and engagement tools from Claude or ChatGPT for cross-channel marketing orchestration" ], "health": "active" }, { "id": "fingerprint-mcp", "name": "Fingerprint MCP Server", "description": "Open-source MCP server from Fingerprint that connects AI agents to device intelligence and fraud prevention data. The first MCP server in the fraud prevention industry. Enables fraud teams to investigate suspicious activity, analyze device fingerprints, query visitor identification events, and assess bot detection signals through AI assistants. Supports Claude Desktop, Cursor, and other MCP-compatible clients. Provides programmatic access to Fingerprint's device intelligence APIs for real-time fraud investigation workflows.", "category": "identity", "endpoint": "fingerprint-mcp", "homepage_url": "https://fingerprint.com", "github_url": "https://github.com/fingerprintjs/fingerprint-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @anthropic-ai/create-mcp @fingerprintjs/fingerprint-mcp-server", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "fraud-prevention", "device-intelligence", "bot-detection", "security", "fingerprinting", "open-source", "identity" ], "use_cases": [ "Investigate suspicious visitor activity and device fingerprints through AI assistants using natural language queries against Fingerprint data", "Detect and analyze bot traffic patterns and automation signals by connecting fraud prevention tools to AI agents via MCP", "Build real-time fraud investigation workflows where AI agents query device intelligence, visitor history, and identification events from Fingerprint" ], "health": "active" }, { "id": "cycode-mcp", "name": "Cycode MCP Server", "description": "Application security MCP server from Cycode that helps secure AI-generated code in real time. Integrates with AI coding assistants to provide security scanning, vulnerability detection, and code governance as part of the development workflow. Connects to source control and pipeline tools including GitHub, GitLab, Bitbucket, and any IDE supporting MCP. Enables security teams to enforce policies inside AI coding assistants and detect issues before code reaches production.", "category": "code", "endpoint": "cycode-mcp", "homepage_url": "https://cycode.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-07", "updated": "2026-06-07", "tags": [ "appsec", "code-security", "vulnerability-detection", "sast", "devsecops", "ai-code", "governance" ], "use_cases": [ "Scan AI-generated code for security vulnerabilities in real time through MCP-connected coding assistants like Cursor and VS Code", "Enforce application security policies inside AI coding workflows to catch issues before they reach source control or production", "Integrate Cycode vulnerability detection and code governance into agentic development pipelines through standardized MCP interfaces" ], "health": "active" }, { "id": "robinhood-trading-mcp", "name": "Robinhood Trading MCP Server", "description": "MCP server from Robinhood that enables AI agents to execute trades on the Robinhood platform. Launched May 2026 as part of Robinhood's Agentic Trading product. Agents connect via MCP to place equity trades, monitor positions, and execute strategies in a dedicated agentic trading account with built-in safety controls including spending limits, real-time activity feeds, push notifications, and instant disconnect. Supports equities with options, crypto, and futures planned. Designed with a safety-always approach including fraud detection, manual approval options, and trade preview capabilities.", "category": "payments", "endpoint": "robinhood-trading-mcp", "homepage_url": "https://robinhood.com/us/en/agentic-trading", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "trading", "finance", "stocks", "equities", "agentic-trading", "investing", "brokerage" ], "use_cases": [ "Connect AI agents to Robinhood to execute automated trading strategies in a dedicated agentic account with built-in safety controls and real-time monitoring", "Build autonomous portfolio rebalancing agents that analyze concentration risk and sector exposure then execute trades through Robinhood's MCP server", "Deploy backtested trading strategies like mean reversion through AI agents that automatically buy oversold stocks and sell on reversion via the Robinhood platform" ], "health": "active" }, { "id": "robinhood-banking-mcp", "name": "Robinhood Banking MCP Server", "description": "MCP server from Robinhood that enables AI agents to make credit card purchases through the Robinhood Gold Card. Part of the Agentic Credit Card product launched May 2026. Agents connect via MCP to a dedicated virtual card with user-controlled spending limits, optional manual approval for every purchase, and instant card deletion. Designed for autonomous shopping, price monitoring, and purchase automation while maintaining full user oversight through the Robinhood Banking app.", "category": "payments", "endpoint": "robinhood-banking-mcp", "homepage_url": "https://robinhood.com/us/en/support/articles/agentic-credit-card", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "payments", "credit-card", "banking", "finance", "shopping", "autonomous-spending", "agentic-finance" ], "use_cases": [ "Enable AI agents to make purchases on your behalf through a dedicated virtual Robinhood Gold Card with user-controlled spending limits and optional manual approvals", "Build price-monitoring agents that track product availability and automatically purchase items when they drop below a target price using the Robinhood Banking MCP", "Automate shopping workflows where AI agents research, compare prices, and complete purchases across merchants while earning 3% cash back on the Robinhood Gold Card" ], "health": "active" }, { "id": "kyanite-mcp-video", "name": "Kyanite mcp-video", "description": "Free open-source MCP server from Kyanite Labs that gives AI agents a real video-editing surface. Provides 85+ tools for programmatic video editing with FFmpeg and new content creation with Hyperframes. Includes guardrails for safe autonomous operation, planning tools for multi-step edits, and support for trimming, concatenating, overlaying, adding audio, applying filters, and generating video from templates. Works with Claude Desktop, Cursor, and other MCP-compatible clients. Python library and CLI also included.", "category": "media", "endpoint": "kyanite-mcp-video", "homepage_url": "https://mcpmarket.com/server/video-1", "github_url": "https://github.com/KyaniteLabs/mcp-video", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "video-editing", "ffmpeg", "media", "open-source", "content-creation", "developer-tools", "guardrails" ], "use_cases": [ "Give AI coding agents full video editing capabilities including trim, concat, overlay, audio mixing, and filter application through a guardrailed MCP interface", "Build automated video production pipelines where AI agents plan multi-step edits, execute FFmpeg operations, and generate new content from Hyperframes templates", "Enable AI assistants in Claude Desktop or Cursor to programmatically create and edit video content with 85+ tools while maintaining safe autonomous operation through built-in guardrails" ], "health": "active" }, { "id": "twelvelabs-mcp", "name": "TwelveLabs MCP Server", "description": "MCP server from Twelve Labs that brings video intelligence capabilities to AI assistants. Enables semantic video search, automatic summarization, Q&A over video content, and embedding generation through a standardized MCP interface. Agents can index videos, find specific scenes using natural language, generate concise summaries, and build RAG workflows that chain search and analysis. Powered by the Marengo embeddings model and Pegasus video language model. Compatible with Claude Desktop, Cursor, Windsurf, Goose, and other MCP clients.", "category": "media", "endpoint": "twelvelabs-mcp", "homepage_url": "https://www.twelvelabs.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "video-intelligence", "video-search", "summarization", "embeddings", "multimodal", "rag", "media" ], "use_cases": [ "Search through hours of video footage using natural language queries to find specific moments, scenes, or visual content via AI assistants connected to TwelveLabs", "Generate automatic video summaries and answer questions about video content through AI assistants using TwelveLabs Pegasus video language model via MCP", "Build retrieval-augmented generation workflows where AI agents first search for relevant video clips then analyze and synthesize findings into reports using chained TwelveLabs MCP tools" ], "health": "active" }, { "id": "pika-mcp", "name": "Pika MCP Server", "description": "MCP server from Pika that gives AI agents access to multi-model creative content generation capabilities. Connects to Claude Code, Codex, and other MCP-compatible agents to provide tools for text-to-video, image-to-video, video editing, image generation, lip sync, voice cloning, music generation, auto captions, and more. Aggregates models including Seedance, Gemini Image, ChatGPT Images, Pika Video, Kling, MiniMax, Veo 3, Sora, ElevenLabs, and Remotion. Includes ready-to-run creative skills for app launch videos, explainers, UGC ads, podcasts, and brand kits. OAuth authentication via the Pika platform.", "category": "media", "endpoint": "pika-mcp", "homepage_url": "https://pika.me/mcp", "github_url": "https://github.com/Pika-Labs/Pika-Skills", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "video-generation", "image-generation", "creative", "content-creation", "multi-model", "media", "ai-video" ], "use_cases": [ "Generate launch videos, explainer content, UGC ads, and branded media assets directly from AI coding agents like Claude Code using Pika's multi-model creative toolkit via MCP", "Create and edit videos, images, music, and voiceovers through natural language prompts in MCP-compatible AI assistants with access to models like Seedance, Veo 3, and Sora", "Build end-to-end creative production workflows where AI agents handle brand kit generation, app store screenshots, podcast creation, and social content using Pika's ready-to-run skills" ], "health": "active" }, { "id": "new-relic-mcp", "name": "New Relic AI MCP Server", "description": "MCP server from New Relic that provides standardized access to observability data for AI agents and assistants. Integrates New Relic telemetry including application performance monitoring, infrastructure metrics, logs, distributed traces, error tracking, and alerting data into MCP-compatible AI tools. Enables AI agents to query production health, investigate incidents, analyze performance trends, and correlate signals across the full stack without manual dashboard navigation. Available in public preview for Claude Desktop, Cursor, and other MCP clients.", "category": "infrastructure", "endpoint": "new-relic-mcp", "homepage_url": "https://newrelic.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "observability", "monitoring", "apm", "infrastructure", "logs", "traces", "devops", "incident-response" ], "use_cases": [ "Query production application health, error rates, and performance metrics through AI assistants connected to New Relic observability data via MCP", "Enable AI agents to investigate production incidents by correlating distributed traces, logs, and infrastructure metrics from New Relic without manual dashboard navigation", "Build autonomous monitoring workflows where AI agents analyze performance trends, detect anomalies, and surface actionable insights from New Relic telemetry data" ], "health": "active" }, { "id": "transcend-mcp", "name": "Transcend MCP Server", "description": "MCP server from Transcend that brings privacy and data governance capabilities to AI assistants. Part of the Agentic Assist product launched March 2026. Enables privacy teams to automate compliance workflows including data subject request processing, data mapping, consent management, and regulatory reporting through AI agents. Reduces days of manual compliance work to minutes of guided interaction. Available to customers who opt in through the Transcend platform.", "category": "data", "endpoint": "transcend-mcp", "homepage_url": "https://transcend.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "privacy", "compliance", "data-governance", "gdpr", "dsr", "consent-management", "enterprise" ], "use_cases": [ "Automate data subject request processing and privacy compliance workflows through AI assistants connected to Transcend's governance platform via MCP", "Enable privacy teams to query data maps, manage consent records, and generate regulatory reports using natural language in MCP-compatible AI tools", "Reduce days of manual compliance work to minutes by connecting AI agents to Transcend's privacy automation capabilities for GDPR, CCPA, and other regulatory frameworks" ], "health": "active" }, { "id": "kajeet-sentinel-mcp", "name": "Kajeet Sentinel MCP Server", "description": "MCP server from Kajeet that connects AI agents to the SentinelOS IoT device management platform. Launched June 2026 as part of the SentinelOS AI agent-ready operating layer. Enables approved AI agents and assistants to query device status, connectivity health, policy data, and network diagnostics under governed access with authentication and role-based permissions. Part of a broader platform including the Sentinel CLI, REST APIs, and webhooks for managing connected device fleets across enterprise and education deployments.", "category": "infrastructure", "endpoint": "kajeet-sentinel-mcp", "homepage_url": "https://www.kajeet.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-08", "updated": "2026-06-08", "tags": [ "iot", "device-management", "connectivity", "enterprise", "education", "networking", "fleet-management" ], "use_cases": [ "Query IoT device status, connectivity health, and policy compliance across enterprise device fleets through AI assistants connected to Kajeet Sentinel via MCP", "Enable AI agents to monitor and diagnose network connectivity issues across managed device deployments using governed access to Sentinel platform data", "Build automated device fleet management workflows where AI agents check device health, analyze connectivity patterns, and surface policy violations through the Kajeet Sentinel MCP server" ], "health": "active" }, { "id": "bumper-mcp", "name": "Bumper MCP Server", "description": "MCP server from Bumper that gives AI agents access to podcast analytics and performance data. Enterprise subscribers can query playback metrics, verified audience counts, listen hours, downloads, followers, and episode-level breakdowns through natural language in any MCP-compatible assistant. Includes access to Bumper Score benchmarks that compare show performance against the broader podcast market using verified consumption data from over 3 billion tracked hours. Launched June 8, 2026 as part of the restructured Bumper Dashboard pricing.", "category": "data", "endpoint": "bumper-mcp", "homepage_url": "https://wearebumper.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "podcast", "analytics", "media", "audio", "audience-measurement", "benchmarking", "enterprise" ], "use_cases": [ "Query podcast performance data including playback, verified audience, listen hours, and downloads through AI assistants connected to Bumper's analytics platform via MCP", "Compare podcast show performance against category benchmarks using the Bumper Score directly from Claude, ChatGPT, or other MCP-compatible tools", "Enable media companies managing multiple podcasts to get instant answers about show portfolios without navigating dashboards or exporting CSV reports" ], "health": "active" }, { "id": "alpaca-mcp", "name": "Alpaca MCP Server", "description": "Official MCP server from Alpaca Markets that enables AI agents to trade stocks, ETFs, crypto, and options, run data analysis, and build strategies in plain English directly from AI assistants and coding tools. Supports account management, order placement, position monitoring, market data retrieval, and strategy backtesting through a standardized MCP interface. Works with Claude Desktop, Cursor, and other MCP-compatible clients. Open source with 800+ GitHub stars.", "category": "payments", "endpoint": "alpaca-mcp", "homepage_url": "https://alpaca.markets", "github_url": "https://github.com/alpacahq/alpaca-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "trading", "finance", "stocks", "crypto", "options", "etf", "brokerage", "open-source" ], "use_cases": [ "Execute trades for stocks, ETFs, crypto, and options through AI assistants connected to Alpaca's brokerage platform via MCP", "Build and backtest trading strategies using natural language in Claude Code or Cursor with direct access to Alpaca market data and order execution", "Monitor portfolio positions, account balances, and market data in real-time through MCP-compatible AI tools without switching to a separate trading interface" ], "health": "active" }, { "id": "front-mcp", "name": "Front MCP Server", "description": "MCP server from Front that provides AI agents with access to customer communication data and workflows within the Front platform. Currently in beta. Allows external AI agents and MCP-compatible tools to access Front context for running complex communication workflows, managing conversations, and coordinating across shared inboxes. Part of Front's broader initiative to bring external AI agents into workspaces as governed teammates with built-in access controls.", "category": "communication", "endpoint": "front-mcp", "homepage_url": "https://front.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "customer-communication", "inbox", "collaboration", "enterprise", "support", "beta", "governance" ], "use_cases": [ "Give AI agents access to Front customer communication context for running complex multi-step workflows across shared inboxes via MCP", "Enable AI assistants to read and triage customer messages, surface conversation history, and coordinate communication workflows within Front workspaces", "Bring external AI agents into Front as governed teammates with role-based access controls and built-in governance for customer-facing communication" ], "health": "active" }, { "id": "domotz-mcp", "name": "Domotz MCP Server", "description": "MCP server from Domotz that connects AI assistants to the Domotz IT network management and monitoring platform. Launched June 2026. Enables AI agents to check device quotas and allowances, query historical metrics with trend analysis, and monitor network device inventory directly through MCP-compatible tools. Designed for MSPs and IT teams managing distributed network infrastructure who want to query device and network health through natural language.", "category": "infrastructure", "endpoint": "domotz-mcp", "homepage_url": "https://www.domotz.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "network-monitoring", "it-management", "msp", "device-management", "infrastructure", "trend-analysis" ], "use_cases": [ "Check device quotas, allowances, and network health across managed infrastructure through AI assistants connected to Domotz via MCP", "Query historical network metrics and trend analysis data from Domotz directly in MCP-compatible AI tools without switching to the monitoring dashboard", "Enable MSPs and IT teams to monitor distributed network device inventory and troubleshoot connectivity issues using natural language prompts through MCP" ], "health": "active" }, { "id": "comfyui-mcp", "name": "ComfyUI MCP Server", "description": "Open-source MCP server and Claude Code plugin for ComfyUI that enables AI agents to execute image generation workflows, visualize pipelines, manage models, control VRAM, and explore the ComfyUI node ecosystem. Provides tools for running ComfyUI workflows programmatically, generating images from prompts, managing checkpoint and LoRA models, and monitoring GPU resource usage. Designed for AI-assisted creative workflows where coding agents can orchestrate ComfyUI pipelines directly.", "category": "media", "endpoint": "comfyui-mcp", "homepage_url": "https://github.com/artokun/comfyui-mcp", "github_url": "https://github.com/artokun/comfyui-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "image-generation", "comfyui", "creative", "open-source", "stable-diffusion", "workflows", "gpu", "ai-art" ], "use_cases": [ "Execute ComfyUI image generation workflows directly from Claude Code or other MCP-compatible AI agents without manually operating the ComfyUI interface", "Manage ComfyUI models, checkpoints, and LoRA files while monitoring VRAM usage through AI assistants connected via MCP", "Build automated creative pipelines where AI coding agents design, execute, and iterate on ComfyUI workflows for image generation and manipulation" ], "health": "active" }, { "id": "trvl-mcp", "name": "trvl AI Travel Agent", "description": "Open-source MCP server and Claude Code skill that turns AI assistants into full-featured travel agents. Installs as a binary with MCP server wiring and skill integration, building a personalized travel profile on setup. Provides tools for flight search, hotel booking, itinerary planning, and travel preference management. Designed for use with Claude Code and other MCP-compatible AI tools where the agent handles end-to-end travel planning through natural language conversation.", "category": "productivity", "endpoint": "trvl-mcp", "homepage_url": "https://github.com/MikkoParkkola/trvl", "github_url": "https://github.com/MikkoParkkola/trvl", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "travel", "booking", "flights", "hotels", "itinerary", "open-source", "ai-agent" ], "use_cases": [ "Plan complete trips including flights, hotels, and itineraries through natural language conversation with AI assistants connected to trvl via MCP", "Build personalized travel profiles that AI agents reference when searching for flights and accommodations matching your preferences and constraints", "Enable AI coding agents in Claude Code to handle end-to-end travel planning and booking workflows through the trvl MCP skill integration" ], "health": "active" }, { "id": "adobe-journey-optimizer-mcp", "name": "Adobe Journey Optimizer MCP Server", "description": "MCP server from Adobe that surfaces Journey Optimizer campaign and offer data directly inside MCP-compatible AI assistants. Currently in Beta as of June 2026. Provides read-only access to campaign statuses, channel configurations, audience targeting, scheduling, and sandbox information through natural language prompts. Enables marketers, campaign managers, and stakeholders to query the same live orchestration data without navigating the Journey Optimizer UI or writing API calls. Currently supported in Claude Web and Claude Desktop.", "category": "productivity", "endpoint": "adobe-journey-optimizer-mcp", "homepage_url": "https://experienceleague.adobe.com/en/docs/journey-optimizer/using/content-management/combine/ajo-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "marketing", "campaigns", "adobe", "enterprise", "customer-experience", "content-management", "beta" ], "use_cases": [ "Query campaign statuses, audience targeting, and channel configurations across Adobe Journey Optimizer sandboxes using natural language in Claude Desktop or Claude Web", "Audit your campaign portfolio by asking AI assistants to surface stopped campaigns, orphaned drafts, and configuration issues without navigating the Journey Optimizer UI", "Enable cross-functional teams to collaborate around live campaign data by querying Adobe Journey Optimizer orchestration details through MCP-compatible AI tools" ], "health": "active" }, { "id": "matlab-mcp", "name": "MATLAB MCP Server", "description": "Official MCP server from MathWorks that enables AI assistants and coding tools to run MATLAB code and interact with the MATLAB computational environment through the Model Context Protocol. Provides tools for executing MATLAB scripts, accessing MATLAB functions, and working with MATLAB data directly from MCP-compatible AI applications. Designed to bring MATLAB's numerical computing, data analysis, and engineering simulation capabilities into AI-assisted development workflows.", "category": "code", "endpoint": "matlab-mcp", "homepage_url": "https://www.mathworks.com", "github_url": "https://github.com/matlab/matlab-mcp-core-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-09", "updated": "2026-06-09", "tags": [ "matlab", "mathworks", "numerical-computing", "engineering", "data-analysis", "simulation", "developer-tools" ], "use_cases": [ "Run MATLAB scripts and functions directly from AI assistants like Claude Code or Cursor through the official MathWorks MCP server", "Access MATLAB's numerical computing and data analysis capabilities from AI-assisted development workflows without switching between tools", "Enable AI agents to orchestrate MATLAB simulations, process engineering data, and generate visualizations through standardized MCP tool calls" ], "health": "active" }, { "id": "clootrack-mcp", "name": "Clootrack MCP Server", "description": "MCP server from Clootrack that connects AI assistants to enterprise Voice of the Customer intelligence through a governed interface. Exposes a rich context layer spanning VoC analytics, churn prediction, price elasticity, sales effectiveness, competitor intelligence, campaign effectiveness, and demand forecasting. Teams can generate reports, create tickets, trigger alerts, and automate workflows grounded in validated customer data directly from Claude, ChatGPT, Microsoft Copilot, or Gemini. Role-based access controls enforce data authorization, PII is anonymized at ingestion, and customer data is never used to train AI models. Launched June 9, 2026.", "category": "data", "endpoint": "clootrack-mcp", "homepage_url": "https://www.clootrack.com/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "customer-intelligence", "voice-of-customer", "analytics", "enterprise", "churn-prediction", "competitor-intelligence", "gdpr" ], "use_cases": [ "Query Voice of the Customer analytics including churn prediction, price elasticity, and competitor intelligence through AI assistants connected to Clootrack via MCP", "Generate boardroom-ready customer intelligence reports and trigger alerts directly from Claude, ChatGPT, or Microsoft Copilot without building custom connectors", "Automate customer insight workflows with governed, AI-ready data that enforces role-based access controls and PII anonymization across enterprise teams" ], "health": "active" }, { "id": "capital-com-mcp", "name": "Capital.com MCP Server", "description": "MCP server plugin from Capital.com that enables AI agents to access live market data, sentiment analysis, and trade execution for CFD trading on the Capital.com platform. Initially available for MENA region clients through a CMA-regulated platform. Provides market research, position monitoring, and order placement through MCP-compatible tools like Claude Desktop and Cursor. Includes a mandatory two-step confirmation process for trade execution to maintain human oversight. Launched June 8, 2026.", "category": "payments", "endpoint": "capital-com-mcp", "homepage_url": "https://capital.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "trading", "cfd", "finance", "market-data", "sentiment-analysis", "regulated", "mena" ], "use_cases": [ "Access live market data and sentiment analysis for CFD trading through AI assistants connected to Capital.com's regulated MENA platform via MCP", "Execute trades with mandatory two-step human confirmation through Claude Desktop or Cursor without switching between research and trading interfaces", "Streamline the path from market research to trading decisions by combining live data, sentiment, and execution in a single MCP-connected AI workflow" ], "health": "active" }, { "id": "nexla-mcp-studio", "name": "Nexla MCP Studio", "description": "Platform from Nexla that enables enterprise teams to build governed, task-specific MCP servers through conversation without writing integration code. Connects to 600+ enterprise systems and 10,000+ available tools and actions spanning Salesforce, Snowflake, SAP, NetSuite, Workday, Databricks, ServiceNow, and more. Users describe a business outcome, provide system access, and Nexla autonomously discovers data and permissions, selects minimum required tools, assembles cross-system context, and generates a production-ready MCP server. Servers inherit access controls, credential management, audit logging, and data lineage. Currently in Early Access. Announced June 9, 2026.", "category": "infrastructure", "endpoint": "nexla-mcp-studio", "homepage_url": "https://nexla.com/mcp-studio", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "enterprise", "integration", "governance", "no-code", "data-platform", "multi-system", "early-access" ], "use_cases": [ "Build governed MCP servers spanning multiple enterprise systems like Salesforce, Snowflake, and ServiceNow through natural language conversation without writing integration code", "Create task-specific MCP servers that assemble only the minimum tools and context needed for a business outcome instead of exposing entire application APIs", "Deploy production-ready MCP servers with built-in access controls, audit logging, and data lineage across 600+ enterprise system connectors" ], "health": "active" }, { "id": "logrocket-mcp", "name": "LogRocket MCP Server", "description": "MCP server from LogRocket that gives AI agents visibility into real user experience data through the Galileo AI engine. Connects AI assistants and coding agents to session replays, customer feedback from Zoom and Gong, support tickets from Zendesk and Intercom, and project management data from GitHub, Linear, and Jira. Galileo watches user sessions, detects issues, diagnoses root causes, quantifies user impact, and suggests fixes that can be pushed directly to Claude Code or Cursor. Used by Rippling and ShipStation Global for automated issue resolution. Hosted at mcp.logrocket.com/mcp. Launched June 9, 2026.", "category": "code", "endpoint": "logrocket-mcp", "homepage_url": "https://logrocket.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "session-replay", "analytics", "debugging", "user-experience", "issue-detection", "product-analytics", "ai-diagnostics" ], "use_cases": [ "Give coding agents in Claude Code or Cursor access to real user session data so they can diagnose UX issues and generate pull requests with fixes automatically", "Build issue resolution agents that watch user sessions, surface usability and technical problems, and route them to coding agents for automated repair", "Enable product research agents to identify new features being shipped, analyze how customers respond, and surface insights without manual session replay review" ], "health": "active" }, { "id": "work-self-maya-mcp", "name": "WORK-SELF Maya Human Context MCP Server", "description": "Enterprise MCP server from WORK-SELF that provides AI agents with governed, permissioned employee-specific human context for agent-human orchestration. Returns Context Capsules and Work Contracts containing task, role, organizational, cultural, transition-readiness, and work-preference context. Features include Autonomy Dials for workflow operating modes, Digital Andon stop-or-escalate signals, and Review Maps that tell employees what to read, skim, decide, or delegate. Built on a proprietary identity graph with 80,000+ profiles and 2.2 billion scenario permutations. Backed by a 17-claim US AI patent. Announced June 9, 2026.", "category": "productivity", "endpoint": "work-self-maya-mcp", "homepage_url": "https://www.work-self.com/product", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "human-context", "enterprise", "workforce", "orchestration", "governance", "identity", "hr-tech" ], "use_cases": [ "Give enterprise AI agents governed human context about employees including work preferences, decision authority, and escalation rules before initiating tasks or handoffs", "Define agent-human Work Contracts that specify which decisions stay human-owned, which tasks are agent-owned, and how autonomy levels shift across workflows", "Enable workforce transformation programs to assess transition readiness and deploy AI agents that adapt their behavior to individual employee roles and work styles" ], "health": "active" }, { "id": "tealium-context-api-mcp", "name": "Tealium Context API MCP Server", "description": "Managed MCP server from Tealium that gives AI agents real-time access to customer context from the Tealium customer data orchestration platform. Combines live behavioral CDP profiles with warehouse data to deliver customer context in milliseconds. Surfaces recent orders, intent signals, loyalty status, audience memberships, and consent data for agentic workflows, service center assist, and next-best-action decisioning. Works with any MCP-compatible agent framework including Claude, ChatGPT, and Gemini. Part of the Tealium Context API expansion of Moments API. Launched June 9, 2026.", "category": "data", "endpoint": "tealium-context-api-mcp", "homepage_url": "https://tealium.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "customer-data", "cdp", "real-time", "personalization", "enterprise", "data-cloud", "marketing" ], "use_cases": [ "Give AI agents instant access to unified customer profiles combining real-time behavioral data and historical warehouse data through Tealium's managed MCP server", "Power service and contact center AI agents with customer context including recent orders, loyalty status, and intent signals in a single low-latency call", "Enable next-best-action decisioning engines to combine current profile state with warehouse-backed audiences and model scores through MCP-connected AI workflows" ], "health": "active" }, { "id": "reportportal-mcp", "name": "ReportPortal MCP Server", "description": "Open-source MCP server that bridges ReportPortal test reporting instances with AI assistants. Provides tools to analyze test execution results, query launch histories, investigate failure patterns, and access test automation analytics directly from Claude Desktop, GitHub Copilot, Cursor, and other MCP-compatible clients. Enables QA teams to ask natural language questions about test health, flaky tests, failure trends, and execution metrics without navigating the ReportPortal dashboard. Built in TypeScript with stdio transport.", "category": "code", "endpoint": "reportportal-mcp", "homepage_url": "https://reportportal.io", "github_url": "https://github.com/reportportal/reportportal-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "testing", "qa", "test-automation", "reporting", "analytics", "open-source", "ci-cd" ], "use_cases": [ "Query test execution results, failure patterns, and flaky test trends through AI assistants connected to ReportPortal via MCP without navigating dashboards", "Enable QA engineers to ask natural language questions about test health and automation metrics directly from Claude Desktop or GitHub Copilot", "Integrate test reporting data into AI-assisted development workflows so coding agents can understand test failures and their history when debugging issues" ], "health": "active" }, { "id": "alphafold-sovereign-mcp", "name": "AlphaFold Sovereign MCP Server", "description": "Open-source MCP server that composes AlphaFold DB and eight public biomedical data sources into a local SQLite knowledge graph accessible through MCP tool calls. Enables AI assistants to query protein structure predictions, cross-reference biomedical datasets, and explore molecular biology data through natural language. Designed for researchers and bioinformaticians who want to combine AlphaFold structural data with related biomedical knowledge without building custom data pipelines.", "category": "data", "endpoint": "alphafold-sovereign-mcp", "homepage_url": "https://github.com/smaniches/alphafold-sovereign", "github_url": "https://github.com/smaniches/alphafold-sovereign", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "biomedical", "protein-structure", "alphafold", "research", "knowledge-graph", "sqlite", "open-source" ], "use_cases": [ "Query AlphaFold protein structure predictions and cross-reference them against eight biomedical data sources through AI assistants via MCP", "Build a local biomedical knowledge graph from AlphaFold DB and public datasets that AI coding agents can query for molecular biology research", "Enable bioinformaticians to explore protein structure data and related biomedical knowledge through natural language without writing custom database queries" ], "health": "active" }, { "id": "shotgrid-mcp", "name": "ShotGrid MCP Server", "description": "Open-source MCP server that gives AI assistants live, accurate knowledge of Autodesk ShotGrid instances for reliable VFX and animation pipeline code generation. Provides tools to inspect ShotGrid project data, query entity schemas, access shot and asset information, and understand pipeline configurations. Designed for technical directors and pipeline engineers who want AI agents to generate correct ShotGrid integration code based on the actual state of their production database.", "category": "media", "endpoint": "shotgrid-mcp", "homepage_url": "https://github.com/rfletchr/shotgrid-mcp", "github_url": "https://github.com/rfletchr/shotgrid-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-10", "updated": "2026-06-10", "tags": [ "vfx", "animation", "shotgrid", "autodesk", "pipeline", "production", "open-source" ], "use_cases": [ "Generate accurate ShotGrid pipeline integration code by giving AI agents live access to production database schemas, entities, and configurations via MCP", "Query shot statuses, asset information, and project data from ShotGrid directly in AI coding tools without switching to the ShotGrid web interface", "Enable technical directors to use AI assistants for pipeline automation tasks grounded in the actual state of their ShotGrid production instance" ], "health": "active" }, { "id": "treppy-mcp", "name": "Treppy MCP Server", "description": "MCP server from VisitorsCoverage that provides a standardized bridge to the travel insurance market for AI assistants embedded in booking copilots and concierge platforms. Instead of building individual carrier integrations, developers plug into a single high-performance endpoint that delivers a full quote-to-compare flow with real-time quotes from multiple carriers and accurate plan information for hundreds of plans. AI concierges can quote travel insurance the same way they suggest restaurants and excursions, turning a recommendation into a one-tap purchase. Works with any MCP-capable agent including Claude, ChatGPT, Cursor, Cline, and custom agent stacks. Free during public beta at treppy.io. Launched June 9, 2026.", "category": "payments", "endpoint": "treppy-mcp", "homepage_url": "https://www.treppy.io/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "travel-insurance", "insurance", "insurtech", "travel", "embedded-finance", "quoting", "multi-carrier" ], "use_cases": [ "Enable AI travel concierges and booking copilots to quote and compare travel insurance from multiple carriers in real time through a single MCP endpoint", "Embed travel insurance as a seamless automated step in AI-led trip planning workflows instead of redirecting users to separate insurance comparison sites", "Build AI agents that recommend and sell travel insurance alongside flights and hotels without writing individual carrier integrations" ], "health": "active" }, { "id": "croft-mcp", "name": "Croft H-2A MCP Server", "description": "MCP connector from Croft, the most-used H-2A platform in the United States, that brings AI assistants directly into customer accounts for agricultural workforce management. Employers, agents, and recruiters can use ChatGPT, Claude, and any MCP-compatible assistant to query their H-2A operations in natural language, asking questions like which workers still need consulate appointments and getting answers in seconds pulled from their Croft account data. Born out of Purdue University's College of Agriculture, Croft already cuts H-2A admin time by more than 50 percent while increasing compliance. Each account comes preloaded with job orders and a free trial of timekeeping and payroll sync. Launched June 1, 2026.", "category": "productivity", "endpoint": "croft-mcp", "homepage_url": "https://www.withcroft.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "agriculture", "h-2a", "workforce", "compliance", "farming", "labor-management", "hr-tech" ], "use_cases": [ "Query H-2A workforce data through AI assistants to check worker statuses, consulate appointments, and job order details without building reports manually", "Enable agricultural employers and labor agents to manage seasonal worker compliance and payroll through natural language conversations in Claude or ChatGPT", "Reduce H-2A administrative overhead by connecting AI agents to Croft platform data for instant answers about workforce operations and regulatory requirements" ], "health": "active" }, { "id": "thinkmarkets-mcp", "name": "ThinkMarkets ChelseaAI MCP Server", "description": "MCP server from ThinkMarkets called ChelseaAI that allows traders to access the ThinkTrader platform through any MCP-compatible AI assistant for live CFD trading. Provides 26 tools spanning market data, position management, order execution, and account information. Traders can check positions, place orders, analyze market conditions, and manage risk through natural conversation. Supports read-only and full trading permission modes where clients control access level. The AI cannot deposit, withdraw, or transfer funds regardless of permission level. Works with Claude, ChatGPT, Grok, and other MCP-compatible clients. Setup takes under two minutes. Available to ThinkTrader account holders from June 2, 2026.", "category": "payments", "endpoint": "thinkmarkets-mcp", "homepage_url": "https://www.thinkmarkets.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "trading", "cfd", "finance", "market-data", "order-execution", "risk-management", "multi-asset" ], "use_cases": [ "Execute CFD trades and manage positions through natural language conversations in Claude or ChatGPT with configurable read-only or full trading permissions", "Monitor portfolio positions, account balances, and market conditions in real time through AI assistants connected to ThinkTrader via MCP", "Combine market analysis and trade execution in a single AI workflow where agents can research conditions and place orders without switching between tools" ], "health": "active" }, { "id": "eplan-mcp", "name": "EPLAN Automation MCP Server", "description": "Open-source MCP server that enables AI assistants to automate EPLAN Electric P8 and EPLAN EEC Pro 2026 electrical design workflows. Exposes 304 tools including 149 EPLAN actions in two execution modes: direct execution and silent QuietMode execution recommended for production use. The local MCP server drives EPLAN P8 directly while two remote MCP servers hosted on Cloudflare Workers expose indexed EEC Pro documentation via semantic search. Claude can execute EPLAN actions in real time, receive feedback, and consult documentation through natural language commands. Designed for electrical engineers and technical directors automating complex design workflows.", "category": "code", "endpoint": "eplan-mcp", "homepage_url": "https://github.com/covagashi/Eplan_2026_IA_MCP_scripts", "github_url": "https://github.com/covagashi/Eplan_2026_IA_MCP_scripts", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "electrical-engineering", "cad", "eplan", "automation", "industrial", "design", "open-source" ], "use_cases": [ "Automate EPLAN Electric P8 electrical design workflows through AI assistants that can execute 149 EPLAN actions and receive real-time feedback via MCP", "Enable electrical engineers to control EPLAN design operations through natural language commands in Claude instead of navigating complex menu systems manually", "Query EPLAN EEC Pro documentation through semantic search from AI coding tools to generate correct integration code based on indexed technical references" ], "health": "active" }, { "id": "lunar-mcpx", "name": "Lunar MCPX Gateway", "description": "Open-source MCP gateway from Lunar.dev that provides a single governed entry point for all agent-to-tool interactions across an organization. Enforces access control, auditability, and policy across every MCP server with approximately 4ms p99 latency. Features include identity-based governance, OAuth passthrough so each end user authenticates with upstream services under their own credentials, and integration with Cursor, Claude Desktop, Claude Code, VS Code, and any MCP-compatible client. Licensed under MIT for non-production use with an Enterprise tier for hosted deployment, automated risk scoring, and additional governance. Deployed by Fortune 200 enterprises to govern AI adoption across engineering teams.", "category": "infrastructure", "endpoint": "lunar-mcpx", "homepage_url": "https://www.lunar.dev/product/mcp", "github_url": "https://github.com/TheLunarCompany/lunar", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "gateway", "governance", "security", "access-control", "enterprise", "open-source", "audit", "infrastructure" ], "use_cases": [ "Route all MCP traffic through a single governed gateway that enforces identity-based access control and audit logging across every agent-to-tool interaction", "Enable OAuth passthrough so each end user authenticates with upstream MCP servers under their own credentials instead of sharing service-level API keys", "Deploy a production-grade MCP control plane that provides real-time observability and policy enforcement across all MCP servers in an enterprise environment" ], "health": "active" }, { "id": "inconvo-mcp", "name": "Inconvo MCP Platform", "description": "Platform from Inconvo (YC S23) that enables SaaS companies to launch remote authenticated MCP servers for their customers in minutes without building custom infrastructure. Connect an existing database and authentication provider to deploy an AI reporting agent attached to customer data that handles conversation state, schema introspection, agent observability, multi-tenancy, and query safety as managed services. Customers can link the MCP server to ChatGPT and other AI tools to query their SaaS data through natural language. Includes agent traces and logs for out-of-the-box observability and a semantic layer for improving agent performance through context engineering.", "category": "infrastructure", "endpoint": "inconvo-mcp", "homepage_url": "https://inconvo.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "saas", "platform", "multi-tenant", "analytics", "reporting", "no-code", "yc", "observability" ], "use_cases": [ "Launch authenticated MCP servers for SaaS customers in minutes by connecting an existing database and auth provider without building custom MCP infrastructure", "Enable SaaS end users to query their account data through ChatGPT and other AI tools via a managed MCP server with built-in multi-tenancy and query safety", "Ship AI reporting agents to customers with out-of-the-box observability, semantic layers, and context engineering without managing conversation state or schema introspection" ], "health": "active" }, { "id": "toast-pos-mcp", "name": "Toast POS MCP Server", "description": "Open-source MCP server that gives AI agents direct access to the Toast restaurant POS and management platform with over 100 restaurant-focused API tools. Covers the complete order lifecycle with 12 order management tools, plus capabilities for checks, menu management, and labor operations. Automatically handles Toast API token refresh on one-hour expiration cycles. Designed for restaurant operators and developers building AI-powered automation on top of Toast's platform for tasks like querying order histories, managing menus, and analyzing labor data through Claude Desktop, Claude Code, or any MCP-compatible client.", "category": "data", "endpoint": "toast-pos-mcp", "homepage_url": "https://github.com/BusyBee3333/toast-mcp-2026-complete", "github_url": "https://github.com/BusyBee3333/toast-mcp-2026-complete", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "restaurant", "pos", "food-service", "orders", "menu-management", "labor", "open-source", "hospitality" ], "use_cases": [ "Query Toast POS order histories, check statuses, and menu data through AI assistants without navigating the Toast management dashboard", "Build AI-powered restaurant automation workflows that manage orders, update menus, and analyze labor data through natural language via MCP", "Enable restaurant operators to get instant answers about daily operations, sales trends, and workforce scheduling by connecting AI agents to their Toast POS system" ], "health": "active" }, { "id": "whisper-graph-mcp", "name": "WhisperGraph MCP Server", "description": "MCP server from Whisper Security that gives AI agents real-time access to a 45-billion-node graph of internet infrastructure for security research and threat intelligence. WhisperGraph maps 7.39 billion nodes and 39 billion edges across 18 source types including DNS resolution, BGP routing, WHOIS, SSL/TLS certificates, certificate transparency, IP allocation, GeoIP, web hyperlinks, email infrastructure, DNSSEC, and curated threat feeds. Agents can perform multi-hop infrastructure pivots at sub-millisecond latency with explainable risk scoring based on 50-plus indicators. Free tier available for individual practitioners and developers. Connects to Claude, Cursor, and any MCP-compatible client in under two minutes.", "category": "data", "endpoint": "whisper-graph-mcp", "homepage_url": "https://www.whisper.security/", "github_url": "https://github.com/whisper-sec/whisper-graph-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-11", "updated": "2026-06-11", "tags": [ "security", "threat-intelligence", "bgp", "dns", "whois", "infrastructure", "graph-database", "osint" ], "use_cases": [ "Give security AI agents instant access to live internet infrastructure data spanning BGP routing, DNS, WHOIS, and threat feeds for automated threat investigation", "Perform multi-hop infrastructure pivots across 18 source types to trace attacker infrastructure and attribute malicious domains without writing custom API calls", "Build security automation workflows that correlate DNS, certificate transparency, and BGP data with curated threat intelligence through a single MCP connection" ], "health": "active" }, { "id": "unabyss-mcp", "name": "Unabyss Context Layer", "description": "MCP-native self-updating context layer that extracts and structures personal and team context from LinkedIn, Notion, Gmail, Slack, GitHub, and other sources into clean layered files. AI agents pull exactly the right context automatically via MCP with item-level permission controls ensuring blocked context never reaches the model. Scores and extracts only relevant lines with up to 10x fewer tokens. Works with Claude, Cursor, Claude Code, ChatGPT, and any MCP-compatible agent. Launched on Product Hunt in June 2026.", "category": "productivity", "endpoint": "unabyss-mcp", "homepage_url": "https://unabyss.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "context", "personal-ai", "memory", "knowledge-management", "permissions", "multi-source", "productivity" ], "use_cases": [ "Give AI agents structured personal and team context from multiple sources so they understand your work without repeated explanation", "Control exactly what context AI models can access with item-level permission toggles across private, professional, and company-confidential data", "Reduce token usage by up to 10x while improving AI response quality through scored context extraction that returns only relevant information" ], "health": "active" }, { "id": "coveo-mcp", "name": "Coveo Hosted MCP Server", "description": "Hosted MCP server from Coveo that connects the Coveo AI-Relevance Platform to large language models including ChatGPT Enterprise and Claude. AI agents access a unified content index spanning an unlimited number of enterprise data sources without custom integrations or additional infrastructure. Maintains enterprise-grade security and governance with queries counting toward existing consumption-based licensing. Available in the ChatGPT Enterprise Apps and Connectors directory. Generally available as of February 2026.", "category": "data", "endpoint": "coveo-mcp", "homepage_url": "https://www.coveo.com/en/developers/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "enterprise-search", "content-index", "knowledge-base", "relevance", "ai-platform", "chatgpt-enterprise" ], "use_cases": [ "Connect enterprise content from unlimited data sources to ChatGPT Enterprise and Claude through a single hosted MCP server without building custom integrations", "Enable AI agents to search and retrieve enterprise knowledge with Coveo relevance ranking while maintaining existing security and governance controls", "Unify scattered enterprise content into a single AI-accessible index so agents can answer questions across all corporate knowledge sources" ], "health": "active" }, { "id": "yottaa-mcp", "name": "Yottaa eCommerce Performance MCP Server", "description": "MCP server from Yottaa purpose-built for eCommerce performance intelligence. AI agents and IDEs query live production data to diagnose third-party script impact, monitor Core Web Vitals, and detect JavaScript errors. Ranks all third-party vendors by precise millisecond contribution to page load times. Uses machine learning for anomaly detection with trend context, root cause analysis, and severity scoring. Connects performance metrics like LCP and INP directly to conversion rates and revenue for ROI-based decisions. Works with Claude, Cursor, and VS Code Copilot. Launched January 2026.", "category": "data", "endpoint": "yottaa-mcp", "homepage_url": "https://www.yottaa.com/mcp-server-announcement-2026/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "ecommerce", "web-performance", "core-web-vitals", "analytics", "third-party-scripts", "anomaly-detection", "conversion" ], "use_cases": [ "Query live eCommerce site performance data through AI agents to identify which third-party scripts are slowing down checkout and other critical pages", "Detect performance regressions and JavaScript errors automatically with machine learning anomaly detection that provides root cause analysis and severity scoring", "Connect Core Web Vitals metrics directly to conversion rates and revenue through AI agents for data-driven performance optimization decisions" ], "health": "active" }, { "id": "mcp-science", "name": "MCP.science Research Servers", "description": "Open-source collection of Model Context Protocol servers for scientific research from Path Integral Institute. Enables AI agents to interact with scientific data, tools, and resources across domains from quantum physics to molecular biology. Includes specialized servers for NCBI genomic data, molecule visualization and property retrieval, and academic paper search and download from multiple sources. Provides infrastructure for AI-powered scientific discovery with a standardized protocol for connecting LLMs to research tools. Community-driven with guides for building custom science MCP servers.", "category": "data", "endpoint": "mcp-science", "homepage_url": "https://mcp.science/", "github_url": "https://github.com/pathintegral-institute/mcp.science", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "science", "research", "genomics", "chemistry", "academic-papers", "open-source", "biology", "physics" ], "use_cases": [ "Give AI agents access to NCBI genomic datasets for genome, gene, and taxonomy queries through a standardized MCP interface", "Enable AI assistants to visualize molecules and retrieve molecular properties for chemistry research workflows", "Search and download academic papers from multiple sources through AI agents without manually navigating individual databases" ], "health": "active" }, { "id": "squarespace-mcp", "name": "Squarespace MCP Server", "description": "Open-source MCP server that enables AI assistants to interact with Squarespace sites through 67 tools covering all major platform features. Built with TypeScript and the official MCP SDK for type-safe reliable access to Squarespace commerce operations including orders, products, inventory, and transactions. Also covers customer and subscriber profiles, webhook management, page and blog management, form submissions, and analytics. Works with Claude Desktop, Claude Code, and any MCP-compatible client for full Squarespace site management through natural language.", "category": "web", "endpoint": "squarespace-mcp", "homepage_url": "https://github.com/BusyBee3333/squarespace-mcp-2026-complete", "github_url": "https://github.com/BusyBee3333/squarespace-mcp-2026-complete", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "squarespace", "cms", "ecommerce", "website-management", "commerce", "open-source", "typescript" ], "use_cases": [ "Manage Squarespace commerce operations including orders, products, inventory, and transactions through AI assistants without navigating the dashboard", "Automate Squarespace site management by having AI agents handle page updates, blog posts, form submissions, and analytics queries through natural language", "Build AI workflows that manage customer profiles, webhook subscriptions, and product catalogs across Squarespace sites through a single MCP connection" ], "health": "active" }, { "id": "microsoft-sql-mcp", "name": "Microsoft SQL MCP Server", "description": "Open-source MCP server from Microsoft that gives AI agents simplified access to data stored in SQL databases. Works with any cloud or on-premises database including Microsoft SQL, PostgreSQL, Azure Cosmos DB, and MySQL. Exposes SQL operations as MCP tools so agents interact with database entities through a typed CRUD surface for creating, reading, updating, deleting records, aggregating data, and executing stored procedures. Included as part of Data API Builder starting in version 1.7. Free to use and runs anywhere. Implements MCP protocol version 2025-06-18.", "category": "data", "endpoint": "microsoft-sql-mcp", "homepage_url": "https://learn.microsoft.com/en-us/azure/data-api-builder/mcp/overview", "github_url": "https://github.com/microsoft/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "database", "sql", "microsoft", "postgresql", "mysql", "cosmos-db", "open-source", "data-api-builder" ], "use_cases": [ "Give AI agents typed CRUD access to SQL databases for querying, inserting, updating, and deleting records through natural language without writing raw SQL", "Connect AI assistants to any cloud or on-premises database including Microsoft SQL, PostgreSQL, Azure Cosmos DB, and MySQL through a single MCP interface", "Execute stored procedures and aggregate data across SQL databases from AI agents with enterprise-grade security and governance built into Data API Builder" ], "health": "active" }, { "id": "financekey-mcp", "name": "FinanceKey Treasury MCP Server", "description": "Native MCP server from FinanceKey that gives enterprise AI tools secure access to live treasury data. One of the first treasury platforms to bring MCP-native workflows to enterprise finance teams. AI assistants including ChatGPT, Claude, and Gemini can securely query real-time treasury positions, cash balances, and financial operations through natural language. Designed for treasury teams, CFOs, and financial operations managers who need instant access to consolidated financial data across banking relationships.", "category": "payments", "endpoint": "financekey-mcp", "homepage_url": "https://treasury-management.com/news/financekey-launches-native-mcp-server-bringing-real-time-treasury-data-to-enterprise-ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "treasury", "finance", "enterprise", "banking", "cash-management", "cfos", "real-time-data" ], "use_cases": [ "Query live treasury positions and cash balances through AI assistants without logging into multiple banking portals or treasury management systems", "Enable CFOs and treasury teams to get instant answers about financial operations and consolidated banking data through natural language conversations", "Build AI-powered treasury workflows that pull real-time financial data for cash forecasting, liquidity analysis, and banking relationship management" ], "health": "active" }, { "id": "anchor-fintech-mcp", "name": "Anchor Fintech MCP Server", "description": "MCP server from Anchor, a leading African financial infrastructure company, that gives AI coding tools real-time accurate access to Anchor full API documentation. The first Nigerian fintech and first on the African continent to make its API documentation natively readable by AI systems. Developers using Claude Code, Cursor, and other MCP-compatible coding agents can query Anchor payment APIs, virtual accounts, and financial infrastructure endpoints through natural language. Designed for developers building on African financial rails.", "category": "payments", "endpoint": "anchor-fintech-mcp", "homepage_url": "https://techpoint.africa/brandpress/anchor-launches-nigerias-first-fintech-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "fintech", "africa", "nigeria", "payments", "banking-api", "developer-tools", "financial-infrastructure" ], "use_cases": [ "Give AI coding agents real-time access to Anchor payment API documentation for building applications on African financial infrastructure", "Enable developers to query virtual account, payment, and financial operations endpoints through natural language in Claude Code and Cursor", "Accelerate development on Nigerian and African financial rails by making API documentation natively readable by AI systems through MCP" ], "health": "active" }, { "id": "simulink-agentic-mcp", "name": "Simulink Agentic Toolkit MCP Server", "description": "MCP server from MathWorks that gives AI agents the tools and expertise to work with Simulink and Model-Based Design. Adds 7 Simulink-specific tools on top of the MATLAB MCP server including model-based design algorithm specification, plant model specification, Simulink model testing, and requirements generation. Skills encode recommended workflows so AI agents follow best practices instead of improvising. Works with Claude Code, GitHub Copilot, Cursor, OpenAI Codex, Sourcegraph Amp, and Gemini CLI. Open source on GitHub. Launched April 2026.", "category": "code", "endpoint": "simulink-agentic-mcp", "homepage_url": "https://www.mathworks.com/products/simulink-agentic-toolkit.html", "github_url": "https://github.com/matlab/simulink-agentic-toolkit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-12", "updated": "2026-06-12", "tags": [ "simulink", "mathworks", "model-based-design", "engineering", "simulation", "control-systems", "open-source" ], "use_cases": [ "Enable AI coding agents to specify, test, and generate requirements for Simulink models through natural language using 7 specialized Simulink tools", "Automate Model-Based Design workflows in Claude Code or Cursor with encoded best-practice skills that guide agents through recommended Simulink processes", "Give engineering teams AI-powered access to Simulink model testing and plant model specification without leaving their preferred coding environment" ], "health": "active" }, { "id": "oracle-autonomous-db-mcp", "name": "Oracle Autonomous AI Database MCP Server", "description": "Managed MCP server built into Oracle Autonomous AI Database that gives AI agents secure agentic access to Oracle databases in the cloud. Exposes Model Context Protocol endpoints so AI agents and clients including Claude Desktop and OCI AI Agent can invoke tools defined with Select AI Agent. Fully managed with no MCP setup required and delivers enterprise-grade auditing and performance controls for AI-to-data workflows. Supports database versions 19c and 26ai on Serverless Exadata Infrastructure. Available on all platforms from multicloud to on-premises. Generally available as of 2026.", "category": "data", "endpoint": "oracle-autonomous-db-mcp", "homepage_url": "https://www.oracle.com/autonomous-database/mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "oracle", "database", "enterprise", "autonomous-database", "cloud", "managed", "sql" ], "use_cases": [ "Give AI agents secure access to Oracle Autonomous databases for querying and managing data through natural language without custom integration code", "Enable AI-powered workflows that invoke database tools with enterprise-grade auditing, performance controls, and role-based access built in", "Connect Claude Desktop, OCI AI Agent, and other MCP clients to Oracle databases across multicloud and on-premises deployments through a single managed MCP endpoint" ], "health": "active" }, { "id": "phrase-mcp", "name": "Phrase MCP Server", "description": "Official open-source MCP server from Phrase for the Phrase localization API. Provides ready-to-use tools for Phrase Strings and Phrase TMS so AI agents can manage translation projects, update keys, access translation memories, and work with localization workflows directly from Claude, Cursor, and other MCP-compatible clients. Supports programmatic access to Style Guides, Quality Profiles, and Language Assets. Built with TypeScript. Open source on GitHub.", "category": "productivity", "endpoint": "phrase-mcp", "homepage_url": "https://phrase.com/product-launch-june-2026/", "github_url": "https://github.com/phrase/phrase-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "localization", "translation", "i18n", "translation-memory", "open-source", "typescript", "content-management" ], "use_cases": [ "Manage translation projects and localization keys through AI agents without leaving your development environment", "Access translation memories, style guides, and quality profiles programmatically through MCP for consistent multilingual content", "Automate localization workflows by having AI agents interact with Phrase Strings and Phrase TMS through natural language commands" ], "health": "active" }, { "id": "google-mcp-toolbox", "name": "Google MCP Toolbox for Databases", "description": "Open-source MCP server from Google that connects AI agents to over 40 enterprise data sources. Handles connection pooling, authentication, and security so agents can interact with databases through natural language without custom integration code. Natively supports AlloyDB, Cloud SQL, Cloud Spanner, BigQuery, and many third-party data sources. Includes Java SDK for typesafe agent orchestration. Reached v1.0 in April 2026. Works with Claude, Cursor, and any MCP-compatible client. Part of the Google Cloud AI ecosystem.", "category": "data", "endpoint": "google-mcp-toolbox", "homepage_url": "https://cloud.google.com/blog/products/ai-machine-learning/mcp-toolbox-for-databases-now-supports-model-context-protocol", "github_url": "https://github.com/googleapis/mcp-toolbox", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "google-cloud", "database", "alloydb", "cloud-sql", "spanner", "bigquery", "open-source", "enterprise" ], "use_cases": [ "Connect AI agents to 40+ enterprise data sources including AlloyDB, Cloud SQL, Spanner, and BigQuery through a single MCP interface with built-in connection pooling", "Build secure AI-to-database workflows with managed authentication and least-privilege access controls handled automatically by the toolbox", "Enable AI assistants to query and interact with Google Cloud databases and third-party data sources through natural language without writing custom integration code" ], "health": "active" }, { "id": "smartling-mcp", "name": "Smartling MCP Server", "description": "Official MCP server from Smartling that exposes enterprise translation, glossary, translation memory, and account-level tools through an MCP-compatible HTTP endpoint. AI assistants can securely call Smartling directly from development environments to automate and scale localization workflows. Works with Claude Code, Visual Studio Code, Cursor, and any MCP-compatible AI platform. Enables software engineers, product managers, and content teams to access translation capabilities without leaving their existing workflows. Open source on GitHub.", "category": "productivity", "endpoint": "smartling-mcp", "homepage_url": "https://www.smartling.com/company-news/smartling-launches-mcp-server", "github_url": "https://github.com/Jacobolevy/smartling-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "localization", "translation", "enterprise", "translation-memory", "glossary", "open-source", "content-management" ], "use_cases": [ "Access Smartling translation capabilities directly from AI coding environments to translate content, manage glossaries, and query translation memories without context switching", "Automate enterprise localization workflows by having AI agents manage translation jobs, check translation status, and interact with Smartling projects through natural language", "Enable product and content teams to scale multilingual content operations by connecting AI assistants to Smartling translation platform through a standardized MCP endpoint" ], "health": "active" }, { "id": "truto-mcp", "name": "Truto Unified API MCP Server", "description": "Managed MCP server platform from Truto that auto-generates MCP servers for over 250 SaaS integrations. Every connected account automatically becomes a set of tools that any MCP-compatible client can invoke. Uses real-time pass-through architecture with no data caching for always-fresh results. Each MCP connection is scoped to a specific integrated account ensuring agent actions are bounded to the correct data. Compatible with Claude, ChatGPT, Cursor, and any MCP client. Supports CRM, HRIS, ATS, accounting, ticketing, and calendar integrations.", "category": "infrastructure", "endpoint": "truto-mcp", "homepage_url": "https://truto.one/blog/best-mcp-server-platform-for-ai-agents-connecting-to-enterprise-saas/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "unified-api", "saas-integrations", "enterprise", "crm", "hris", "ats", "accounting", "platform" ], "use_cases": [ "Connect AI agents to 250+ SaaS platforms through auto-generated MCP servers with real-time pass-through data access and per-account scoping", "Build AI workflows that interact with CRM, HRIS, ATS, accounting, and ticketing systems through a single unified MCP interface without custom integrations", "Give AI agents typed tool definitions generated directly from SaaS API schemas to eliminate hallucination and ensure accurate data operations across enterprise platforms" ], "health": "active" }, { "id": "cve-mcp", "name": "CVE Security Intelligence MCP Server", "description": "Open-source MCP server that gives AI agents 27 security intelligence tools spanning 21 external APIs. Turns Claude into a full-spectrum security analyst with correlated access to NVD for CVE lookup, FIRST for EPSS scoring, CISA KEV status checks, MITRE ATT&CK mapping, Shodan for network intelligence, VirusTotal for file and URL analysis, and GreyNoise for threat intelligence. Supports bulk CVE lookups of up to 20 CVEs in parallel. Tools organized into five categories: Core Vulnerability Intelligence, Exploit and Attack Intelligence, Advanced Risk and Reporting, Network Intelligence, and Threat Intelligence. Works with Claude Desktop and Claude Code.", "category": "code", "endpoint": "cve-mcp", "homepage_url": "https://github.com/mukul975/cve-mcp-server", "github_url": "https://github.com/mukul975/cve-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "security", "vulnerability", "cve", "threat-intelligence", "shodan", "virustotal", "mitre-attack", "open-source" ], "use_cases": [ "Run comprehensive vulnerability assessments through AI agents with correlated intelligence from NVD, EPSS, CISA KEV, and MITRE ATT&CK in a single query", "Perform network and threat intelligence gathering through Claude with integrated Shodan, VirusTotal, and GreyNoise lookups without switching between multiple security tools", "Bulk analyze up to 20 CVEs in parallel with automated EPSS scoring, exploit availability checks, and severity assessments for prioritized remediation planning" ], "health": "active" }, { "id": "appomni-mcp", "name": "AppOmni SaaS Security MCP Server", "description": "MCP server from AppOmni that enables AI agents and security platforms to access deep SaaS security intelligence. AskOmni operates as an MCP server providing insights into SaaS identities, security posture, data exposures, and user behaviors for threat investigations across the SaaS domain. Integrates with SIEM, NDR, XDR, and IAM solutions to enrich SaaS alert context, detect real threats, and filter false positives. Can identify and block unauthorized prompt activity in ServiceNow agentic AI. Announced at RSA Conference. Works with Microsoft Copilot, Claude, and other MCP-compatible security tools.", "category": "infrastructure", "endpoint": "appomni-mcp", "homepage_url": "https://appomni.com/press-releases/worlds-first-saas-security-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "saas-security", "siem", "xdr", "threat-detection", "identity-security", "posture-management", "enterprise" ], "use_cases": [ "Give security AI agents access to SaaS identity, posture, and behavioral intelligence for automated threat investigations across enterprise SaaS environments", "Enrich SIEM and SOAR alerts with SaaS-specific context through MCP integration to detect real threats and filter false positives automatically", "Monitor and block unauthorized AI agent activity in enterprise SaaS platforms like ServiceNow by connecting security tools to AppOmni through MCP" ], "health": "active" }, { "id": "cequence-ai-gateway-mcp", "name": "Cequence AI Gateway MCP Server", "description": "Enterprise MCP gateway from Cequence that transforms any API into MCP-compatible tools with automated security, governance, and DLP scanning. Supports over 140 verified enterprise application integrations across collaboration, DevOps, marketing, and security platforms. Agent Personas feature provides infrastructure-level privilege scoping for autonomous AI agents with least-privilege access controls. Applies DLP scanning with 100+ detection types covering PII, credentials, financial data, and health records to both agent requests and MCP server responses. Deploys as SaaS or in customer private cloud. Works with Claude, Cursor, and Windsurf IDE.", "category": "infrastructure", "endpoint": "cequence-ai-gateway-mcp", "homepage_url": "https://www.cequence.ai/products/ai-gateway/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-13", "updated": "2026-06-13", "tags": [ "api-gateway", "enterprise-security", "dlp", "governance", "agent-personas", "zero-trust", "saas" ], "use_cases": [ "Transform enterprise APIs into secure MCP-compatible tools with automated DLP scanning, privilege scoping, and audit logging for safe AI agent access", "Deploy least-privilege Agent Personas that control exactly what autonomous AI agents can do down to the specific tool call across 140+ enterprise applications", "Govern AI agent interactions with corporate systems through a centralized MCP gateway with real-time monitoring, IP-locked sessions, and 100+ PII detection types" ], "health": "active" }, { "id": "azure-mcp-server", "name": "Azure MCP Server", "description": "Official unified MCP server from Microsoft that enables AI agents to securely access and manage Azure resources through natural language. Provides tools for Azure Resource Graph queries, ARM template deployments, Azure Kubernetes Service cluster management, Azure Container Apps, Cosmos DB, and AI Foundry. Built into Visual Studio 2026 and available as a standalone server. Inherits the local machine active az CLI session credentials for enterprise-grade security with no static connection strings. Open source on GitHub under the microsoft/mcp catalog.", "category": "infrastructure", "endpoint": "azure-mcp-server", "homepage_url": "https://learn.microsoft.com/en-us/azure/developer/azure-mcp-server/overview", "github_url": "https://github.com/microsoft/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "azure", "microsoft", "cloud", "kubernetes", "resource-graph", "arm-templates", "open-source", "enterprise" ], "use_cases": [ "Query Azure Resource Graph to list resource groups, trace NSG rules, and discover orphaned resources through natural language without memorizing Azure CLI syntax", "Manage Azure Kubernetes Service clusters, Container Apps, and Cosmos DB through AI agents with enterprise-grade security inherited from local az CLI credentials", "Deploy and manage ARM template deployments across Azure subscriptions through a standardized MCP interface built into Visual Studio 2026" ], "health": "active" }, { "id": "honeycomb-mcp", "name": "Honeycomb MCP Server", "description": "Hosted MCP server from Honeycomb that lets AI agents directly query, analyze, and visualize observability data including traces, triggers, and SLOs using natural language. First observability vendor to treat MCP as a fully managed service rather than a self-hosted tool. Available in the AWS Marketplace AI Agents and Tools category. Expanded in March 2026 with MCP capabilities for Claude Code, Cursor, AWS DevOps Agent, and additional platforms. Includes Agent Skills for guided observability workflows. May 2026 introduced Agent Timeline, Canvas Agent, and Canvas Skills for AI agents in production.", "category": "infrastructure", "endpoint": "honeycomb-mcp", "homepage_url": "https://docs.honeycomb.io/integrations/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "observability", "tracing", "slo", "managed", "aws-marketplace", "agent-observability", "production" ], "use_cases": [ "Query and analyze distributed traces, triggers, and SLOs through AI agents using natural language without running a local MCP server", "Monitor AI agents in production with Agent Timeline and Canvas Agent features purpose-built for agentic workflow observability", "Deploy Honeycomb observability capabilities to Claude Code, Cursor, and AWS DevOps Agent through a managed hosted MCP endpoint available on AWS Marketplace" ], "health": "active" }, { "id": "vault-radar-mcp", "name": "HashiCorp Vault Radar MCP Server", "description": "MCP server from HashiCorp Cloud Platform that enables AI agents to scan and detect secrets, credentials, and sensitive data across repositories and infrastructure. Part of the Vault Radar product for secret scanning and detection. Provides tools for identifying exposed API keys, tokens, passwords, and other secrets in codebases and cloud environments. Integrates with the broader HashiCorp Vault ecosystem for automated remediation workflows. Works with Claude and other MCP-compatible clients.", "category": "code", "endpoint": "vault-radar-mcp", "homepage_url": "https://developer.hashicorp.com/hcp/docs/vault-radar/mcp-server/overview", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "security", "secret-scanning", "hashicorp", "vault", "credentials", "compliance", "cloud-security" ], "use_cases": [ "Scan repositories and infrastructure for exposed secrets, API keys, and credentials through AI agents with automated detection and alerting", "Integrate secret scanning into AI-powered development workflows to catch credential leaks before they reach production", "Connect Vault Radar secret detection capabilities with AI agents for automated remediation workflows within the HashiCorp ecosystem" ], "health": "active" }, { "id": "sap-commerce-storefront-mcp", "name": "SAP Commerce Cloud Storefront MCP Server", "description": "MCP server from SAP that makes a retailer product catalog, pricing, inventory availability, and promotion structure accessible to any MCP-compatible AI agent. Enables agentic commerce by allowing AI agents including ChatGPT, Perplexity, Claude, and proprietary enterprise assistants to discover products and execute transactions autonomously. Announced at NRF 2026 as part of SAP AI retail operating system. Supports channel-less commerce by enabling businesses to engage with multiple AI agents embedded in their own experiences or from third-party assistants.", "category": "data", "endpoint": "sap-commerce-storefront-mcp", "homepage_url": "https://news.sap.com/2026/01/for-retailers-agentic-commerce-is-here/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "sap", "commerce", "retail", "e-commerce", "agentic-commerce", "product-catalog", "enterprise" ], "use_cases": [ "Enable AI agents to discover products, check pricing, and verify inventory availability across a retailer SAP Commerce Cloud catalog through natural language", "Power channel-less commerce by exposing product catalog and promotion data to multiple AI agents from ChatGPT, Perplexity, Claude, and proprietary enterprise assistants simultaneously", "Automate retail transaction workflows by connecting AI agents to SAP Commerce Cloud for autonomous product discovery, cart management, and checkout operations" ], "health": "active" }, { "id": "qualys-mcp", "name": "Qualys MCP Server", "description": "Open-source MCP server that provides real-time vulnerability, cloud security, endpoint, and compliance data from Qualys via natural language. Enables AI agents to query vulnerability management data, cloud security posture, and compliance status across enterprise environments. Part of the Qualys TotalAI ecosystem for AI-powered security operations. Supports detection of MCP servers as shadow IT across network, host, and supply chain perspectives. Works with Claude and other MCP-compatible security tools. Community-maintained on GitHub.", "category": "code", "endpoint": "qualys-mcp", "homepage_url": "https://blog.qualys.com/product-tech/2026/03/19/mcp-servers-shadow-it-ai-qualys-totalai-2026", "github_url": "https://github.com/nelssec/qualys-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "security", "vulnerability-management", "compliance", "cloud-security", "endpoint-security", "enterprise", "open-source" ], "use_cases": [ "Query Qualys vulnerability management data through AI agents to identify critical vulnerabilities, patch status, and remediation priorities via natural language", "Monitor cloud security posture and compliance status across enterprise environments by connecting AI security tools to Qualys through MCP", "Detect and inventory shadow MCP servers across network, host, and supply chain layers using Qualys TotalAI discovery capabilities" ], "health": "active" }, { "id": "fastio-mcp", "name": "Fastio MCP Server", "description": "Cloud-native MCP server from Fastio providing AI agents with persistent file storage, memory, and semantic search capabilities. Exposes 19 tools via Streamable HTTP and SSE transports covering file CRUD operations, folder management, and RAG-powered semantic search. Intelligence Mode auto-indexes files for retrieval-augmented generation. File locks prevent conflicts when multiple agents access the same file. Agents get dedicated accounts with 50GB free storage and 5000 monthly credits. Compatible with Claude Desktop, Cursor, Cline, and any MCP client that speaks HTTP.", "category": "infrastructure", "endpoint": "fastio-mcp", "homepage_url": "https://fast.io/resources/open-source-mcp-servers/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "file-storage", "agent-memory", "rag", "semantic-search", "cloud-storage", "file-management", "free-tier" ], "use_cases": [ "Give AI agents persistent cloud storage with 50GB free and semantic search for building long-term memory and file management workflows", "Enable multi-agent file collaboration with file locking and concurrent access controls through a standardized MCP interface", "Auto-index files for retrieval-augmented generation using Intelligence Mode so AI agents can search and retrieve documents semantically" ], "health": "active" }, { "id": "nginx-agentic-mcp", "name": "NGINX Agentic Observability MCP Server", "description": "MCP traffic monitoring module from NGINX that inspects Model Context Protocol traffic in real time and reports on throughput, latencies, errors, and traces. Introduces agentic observability at the infrastructure layer by providing visibility into MCP server interactions as they happen. Enables operators to monitor AI agent to MCP server communication patterns, identify bottlenecks, and troubleshoot latency issues. Integrates with existing NGINX deployments as a module. Announced on the NGINX Community Blog as part of the agentic AI infrastructure stack.", "category": "infrastructure", "endpoint": "nginx-agentic-mcp", "homepage_url": "https://blog.nginx.org/blog/introducing-agentic-observability-in-nginx-real-time-mcp-traffic-monitoring", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-14", "updated": "2026-06-14", "tags": [ "nginx", "observability", "traffic-monitoring", "latency", "infrastructure", "agentic-observability", "real-time" ], "use_cases": [ "Monitor MCP server traffic in real time at the NGINX layer to track throughput, latencies, and error rates across AI agent workflows", "Identify bottlenecks and troubleshoot latency in AI agent to MCP server communication patterns without modifying application code", "Add agentic observability to existing NGINX deployments as a module for full visibility into Model Context Protocol interactions" ], "health": "active" }, { "id": "webull-mcp", "name": "Webull MCP Server", "description": "Official MCP server from Webull (NASDAQ: BULL) that enables investors to access Webull OpenAPI through plain-language AI commands for trading and portfolio management. Place trades, manage positions, query account balances, and analyze market data using natural language through any MCP-compatible AI client. Removes the need for manual API script writing by translating conversational intent into brokerage operations. Announced June 11, 2026 as part of Webull broader AI integration strategy. Supports stocks, options, and other instruments available on the Webull platform.", "category": "data", "endpoint": "webull-mcp", "homepage_url": "https://www.webull.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "trading", "brokerage", "investing", "stocks", "options", "portfolio", "finance", "market-data" ], "use_cases": [ "Place stock and options trades through AI agents using plain-language commands without writing API integration code", "Query account balances, open positions, and portfolio performance through natural language in Claude or other MCP-compatible clients", "Analyze market data and manage investment positions through conversational AI workflows connected to Webull OpenAPI" ], "health": "active" }, { "id": "thegraph-mcp", "name": "The Graph MCP Server", "description": "MCP server from The Graph protocol that enables AI agents to query live on-chain blockchain data through Subgraphs and Substreams using natural language. Fans a single GraphQL query out to live Subgraph endpoints across multiple blockchain networks. Part of The Graph ecosystem for decentralized data indexing. Includes AI agent skills for guided blockchain data workflows. Supports querying DeFi protocols, NFT marketplaces, DAOs, and any indexed on-chain data. Open source on GitHub. Released June 11, 2026 alongside new AI agent skills for Subgraphs and Substreams.", "category": "data", "endpoint": "thegraph-mcp", "homepage_url": "https://thegraph.com/blog/querying-blockchain-data-natural-language-mcp-skills", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "blockchain", "web3", "subgraph", "graphql", "defi", "on-chain-data", "decentralized", "open-source" ], "use_cases": [ "Query live on-chain blockchain data across multiple networks through AI agents using natural language instead of writing GraphQL queries manually", "Analyze DeFi lending protocols, NFT marketplace activity, and DAO governance data through AI-powered Subgraph queries", "Build AI agent workflows that combine blockchain data from multiple Subgraph endpoints into unified cross-chain analytics" ], "health": "active" }, { "id": "subotiz-mcp", "name": "Subotiz MCP Server", "description": "MCP server from Subotiz that enables AI agents and developers to manage global subscription commerce, billing infrastructure, and payment pipelines through natural language. Engineers can query customer profiles, adjust pricing plans, audit webhook event logs, inspect refund histories, and retrieve documentation directly from code editors. Built on the open-source Model Context Protocol standard. Works with Cursor, VS Code, and Claude Desktop. Part of the broader Subotiz AI Agent Suite with five specialized commerce agents. Announced June 12, 2026. Designed for SaaS, AI, and digital entertainment enterprises.", "category": "payments", "endpoint": "subotiz-mcp", "homepage_url": "https://developer.subotiz.com/v1.0-en-us/reference/mcp", "github_url": "https://github.com/Subotiz/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "subscription", "billing", "payments", "commerce", "saas", "pricing", "webhooks", "open-source" ], "use_cases": [ "Manage subscription billing infrastructure through natural language in Cursor or VS Code without writing boilerplate API scripts for routine operations", "Query customer profiles, adjust pricing plans, and audit webhook event logs through AI agents connected to Subotiz payment pipelines", "Simulate and validate subscription payment pipelines through MCP-driven testing workflows for rapid SaaS monetization setup" ], "health": "active" }, { "id": "dataverse-mcp", "name": "Microsoft Dataverse MCP Server", "description": "MCP server from Microsoft that exposes Dataverse tables and records to AI agents and MCP-compatible clients. Part of the Power Platform ecosystem, enabling Copilot Studio agents, Visual Studio Code, and other MCP clients to access structured business data through natural language. Introduced closed-loop learning for enterprise agents in the June 2026 Power Platform update. Provides intelligent access to Dataverse entities including accounts, contacts, opportunities, and custom tables. Integrates with the broader Power Apps and Dynamics 365 ecosystem for enterprise data access.", "category": "data", "endpoint": "dataverse-mcp", "homepage_url": "https://learn.microsoft.com/en-us/power-apps/maker/data-platform/data-platform-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "microsoft", "dataverse", "power-platform", "dynamics-365", "enterprise", "crm", "business-data", "copilot-studio" ], "use_cases": [ "Give AI agents access to Dataverse business data including accounts, contacts, and opportunities through a standardized MCP interface with enterprise authentication", "Connect Copilot Studio agents to Power Platform data through MCP for natural language queries across Dynamics 365 and custom business tables", "Enable closed-loop learning for enterprise agents that read and write Dataverse records through the Power Platform MCP integration" ], "health": "active" }, { "id": "block-mcp", "name": "Block MCP for WordPress", "description": "Open-source MCP server from GravityKit that enables AI agents to edit WordPress posts at the Gutenberg block level without breaking block structure. Provides block-aware editing capabilities that understand WordPress block markup, allowing AI tools to insert, modify, reorder, and delete individual blocks while preserving the overall document structure. Solves the problem of AI agents corrupting block serialization when editing WordPress content as raw HTML. Works with Claude Desktop, Cursor, and other MCP clients. Community-maintained and open source.", "category": "web", "endpoint": "block-mcp", "homepage_url": "https://www.gravitykit.com/introducing-block-mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "wordpress", "gutenberg", "cms", "content-management", "blocks", "editing", "open-source" ], "use_cases": [ "Edit WordPress posts at the block level through AI agents without corrupting Gutenberg block markup or document structure", "Insert, modify, reorder, and delete individual Gutenberg blocks through natural language commands in Claude or Cursor", "Enable AI-powered WordPress content workflows that understand block types, attributes, and serialization for safe automated editing" ], "health": "active" }, { "id": "tecton-mcp", "name": "Tecton MCP Server", "description": "MCP server from Tecton that gives AI coding agents access to the Tecton feature store for machine learning feature development and management. Enables developers to query feature definitions, explore feature repositories, test feature pipelines, and debug feature serving issues through natural language in their IDE. Includes Cursor rules for guided feature engineering workflows. Helps ML teams develop, test, and iterate on feature definitions faster by connecting AI assistants directly to the Tecton platform. Open source on GitHub.", "category": "ai", "endpoint": "tecton-mcp", "homepage_url": "https://www.tecton.ai/", "github_url": "https://github.com/tecton-ai/tecton-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "feature-store", "machine-learning", "ml-features", "data-engineering", "feature-pipelines", "open-source" ], "use_cases": [ "Query and explore Tecton feature store definitions through AI agents for faster ML feature development and debugging", "Test and iterate on feature pipeline configurations through natural language in Cursor or VS Code with Tecton MCP integration", "Debug feature serving issues and inspect feature values through AI-powered workflows connected to the Tecton feature platform" ], "health": "active" }, { "id": "unity-mcp", "name": "Unity MCP Server", "description": "Community MCP server that connects AI agents to the Unity game engine for automated game development workflows. Enables AI tools to interact with Unity Editor programmatically including scene management, asset manipulation, component configuration, and build operations. Supports reading and modifying Unity project structures, inspecting game objects and hierarchies, and executing editor commands through natural language. Active development with version 0.80.0 released June 10, 2026. Open source on GitHub with regular updates and growing community adoption.", "category": "code", "endpoint": "unity-mcp", "homepage_url": "https://github.com/IvanMurzak/Unity-MCP", "github_url": "https://github.com/IvanMurzak/Unity-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-15", "updated": "2026-06-15", "tags": [ "unity", "game-development", "game-engine", "editor", "3d", "scenes", "assets", "open-source" ], "use_cases": [ "Automate Unity game development workflows through AI agents for scene management, asset manipulation, and component configuration", "Inspect and modify Unity project structures, game object hierarchies, and editor settings through natural language commands", "Accelerate game prototyping by using AI agents to create scenes, configure components, and manage builds in Unity Editor" ], "health": "active" }, { "id": "power-apps-mcp", "name": "Power Apps MCP Server", "description": "MCP server from Microsoft Power Platform that enables AI agents to interact with Power Apps environments using closed-loop learning. Agents can create, read, update, and manage Power Apps canvas apps, model-driven apps, Dataverse tables, and Power Automate flows through natural language. Announced June 11, 2026 as part of the Power Platform June 2026 feature update. Supports enterprise governance and admin controls. Integrates with Copilot Studio and Microsoft 365 ecosystems. Designed for low-code app builders and enterprise IT teams.", "category": "productivity", "endpoint": "power-apps-mcp", "homepage_url": "https://www.microsoft.com/en-us/power-platform/blog/2026/06/11/whats-new-in-power-platform-june-2026-feature-update/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "microsoft", "power-platform", "power-apps", "low-code", "dataverse", "enterprise", "managed" ], "use_cases": [ "Build and modify Power Apps canvas apps through AI agent commands with closed-loop feedback that validates changes against Dataverse schema", "Manage Dataverse tables, columns, and relationships through natural language in Copilot Studio or any MCP-compatible client", "Orchestrate Power Automate flows and Power Apps deployments across environments using AI agents with enterprise governance controls" ], "health": "active" }, { "id": "cosmicjs-mcp", "name": "Cosmic JS MCP Server", "description": "Native MCP server from Cosmic, the headless CMS platform, that exposes 18 tools for AI-powered content management. Enables AI agents to create, read, update, and delete content objects, manage media assets, query content types, and configure webhooks through natural language. Supports bucket-level operations for multi-tenant content architectures. Works with Claude Desktop, Cursor, VS Code, and any MCP-compatible client. Designed for developers building AI-assisted publishing workflows and content-driven applications.", "category": "productivity", "endpoint": "cosmicjs-mcp", "homepage_url": "https://www.cosmicjs.com/blog/mcp-server-complete-guide", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "cms", "headless-cms", "content-management", "cosmic", "publishing", "media", "webhooks" ], "use_cases": [ "Create and publish content objects through AI agents using natural language commands connected to your Cosmic headless CMS bucket", "Manage media assets, content types, and webhook configurations through MCP-driven workflows in Claude Desktop or Cursor", "Build AI-assisted editorial pipelines that read existing content, generate drafts, and publish directly to Cosmic without leaving the coding environment" ], "health": "active" }, { "id": "formio-mcp", "name": "Form.io UAG MCP Server", "description": "MCP server from Form.io that enables AI agents to build, manage, and deploy enterprise forms and workflows in regulated environments. Part of the Form.io Universal Agent Gateway (UAG) platform. Supports creating form schemas, managing submissions, configuring validation rules, and orchestrating approval workflows through natural language. Designed for healthcare, government, and financial services organizations that require compliance-ready form infrastructure. Integrates with Form.io's governance and audit trail capabilities.", "category": "productivity", "endpoint": "formio-mcp", "homepage_url": "https://form.io/mcp-server-list-regulated-enterprise-developers/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "forms", "workflows", "enterprise", "compliance", "healthcare", "government", "regulated", "managed" ], "use_cases": [ "Build and deploy compliance-ready forms for healthcare and government applications through AI agents with built-in governance controls", "Manage form submissions, validation rules, and approval workflows through natural language in regulated enterprise environments", "Orchestrate multi-step form workflows with audit trails through MCP-connected AI agents for financial services compliance" ], "health": "active" }, { "id": "highspot-mcp", "name": "Highspot MCP Server", "description": "MCP server from Highspot, the sales enablement platform, now available in the OpenAI ChatGPT App Store. Brings deal execution capabilities directly into ChatGPT and other MCP-compatible clients. Part of Highspot's Winter Launch '26 release featuring Deal Intelligence powered by Deal Agent. Enables sales teams to access pitch decks, analyze deal progression, query content libraries, and get coaching recommendations through AI agents. Analyzes CRM data and buyer engagement signals. Announced June 8, 2026.", "category": "productivity", "endpoint": "highspot-mcp", "homepage_url": "https://www.businesswire.com/news/home/20260608502630/en/Highspot-MCP-Server-Now-Available-in-the-OpenAI-ChatGPT-App-Store-Bringing-Deal-Execution-Directly-Into-ChatGPT", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "sales-enablement", "deal-intelligence", "crm", "content-library", "chatgpt", "enterprise", "managed" ], "use_cases": [ "Access sales pitch decks and enablement content from Highspot's content library directly inside ChatGPT or Claude for deal preparation", "Analyze deal progression, buyer engagement signals, and CRM data through AI agents to get real-time coaching recommendations", "Query Highspot content libraries and deal rooms through natural language to surface the most relevant collateral for specific sales conversations" ], "health": "active" }, { "id": "pollinations-mcp", "name": "Pollinations MCP Server", "description": "MCP server from Pollinations, the open-source generative AI platform, that exposes image generation, text generation, and audio synthesis tools to AI agents. Features a live model catalog that dynamically updates as new AI models become available. Supports multiple generation backends including Stable Diffusion, Flux, and various LLMs. Free tier available with API key for higher limits. Updated June 8, 2026 with dynamic model catalog support. Works with Claude Desktop, Cursor, and any MCP-compatible client.", "category": "ai", "endpoint": "pollinations-mcp", "homepage_url": "https://github.com/pollinations/pollinations", "github_url": "https://github.com/pollinations/pollinations", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "generative-ai", "image-generation", "text-generation", "audio", "stable-diffusion", "flux", "open-source", "free-tier" ], "use_cases": [ "Generate images using Stable Diffusion, Flux, and other models through AI agent workflows in Claude or Cursor without managing GPU infrastructure", "Create multimodal content pipelines that combine text generation, image creation, and audio synthesis through a single MCP server connection", "Access a dynamically updated catalog of generative AI models and switch between them through natural language commands in any MCP-compatible client" ], "health": "active" }, { "id": "paperclip-mcp", "name": "Paperclip MCP Server", "description": "MCP server from Paperclip AI that exposes approval management and document workflow tools to AI agents. Enables creating, reviewing, and managing approval requests through natural language. Part of Paperclip's document intelligence platform for automated document processing and approval routing. Supports multi-step approval chains, document classification, and status tracking. Released as a standalone npm package (@paperclipai/mcp-server). Currently in beta. Designed for teams automating document-heavy business processes.", "category": "productivity", "endpoint": "paperclip-mcp", "homepage_url": "https://github.com/paperclipai/paperclip", "github_url": "https://github.com/paperclipai/paperclip", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @paperclipai/mcp-server", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "approvals", "document-management", "workflow", "automation", "document-intelligence", "beta" ], "use_cases": [ "Create and route approval requests through AI agents using natural language without switching to a separate approval management dashboard", "Automate multi-step document approval chains and track approval status through MCP-connected AI workflows in Claude or Cursor", "Classify incoming documents and automatically route them to appropriate approval workflows through AI agent pipelines" ], "health": "active" }, { "id": "honeybadger-mcp", "name": "Honeybadger MCP Server", "description": "Official MCP server from Honeybadger that gives AI coding assistants direct access to application error data, faults, notices, and uptime checks. Enables AI tools like Claude, Cursor, and Copilot to fetch, search, and analyze production errors in context while developers code. Provides structured access to Honeybadger's API through the MCP protocol. Supports listing projects, searching faults, retrieving notice details, and checking uptime monitors. Open source on GitHub under the honeybadger-io organization.", "category": "code", "endpoint": "honeybadger-mcp", "homepage_url": "https://www.honeybadger.io/changelog/honeybadger-mcp-server/", "github_url": "https://github.com/honeybadger-io/honeybadger-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx honeybadger-mcp-server", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "error-monitoring", "debugging", "observability", "honeybadger", "faults", "uptime", "open-source" ], "use_cases": [ "Fetch and analyze production errors directly inside Cursor or Claude while debugging without switching to the Honeybadger dashboard", "Search faults by error class, component, or environment and retrieve detailed notice payloads through AI-assisted triage workflows", "Monitor uptime check status and correlate downtime events with application errors through AI agent queries" ], "health": "active" }, { "id": "safedep-vet-mcp", "name": "SafeDep Vet MCP Server", "description": "MCP server built into SafeDep vet that protects AI-generated code from slopsquatting attacks, malicious packages, known vulnerabilities, and other software supply chain risks. When an AI coding assistant generates dependency recommendations, vet's MCP tools validate packages against vulnerability databases, malware signatures, and package registry metadata in real time. Supports npm, PyPI, Go, Maven, and other major ecosystems. Open source on GitHub. Designed for developers using AI coding assistants who need automated dependency safety checks.", "category": "infrastructure", "endpoint": "safedep-vet-mcp", "homepage_url": "https://safedep.io/introducing-vet-mcp-server", "github_url": "https://github.com/safedep/vet", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "security", "supply-chain", "slopsquatting", "vulnerability", "dependency", "open-source", "malware-detection" ], "use_cases": [ "Automatically validate AI-suggested package dependencies against vulnerability databases and malware signatures before adding them to your project", "Protect against slopsquatting attacks where AI hallucinated package names could lead to installing malicious typosquat packages", "Run real-time supply chain security checks on npm, PyPI, Go, and Maven dependencies directly within Cursor, Claude Code, or VS Code AI workflows" ], "health": "active" }, { "id": "julia-mcp", "name": "Julia MCP Server (Kaimon.jl)", "description": "MCP server that keeps persistent Julia language sessions alive across AI agent calls. Variables, functions, loaded packages, and computed state persist between tool executions, enabling stateful scientific computing workflows. Part of the Kaimon.jl project that bridges AI agents and the Julia ecosystem. Supports executing Julia code, inspecting variables, loading packages, and running benchmarks through MCP tools. Open source. Designed for researchers and data scientists who use Julia for numerical computing, machine learning, and scientific simulations.", "category": "code", "endpoint": "julia-mcp", "homepage_url": "https://discourse.julialang.org/t/ann-kaimon-jl-opening-the-gate-between-ai-agents-and-julia/135880", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-16", "updated": "2026-06-16", "tags": [ "julia", "scientific-computing", "repl", "persistent-sessions", "research", "numerical-computing", "open-source" ], "use_cases": [ "Run stateful Julia computing sessions through AI agents where variables and loaded packages persist across multiple tool calls", "Execute scientific computing workflows including data analysis, differential equations, and machine learning model training through natural language in Claude or Cursor", "Benchmark and profile Julia code through AI agent interactions with persistent session state for iterative optimization" ], "health": "active" }, { "id": "florence-healthcare-mcp", "name": "Florence Healthcare MCP Server", "description": "MCP server from Florence Healthcare that gives AI agents native access to eleven clinical trial workflow tools spanning 65,000 research sites and 30,000 active protocols. Enables sponsor and site AI agents to securely query, analyze, and act upon site reality in real time. Supports identifying missing documents, detecting skipped tasks, tracking study progress, and automating eTMF reconciliation through natural language. Works with Claude, ChatGPT, and custom agents. Announced June 16, 2026 at the DIA Global Annual Meeting. Includes dedicated SDKs for integration.", "category": "productivity", "endpoint": "florence-healthcare-mcp", "homepage_url": "https://www.florencehc.com/model-context-protocol-access-announcement/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "clinical-trials", "healthcare", "workflow", "document-management", "compliance", "enterprise", "managed" ], "use_cases": [ "Query missing IRB approvals, updated 1572s, and amendment packages across clinical trial sites through AI agents without manually auditing folders", "Monitor site health, predict enrollment risks, and automate eTMF reconciliation across thousands of research sites using sponsor-deployed AI agents", "Detect gaps in training compliance and site-level workflows blocking study activation through natural language queries to Florence's eleven workflow tools" ], "health": "active" }, { "id": "tridens-mcp", "name": "Tridens Monetization MCP Server", "description": "MCP server from Tridens Technology that connects AI tools and assistants to the Tridens Monetization billing platform for communications service providers. Routes requests to specialized Tridens AI Agents that handle market research, offer and pricing creation, billing explanations, and catalog management. Enables CSPs, MVNOs, and digital service providers to manage monetization operations through natural language in ChatGPT, Claude, or Gemini. Announced June 12, 2026. Designed for telecom billing and subscription management workflows.", "category": "productivity", "endpoint": "tridens-mcp", "homepage_url": "https://tridenstechnology.com/communications/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "telecom", "billing", "monetization", "pricing", "subscription", "enterprise", "managed" ], "use_cases": [ "Research competitor offers and design competitive mobile plans that are automatically created as packages, products, and pricing in Tridens Monetization", "Manage telecom catalog and billing workflows through natural language commands in ChatGPT, Claude, or Gemini without navigating the Tridens dashboard", "Automate repetitive catalog configuration and pricing changes for CSPs and MVNOs through AI agent pipelines connected to Tridens AI Agents via MCP" ], "health": "active" }, { "id": "crowdstrike-falcon-mcp", "name": "CrowdStrike Falcon MCP Server", "description": "Official MCP server from CrowdStrike that connects AI agents to the Falcon cybersecurity platform for intelligent security analysis. Provides tools for querying detections, investigating hosts, searching indicators of compromise, and analyzing threat intelligence through the CrowdStrike Falcon API. Supports host containment actions, RTR session management, and vulnerability assessment. Open source on GitHub under the CrowdStrike organization. Currently at v0.12.0 with active development. Works with Claude, Cursor, and any MCP-compatible client.", "category": "infrastructure", "endpoint": "crowdstrike-falcon-mcp", "homepage_url": "https://github.com/CrowdStrike/falcon-mcp", "github_url": "https://github.com/CrowdStrike/falcon-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "security", "cybersecurity", "crowdstrike", "threat-intelligence", "endpoint-detection", "incident-response", "open-source" ], "use_cases": [ "Query CrowdStrike Falcon detections and investigate compromised hosts through AI agents in Claude or Cursor during incident response workflows", "Search indicators of compromise and analyze threat intelligence data through natural language without switching to the Falcon console", "Assess host vulnerabilities and manage real-time response sessions through MCP-connected AI agents for automated security operations" ], "health": "active" }, { "id": "apideck-mcp", "name": "Apideck Unified API MCP Server", "description": "MCP server from Apideck that exposes 330 tools across 10 unified APIs covering accounting, CRM, file storage, HRIS, ATS, ecommerce, issue tracking, and more. Connects any MCP-compatible agent to 200+ SaaS connectors through one integration. Features three operating modes: dynamic (progressive tool discovery with 85% fewer tokens), static (all tools loaded), and code (programmatic endpoint access via sandboxed JS). Includes hosted endpoint at mcp.apideck.dev and local stdio option. MIT licensed. Updated to v0.11.0 on June 16, 2026.", "category": "productivity", "endpoint": "apideck-mcp", "homepage_url": "https://www.apideck.com/", "github_url": "https://github.com/apideck-libraries/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @apideck/mcp start", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "unified-api", "accounting", "crm", "hris", "file-storage", "ecommerce", "integration-platform", "open-source" ], "use_cases": [ "Connect AI agents to 200+ SaaS applications through a single MCP integration covering accounting, CRM, HRIS, file storage, and ecommerce APIs", "Run month-end close checks by fanning out aged-creditors, aged-debtors, balance sheet, and P&L reports in parallel through a single workflow tool", "Progressively discover and call 330 API tools across 10 unified APIs using dynamic mode that reduces initial token overhead by 85 percent" ], "health": "active" }, { "id": "automox-mcp", "name": "Automox MCP Server", "description": "Community MCP server for Automox, the cloud-native IT endpoint management platform. Acts as a stateless proxy between AI assistants and the Automox API, enabling device management, patch deployment, software installation, and compliance reporting through natural language. Supports querying device inventory, triggering patch scans, managing server groups, and executing Worklets. Open source on GitHub under AutomoxCommunity. Works with Claude Desktop, Cursor, and any MCP-compatible client. Designed for IT operations teams managing endpoint fleets.", "category": "infrastructure", "endpoint": "automox-mcp", "homepage_url": "https://github.com/AutomoxCommunity/automox-mcp", "github_url": "https://github.com/AutomoxCommunity/automox-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "endpoint-management", "it-operations", "patching", "device-management", "compliance", "open-source" ], "use_cases": [ "Query device inventory and compliance status across your endpoint fleet through AI agents without logging into the Automox console", "Trigger patch scans, deploy software updates, and manage server groups through natural language commands in Claude or Cursor", "Execute Automox Worklets and review patching compliance reports through MCP-connected AI workflows for automated IT operations" ], "health": "active" }, { "id": "valona-intelligence-mcp", "name": "Valona Intelligence MCP Server", "description": "MCP server from Valona Intelligence, the competitive and market intelligence platform named a Leader in the 2026 Gartner Magic Quadrant. Makes Valona's continuously curated market analysis, competitor tracking, and quantitative financial data directly available inside Microsoft Copilot, Claude, and other enterprise AI tools. Provides AI agents with pre-built intelligence rather than requiring them to reconstruct analysis from raw data each time. Announced June 16, 2026. Currently in enterprise pilot with select customers. Designed for CMI teams, strategists, and enterprise leadership.", "category": "data", "endpoint": "valona-intelligence-mcp", "homepage_url": "https://www.valonaintelligence.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "market-intelligence", "competitive-intelligence", "enterprise", "financial-data", "gartner-leader", "managed" ], "use_cases": [ "Access continuously updated competitive intelligence and market analysis through AI agents in Microsoft Copilot or Claude without recreating analysis from scratch", "Monitor competitor moves, market trends, and regulatory developments across 200,000+ verified sources through enterprise AI agent workflows", "Feed validated market intelligence into AI-driven strategic planning and decision-making workflows with pre-curated analysis from Valona's platform" ], "health": "active" }, { "id": "qrvey-mcp", "name": "Qrvey MCP Server", "description": "MCP server from Qrvey that brings embedded analytics capabilities to AI agents within multi-tenant SaaS products. Securely connects agents to datasets, dashboards, metadata, and tenant-specific permissions. Part of the Qrvey 9.2+ release introducing agentic analytics for SaaS platforms. Enables AI assistants to query analytics data, generate charts, and deliver governed insights within the context of each tenant's data access permissions. Designed for SaaS product teams embedding analytics and AI assistants into their applications.", "category": "data", "endpoint": "qrvey-mcp", "homepage_url": "https://qrvey.com/embedded-ai-analytics-platform/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "embedded-analytics", "saas", "multi-tenant", "dashboards", "data-visualization", "agentic-analytics", "managed" ], "use_cases": [ "Connect AI agents to tenant-specific analytics datasets and dashboards within multi-tenant SaaS applications through governed MCP endpoints", "Enable end users to query embedded analytics data through natural language AI assistants with automatic enforcement of tenant-level permissions", "Build agentic analytics workflows that generate charts, surface insights, and automate reporting within SaaS products using Qrvey's embedded platform" ], "health": "active" }, { "id": "smartsheet-mcp-enterprise", "name": "Smartsheet Enterprise MCP Server", "description": "Enterprise MCP server expansion from Smartsheet that adds ChatGPT, Microsoft Copilot, and Google Cloud Gemini connections alongside existing Claude support. Enables enterprise teams to query, update, and manage Smartsheet projects, sheets, and workflows through AI agents across all major AI platforms. Announced June 11, 2026 as an enterprise-grade expansion of Smartsheet's MCP capabilities. Supports multi-platform agent access to project management data with enterprise authentication and governance controls.", "category": "productivity", "endpoint": "smartsheet-mcp-enterprise", "homepage_url": "https://www.smartsheet.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "project-management", "enterprise", "smartsheet", "multi-platform", "chatgpt", "copilot", "gemini", "managed" ], "use_cases": [ "Query and update Smartsheet projects and sheets through ChatGPT, Microsoft Copilot, Gemini, or Claude using natural language with enterprise governance controls", "Build cross-platform AI agent workflows that manage project timelines, task assignments, and sheet updates across enterprise teams via MCP", "Connect enterprise AI assistants to Smartsheet data for automated status reporting, resource allocation queries, and workflow management" ], "health": "active" }, { "id": "bumper-podcast-mcp", "name": "Bumper Podcast MCP Server", "description": "MCP server from Bumper that gives enterprise podcast teams AI agent access to show analytics, listener metrics, and episode performance data. Part of Bumper's free-tier dashboard expansion announced June 2026. Enables querying podcast performance data, comparing episode metrics, and generating analytics reports through natural language in any MCP-compatible AI client. Designed for podcast networks and enterprise media teams managing multiple shows. Supports tenant-level data isolation for multi-show management.", "category": "data", "endpoint": "bumper-podcast-mcp", "homepage_url": "https://www.bumperpodcasts.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-17", "updated": "2026-06-17", "tags": [ "podcast", "analytics", "media", "enterprise", "metrics", "managed" ], "use_cases": [ "Query podcast listener metrics, episode performance, and show analytics through AI agents without navigating the Bumper dashboard", "Compare episode performance across multiple shows and generate analytics reports through natural language in Claude or other MCP clients", "Build automated podcast performance monitoring workflows that surface listener trends and engagement patterns through AI agent pipelines" ], "health": "active" }, { "id": "yext-mcp", "name": "Yext MCP Server", "description": "Hosted MCP server from Yext that connects AI agents to the Yext Knowledge Graph, giving them real-time access to structured brand data including locations, products, events, and analytics. Enables AI assistants in ChatGPT, Claude, and Gemini to read and edit core brand data through natural language without custom API integrations. Supports use cases like managing local listings, querying analytics via Scout Visibility, and powering brand-controlled chatbots. Enterprise-grade with authentication, permissions, and compliance built in. Currently in beta. Announced December 2025 with ongoing expansion through June 2026.", "category": "data", "endpoint": "yext-mcp", "homepage_url": "https://www.yext.com/blog/unlock-the-agentic-ai-era-with-yext-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "knowledge-graph", "brand-data", "local-seo", "analytics", "enterprise", "managed", "beta" ], "use_cases": [ "Query and update location data, product listings, and event information across the Yext Knowledge Graph through AI agents in ChatGPT, Claude, or Gemini", "Power brand-controlled chatbots and internal AI assistants with verified, structured business data from Yext without building custom API integrations", "Analyze local SEO performance, listing metrics, and Scout Visibility insights through natural language queries via MCP-connected AI workflows" ], "health": "active" }, { "id": "data-commons-mcp", "name": "Google Data Commons MCP Server", "description": "MCP server from Google that gives AI agents access to the Data Commons open knowledge graph containing public statistical data from sources like the US Census, World Bank, CDC, and more. Provides two tools: search_indicators for discovering available variables and topics by place or metric, and get_observations for fetching statistical data for specific variables and places. Available as a free hosted service on Google Cloud or self-hosted via Python package or Docker image. Supports Streamable HTTP and stdio transports. Works with Gemini CLI, Claude, and any MCP-compatible client. Apache 2.0 licensed. Install via uvx datacommons-mcp.", "category": "data", "endpoint": "data-commons-mcp", "homepage_url": "https://docs.datacommons.org/mcp/", "github_url": "https://github.com/datacommonsorg/agent-toolkit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "uvx datacommons-mcp serve stdio", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "public-data", "statistics", "government", "census", "economics", "health-data", "open-source", "google" ], "use_cases": [ "Query public statistical data across countries and regions through natural language, such as GDP rankings, population trends, and health indicators from authoritative sources", "Search available indicators and topics for any place or metric using the search_indicators tool to discover what data Data Commons has before fetching observations", "Compare economic, demographic, and health statistics across geographies and time periods through AI agent workflows connected to the hosted Data Commons MCP service" ], "health": "active" }, { "id": "ibm-openpages-mcp", "name": "IBM OpenPages MCP Server", "description": "Experimental MCP server from IBM that connects AI agents to the OpenPages governance, risk, and compliance platform. Enables querying GRC data, managing risk assessments, and interacting with compliance workflows through natural language in MCP-compatible AI clients. Open source on GitHub under the IBM organization. Designed for enterprise GRC teams using OpenPages for regulatory compliance, audit management, and operational risk. Supports local deployment via stdio transport with API key authentication to the OpenPages instance.", "category": "productivity", "endpoint": "ibm-openpages-mcp", "homepage_url": "https://github.com/IBM/ibm-openpages-local-mcp-server", "github_url": "https://github.com/IBM/ibm-openpages-local-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "grc", "governance", "risk-management", "compliance", "audit", "ibm", "enterprise", "open-source" ], "use_cases": [ "Query governance, risk, and compliance data from IBM OpenPages through AI agents without navigating the OpenPages dashboard directly", "Manage risk assessments and compliance workflows through natural language commands in Claude or other MCP-compatible AI clients", "Automate GRC reporting and audit task management through MCP-connected AI agent pipelines integrated with the OpenPages platform" ], "health": "active" }, { "id": "ssh-manager-mcp", "name": "MCP SSH Manager", "description": "MCP server that provides 37 tools for managing multiple SSH connections through AI agents. Enables Claude Code, OpenAI Codex, and other MCP-compatible clients to execute remote commands, transfer files, manage tunnels, and handle multi-server orchestration through natural language. Supports concurrent connections to multiple hosts with session persistence. Includes tools for command execution, file upload and download, port forwarding, and server inventory management. Open source on GitHub under bvisible. Designed for DevOps teams and system administrators managing remote server fleets.", "category": "infrastructure", "endpoint": "ssh-manager-mcp", "homepage_url": "https://github.com/bvisible/mcp-ssh-manager", "github_url": "https://github.com/bvisible/mcp-ssh-manager", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "ssh", "devops", "remote-management", "server-administration", "file-transfer", "tunneling", "open-source" ], "use_cases": [ "Execute commands across multiple remote servers simultaneously through AI agents in Claude Code or Cursor without manually SSH-ing into each host", "Transfer files between local and remote machines, set up port forwarding, and manage SSH tunnels through natural language commands via MCP", "Orchestrate multi-server deployments and maintenance tasks through AI agent workflows that maintain persistent SSH sessions across server fleets" ], "health": "active" }, { "id": "aibap-mcp", "name": "AIBAP SAP ABAP MCP Server", "description": "MCP server for SAP ABAP development that connects AI agents to SAP systems via the ABAP Development Tools API. Enables reading, writing, testing, and deploying ABAP code through natural language in MCP-compatible AI clients without requiring SAP GUI. Supports source code management, transport handling, and syntax checking through the ADT REST API. Open source under MIT license on GitHub under Hochfrequenz. Designed for SAP developers and consultants working with ABAP codebases who want AI-assisted development workflows. Created June 15, 2026.", "category": "code", "endpoint": "aibap-mcp", "homepage_url": "https://github.com/Hochfrequenz/aibap.mcp", "github_url": "https://github.com/Hochfrequenz/aibap.mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "sap", "abap", "erp", "enterprise-development", "adt-api", "open-source" ], "use_cases": [ "Read, write, and refactor SAP ABAP source code through AI agents without launching SAP GUI or Eclipse ADT", "Run syntax checks, execute unit tests, and manage transport requests for ABAP objects through natural language commands in Claude or Cursor", "Automate routine SAP ABAP development tasks like code review, documentation generation, and transport management through MCP-connected AI workflows" ], "health": "active" }, { "id": "pipedream-connect-mcp", "name": "Pipedream Connect MCP Server", "description": "MCP server from Pipedream that connects AI agents to over 2,500 APIs with more than 8,000 prebuilt tools covering services like Slack, GitHub, Google Sheets, Salesforce, HubSpot, and thousands more. Provides a single MCP endpoint that gives agents authenticated access to actions across the entire Pipedream integration catalog. Handles OAuth and API key management for connected services. Open source on GitHub under PipedreamHQ with 11,000+ stars. Works with Claude, ChatGPT, and any MCP-compatible client. Designed for developers building AI agents that need to interact with multiple third-party services.", "category": "productivity", "endpoint": "pipedream-connect-mcp", "homepage_url": "https://pipedream.com/", "github_url": "https://github.com/PipedreamHQ/pipedream", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "integration-platform", "automation", "api-gateway", "multi-service", "oauth", "workflow", "open-source" ], "use_cases": [ "Connect AI agents to 2,500+ APIs through a single MCP endpoint with prebuilt tools for services like Slack, GitHub, Google Sheets, and Salesforce", "Automate cross-service workflows through natural language by chaining actions across multiple third-party APIs without writing custom integration code", "Build AI agents that authenticate to and interact with dozens of SaaS services simultaneously using Pipedream's managed OAuth and API key infrastructure" ], "health": "active" }, { "id": "amd-lemonade-mcp", "name": "AMD Lemonade MCP Server", "description": "Open source local LLM server from AMD that runs language models on Ryzen AI PCs with NPU acceleration and now includes MCP server integration as of version 10.8 released June 17, 2026. Provides a local, private inference endpoint compatible with MCP tool calling, enabling AI agents to use locally-running models for reasoning and tool execution without cloud dependencies. Supports streaming tool calls and works with Hugging Face Tiny Agents and other MCP-compatible frameworks. Designed for developers who want fully local, private AI agent capabilities on AMD hardware. MIT licensed on GitHub under lemonade-sdk.", "category": "ai", "endpoint": "amd-lemonade-mcp", "homepage_url": "https://www.amd.com/en/developer/resources/technical-articles/2025/local-tiny-agents--mcp-agents-on-ryzen-ai-with-lemonade-server.html", "github_url": "https://github.com/lemonade-sdk/lemonade", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "local-llm", "amd", "ryzen-ai", "npu", "private", "edge-ai", "open-source" ], "use_cases": [ "Run AI agents entirely on-device using AMD Ryzen AI NPU acceleration with MCP tool calling for private, cloud-free inference", "Connect Hugging Face Tiny Agents and other MCP-compatible frameworks to a local Lemonade server for tool-augmented reasoning on AMD hardware", "Build edge AI agent workflows that execute MCP tools locally without sending data to external services, using AMD NPU for fast on-device inference" ], "health": "active" }, { "id": "google-developer-knowledge-mcp", "name": "Google Developer Knowledge MCP Server", "description": "MCP server from Google that provides AI agents with access to developer documentation, API references, and technical knowledge from Google's developer ecosystem. Part of Google's expanding MCP support across its services announced in June 2026. Enables AI coding assistants and development tools to query up-to-date Google developer documentation, SDK references, and best practices through natural language. Designed for developers working with Google Cloud, Android, Firebase, and other Google platforms who want AI-assisted access to technical documentation.", "category": "code", "endpoint": "google-developer-knowledge-mcp", "homepage_url": "https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-18", "updated": "2026-06-18", "tags": [ "documentation", "developer-tools", "google-cloud", "android", "firebase", "api-reference", "managed" ], "use_cases": [ "Query Google developer documentation, SDK references, and API guides through AI agents without searching multiple documentation sites manually", "Access up-to-date technical knowledge about Google Cloud, Android, Firebase, and other Google platforms through natural language in MCP-compatible coding assistants", "Integrate Google developer knowledge into AI-powered development workflows for accurate, current API usage examples and best practices" ], "health": "active" }, { "id": "paperjsx-mcp", "name": "PaperJSX MCP Server", "description": "Local MCP server that gives AI agents document generation tools for creating PPTX presentations, DOCX reports and contracts, PDF invoices and charts, and XLSX spreadsheets from JSON specifications. Wraps the free-tier @paperjsx/json-to-* packages with a dozen MCP tools. Runs in-process with no API key, no network calls, and no cloud backend. Every tool exposes a JSON Schema derived from its Zod definition so the agent sees accurate parameter hints. Writes generated files to disk and returns the absolute path. Works with Claude Desktop, Cursor, VS Code Copilot, Windsurf, Cline, Gemini CLI, and other MCP-compatible clients. Requires Node.js 18+. MIT licensed.", "category": "productivity", "endpoint": "paperjsx-mcp", "homepage_url": "https://paperjsx.com/", "github_url": "https://github.com/paperjsx/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @paperjsx/mcp-server", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "document-generation", "pdf", "docx", "pptx", "xlsx", "spreadsheets", "presentations", "open-source", "local" ], "use_cases": [ "Generate polished PPTX presentations, DOCX reports, PDF invoices, and XLSX spreadsheets from natural language prompts through AI agents in Claude Desktop or Cursor", "Automate contract and report creation by describing the document structure in conversation and letting the MCP server produce the file locally without cloud dependencies", "Build document generation pipelines where AI agents create formatted business documents from JSON specs and return file paths for downstream processing" ], "health": "active" }, { "id": "ms-365-mcp", "name": "Microsoft 365 MCP Server", "description": "MCP server by Softeria for interacting with Microsoft 365 and Office services through the Microsoft Graph API. Provides 200+ dynamically generated tools covering Excel, Calendar, Mail, OneDrive, OneNote, To Do, Planner, Outlook contacts, and user management. Supports read-only mode, tool filtering, and both HTTP and stdio transports. Authentication via MSAL with Microsoft Entra (Azure AD) app registration. Open source under MIT license. Requires Node.js 18+ and administrator-consented Graph API permissions.", "category": "productivity", "endpoint": "ms-365-mcp", "homepage_url": "https://github.com/Softeria/ms-365-mcp-server", "github_url": "https://github.com/Softeria/ms-365-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx @softeria/ms-365-mcp-server", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "microsoft-365", "office", "graph-api", "email", "calendar", "excel", "onedrive", "planner", "open-source" ], "use_cases": [ "Read and manage Outlook email, calendar events, and contacts through AI agents connected to Microsoft 365 via the Graph API", "Interact with Excel workbooks, OneDrive files, and OneNote notebooks through natural language commands in Claude or other MCP-compatible clients", "Automate Microsoft 365 workflows including To Do task management, Planner boards, and user administration through MCP-connected AI agents" ], "health": "active" }, { "id": "sportiq-mcp", "name": "SportIQ MCP Server", "description": "MCP server with 44 AI-callable tools for sports analytics across FIFA World Cup 2026, Formula 1, and IPL cricket. Features Monte Carlo bracket simulations with Poisson expected-goals models for football qualification probabilities, an F1 pit-strategy model using OpenF1 telemetry for stop-lap and compound recommendations, and a Dream11 IPL team builder using PuLP constraint solver for valid 11-player squads under credit and role caps. Public instance live on Cloud Run. Works with Claude, Cursor, Zed, and ChatGPT. MIT licensed. Created by Utkarsh Gupta.", "category": "data", "endpoint": "sportiq-mcp", "homepage_url": "https://github.com/Ninjabeam20/SportIQ-MCP", "github_url": "https://github.com/Ninjabeam20/SportIQ-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "sports", "analytics", "football", "formula-1", "cricket", "monte-carlo", "prediction", "open-source" ], "use_cases": [ "Simulate FIFA World Cup 2026 bracket outcomes using Monte Carlo methods with Poisson expected-goals models to project team qualification probabilities", "Optimize Formula 1 pit-stop strategy using OpenF1 telemetry data with tyre-degradation models that recommend stop laps and compound choices", "Build optimized Dream11 fantasy cricket teams for IPL using constraint-solving AI that picks valid squads under credit, role, and team caps" ], "health": "active" }, { "id": "fastmail-mcp", "name": "Fastmail MCP Server", "description": "Official MCP server from Fastmail that gives AI agents access to email, calendar, and contacts through the JMAP protocol. Hosted at api.fastmail.com/mcp with OAuth authentication providing three permission levels: read-only, write, and send. Enables AI assistants to search and organize emails, draft and send messages, manage calendar events with participants, and look up contacts. Works with Claude, ChatGPT, and any MCP-compatible client. Launched April 2026. No local installation required — connects directly to Fastmail's hosted endpoint.", "category": "communication", "endpoint": "fastmail-mcp", "homepage_url": "https://www.fastmail.com/blog/an-mcp-server-for-fastmail/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "email", "calendar", "contacts", "jmap", "fastmail", "managed", "oauth" ], "use_cases": [ "Search, read, and organize Fastmail emails through AI agents in Claude or ChatGPT with OAuth-authenticated read-only or full access", "Manage calendar events including creating meetings with participants and checking schedules through natural language via MCP-connected AI assistants", "Draft and send emails, look up contacts, and automate email workflows through Fastmail's hosted MCP endpoint without local server installation" ], "health": "active" }, { "id": "mcp-conduit", "name": "MCP Conduit", "description": "Open-source MCP gateway that routes requests across multiple MCP servers with 0.02ms overhead and 46K+ requests-per-second cache hits. Provides authentication, guardrails, plugin support, and multi-server routing in a single gateway layer. Validated with 1,341 tests. Enables organizations to consolidate access to multiple MCP servers behind a single entry point with policy enforcement, caching, and observability. Designed for production deployments where multiple MCP servers need unified access control and traffic management. Created by lacausecrypto.", "category": "infrastructure", "endpoint": "mcp-conduit", "homepage_url": "https://github.com/lacausecrypto/mcp-conduit", "github_url": "https://github.com/lacausecrypto/mcp-conduit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "gateway", "routing", "caching", "auth", "guardrails", "infrastructure", "open-source", "multi-server" ], "use_cases": [ "Route AI agent requests across multiple MCP servers through a single gateway with authentication, caching, and policy enforcement", "Consolidate access control for your MCP server fleet behind one entry point with sub-millisecond overhead and 46K+ RPS cache performance", "Add guardrails, observability, and plugin-based extensions to MCP server deployments without modifying individual server implementations" ], "health": "active" }, { "id": "mcp-sports-hub", "name": "Sports Hub MCP Server", "description": "Unified MCP server that aggregates 32 sports API providers into a single service with 336 tools covering scores, stats, odds, esports, college sports, chess, AFL, and more across 70+ sports. Each provider works independently — missing API keys do not block startup and tools return errors only when called without their key. Supports a free-only mode with 12 providers and approximately 109 tools via the SPORTS_HUB_PROVIDERS=free environment variable. Uses stdio transport. Works with Claude, GPT, Gemini, Llama, Mistral, and any MCP-compatible client. Requires Node.js 18+. Created by lacausecrypto.", "category": "data", "endpoint": "mcp-sports-hub", "homepage_url": "https://github.com/lacausecrypto/mcp-sports-hub", "github_url": "https://github.com/lacausecrypto/mcp-sports-hub", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "sports", "scores", "odds", "esports", "statistics", "aggregator", "open-source", "multi-provider" ], "use_cases": [ "Query live scores, standings, and statistics across 70+ sports from 32 providers through a single MCP server connected to any AI assistant", "Access betting odds, esports results, college sports data, and chess ratings through unified AI agent tools without managing dozens of separate API integrations", "Run a free-tier sports data setup with 12 providers and 109 tools for hobby projects and prototyping AI sports analytics workflows" ], "health": "active" }, { "id": "cisco-defenseclaw-mcp", "name": "Cisco DefenseClaw", "description": "Open-source security governance framework from Cisco AI Defense for agentic AI systems. Scans AI agent skills and MCP servers for vulnerabilities using a combination of the Cisco AI Defense inspect API, YARA rules, and LLM-as-a-judge to detect malicious MCP tools, prompt injections, tool poisoning, and toxic flows. Includes Skills Scanner, MCP Scanner, AI Bill of Materials generator, and CodeGuard for static analysis. Ensures every agent skill is scanned, every MCP server verified, and every AI asset cataloged automatically. Released at RSA 2026. Apache 2.0 licensed. Python-based.", "category": "infrastructure", "endpoint": "cisco-defenseclaw-mcp", "homepage_url": "https://cisco-ai-defense.github.io/", "github_url": "https://github.com/cisco-ai-defense/defenseclaw", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "security", "scanning", "governance", "vulnerability-detection", "cisco", "enterprise", "open-source", "ai-bom", "rsa-2026" ], "use_cases": [ "Scan MCP servers and agent skills for security vulnerabilities including prompt injection, tool poisoning, and toxic flows before deploying them in production", "Generate AI Bills of Materials cataloging every agent, skill, and MCP server in your organization for compliance and audit purposes", "Integrate automated security governance into CI/CD pipelines to verify that every MCP server and agent skill meets security policies before release" ], "health": "active" }, { "id": "segmentstream-mcp", "name": "SegmentStream MCP Server", "description": "MCP server from SegmentStream that gives AI agents access to cross-channel marketing attribution, budget optimization, and incrementality testing data. Connects to 30+ advertising platforms including Google Ads, Meta, TikTok, LinkedIn, Pinterest, and Snapchat. Provides attribution-corrected unified views of marketing performance rather than self-reported platform numbers. Enables AI assistants in Claude, ChatGPT, or Gemini to query cross-channel ROAS, investigate CPA changes, and optimize budgets through natural language. Included on every SegmentStream plan tier. Commercial SaaS with MCP endpoint.", "category": "data", "endpoint": "segmentstream-mcp", "homepage_url": "https://segmentstream.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "marketing", "attribution", "analytics", "advertising", "budget-optimization", "cross-channel", "saas", "managed" ], "use_cases": [ "Query cross-channel marketing attribution data corrected for self-reporting bias across Google Ads, Meta, TikTok, and 27+ other ad platforms through AI agents", "Analyze and optimize advertising budgets using incrementality testing results and attribution-corrected ROAS data via natural language in Claude or Gemini", "Investigate CPA spikes and campaign performance anomalies across all advertising channels through a single MCP-connected AI assistant workflow" ], "health": "active" }, { "id": "snyk-agent-scan-mcp", "name": "Snyk Agent Scan", "description": "Security scanner from Snyk for AI agents, MCP servers, and agent skills. Part of Snyk's Agent Security suite launched at RSAC 2026. Scans for common security vulnerabilities including prompt injections, tool poisoning, and toxic flows in agent skills and MCP servers. Provides MCP server governance through automated scanning and compliance checks. Available as open preview. Integrates with Snyk Studio for AI-assisted vulnerability detection and remediation in coding workflows. Works alongside Agent Guard for real-time enforcement and agent red-teaming via CLI.", "category": "infrastructure", "endpoint": "snyk-agent-scan-mcp", "homepage_url": "https://snyk.io/", "github_url": "https://github.com/snyk/agent-scan", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-19", "updated": "2026-06-19", "tags": [ "security", "vulnerability-scanning", "agent-security", "governance", "snyk", "open-source", "compliance" ], "use_cases": [ "Scan MCP servers and AI agent skills for prompt injection, tool poisoning, and toxic flow vulnerabilities before production deployment", "Automate security governance for your MCP server fleet by integrating Snyk Agent Scan into CI/CD pipelines for continuous vulnerability monitoring", "Red-team AI agents via the Snyk CLI to test for security weaknesses and ensure agent skills meet organizational security policies" ], "health": "active" }, { "id": "mcpjungle-mcp", "name": "MCPJungle", "description": "Self-hosted MCP gateway and registry for managing multiple MCP servers from a single endpoint. Built in Go with centralized tool discovery, access control, and multi-transport support for both Streamable HTTP and stdio. Agents connect to one gateway instead of multiple endpoints. Supports enterprise workflows with authentication, observability, and registry metadata. Deploys via Docker with a Postgres backend. Works with Claude Desktop, Cursor, and any MCP-compatible client. 1.1K GitHub stars. Open source under MIT license.", "category": "infrastructure", "endpoint": "mcpjungle-mcp", "homepage_url": "https://github.com/mcpjungle/MCPJungle", "github_url": "https://github.com/mcpjungle/MCPJungle", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "gateway", "registry", "self-hosted", "enterprise", "multi-server", "access-control", "open-source", "go" ], "use_cases": [ "Centralize access to multiple MCP servers behind a single gateway endpoint with built-in authentication and tool discovery for enterprise AI agent deployments", "Register and manage MCP servers and their tools through a self-hosted registry so teams can discover available agent capabilities without scattered configurations", "Route AI agent requests across multiple MCP servers with access control and observability from one Docker-deployed gateway" ], "health": "active" }, { "id": "metamcp-mcp", "name": "MetaMCP", "description": "Unified middleware MCP server with a web GUI for managing multiple MCP server connections. Acts as a proxy that dynamically aggregates MCP servers into a single unified endpoint. Supports multi-workspace switching for isolating contexts between different databases or projects. Self-hostable via Docker Compose. Works with any MCP client including Claude Desktop, Cursor, and VS Code. 2.4K GitHub stars. Free and open source. Created by metatool-ai.", "category": "infrastructure", "endpoint": "metamcp-mcp", "homepage_url": "https://docs.metamcp.com/", "github_url": "https://github.com/metatool-ai/metamcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "middleware", "aggregator", "gui", "proxy", "multi-workspace", "docker", "open-source", "self-hosted" ], "use_cases": [ "Manage all MCP server connections through a single web GUI with workspace isolation so different projects or databases never pollute each other's context", "Aggregate multiple MCP servers into one unified endpoint that any MCP client can connect to without managing separate server configurations", "Switch between workspaces dynamically to route AI agent requests to different sets of MCP servers based on the current project context" ], "health": "active" }, { "id": "anyquery-mcp", "name": "Anyquery", "description": "SQL query engine that lets AI agents query 40+ applications and data sources using standard SQL. Built on SQLite with a plugin system covering GitHub, Notion, Slack, Gmail, Google Calendar, Spotify, Apple Notes, Chrome bookmarks, and more. Includes a built-in MCP server accessible via stdio or HTTP transport. Can also act as a MySQL-compatible server for tools like TablePlus and Metabase. Single binary distribution. 1.7K GitHub stars. Open source. Created by Julien Music.", "category": "data", "endpoint": "anyquery-mcp", "homepage_url": "https://anyquery.dev/", "github_url": "https://github.com/julien040/anyquery", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "anyquery mcp --stdio", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "sql", "query-engine", "data-integration", "sqlite", "multi-source", "notion", "github", "gmail", "open-source" ], "use_cases": [ "Query data from 40+ applications including GitHub, Notion, Slack, and Gmail using standard SQL through an AI agent connected via MCP", "Let AI assistants join and analyze data across multiple SaaS tools in a single SQL query without building custom API integrations", "Run ad-hoc analytics across your personal data sources like Apple Notes, Chrome bookmarks, and Spotify through natural language translated to SQL" ], "health": "active" }, { "id": "1mcp-agent", "name": "1MCP Agent", "description": "Unified MCP runtime that aggregates multiple MCP servers behind a single serve process. Provides CLI mode with progressive discovery commands for inspect, instructions, and run workflows. Supports template servers for per-client or per-session resolution, async and lazy loading for faster startup, and namespace isolation. Built in TypeScript. Works with Claude Code, Cursor, Codex, and other MCP-compatible agents. Solves configuration sprawl by centralizing MCP server management. Created by 1mcp-app.", "category": "infrastructure", "endpoint": "1mcp-agent", "homepage_url": "https://github.com/1mcp-app/agent", "github_url": "https://github.com/1mcp-app/agent", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "aggregator", "runtime", "cli", "typescript", "lazy-loading", "namespace", "open-source", "multi-server" ], "use_cases": [ "Aggregate multiple MCP servers into a single unified runtime so AI agents connect to one endpoint instead of managing separate server configurations", "Use CLI mode with progressive discovery to inspect available tools, read server instructions, and run specific MCP operations across aggregated servers", "Reduce configuration sprawl by centralizing MCP server management with template servers that resolve per-client or per-session for multi-project workflows" ], "health": "active" }, { "id": "dollhousemcp", "name": "DollhouseMCP", "description": "Open-source MCP server for dynamic AI persona management with 42 tools covering personas, skills, templates, agents, memories, and ensembles. Includes a GitHub-powered marketplace for browsing, installing, and submitting community personas. Supports persona export and import across platforms. Works with Claude Code, Claude Desktop, Cursor, Gemini, Codex, and local LLMs. Elements follow you across MCP-compatible clients. Community-driven with automated submission workflows. MIT licensed.", "category": "ai", "endpoint": "dollhousemcp", "homepage_url": "https://github.com/DollhouseMCP/mcp-server", "github_url": "https://github.com/DollhouseMCP/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "persona", "customization", "marketplace", "skills", "templates", "agents", "community", "open-source" ], "use_cases": [ "Create and manage custom AI personas, skills, and templates that persist across Claude, Cursor, Gemini, and other MCP-compatible clients", "Browse and install community-contributed personas from a GitHub-powered marketplace with one-click installation and automated submission workflows", "Build complex AI agent configurations using ensembles that combine multiple personas, skills, and memories into reusable packages" ], "health": "active" }, { "id": "sap-ui5-mcp", "name": "SAP UI5 MCP Server", "description": "Official MCP server from SAP for AI-assisted UI5 framework development. Provides AI agents with access to UI5 CLI tools, UI5 linter, API documentation, and framework-specific context. Built in TypeScript. Integrates with VS Code GitHub Copilot, Claude Code, Cursor, and OpenCode. Part of the official SAP MCP server suite alongside CAP and Fiori Elements servers. Recommended for use with the SAP Fiori MCP server for the best agentic coding experience. Published as @ui5/mcp-server on npm.", "category": "code", "endpoint": "sap-ui5-mcp", "homepage_url": "https://github.com/UI5/mcp-server", "github_url": "https://github.com/UI5/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @ui5/mcp-server", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "sap", "ui5", "framework", "developer-tools", "typescript", "official", "enterprise", "fiori" ], "use_cases": [ "Get AI-assisted SAP UI5 development with framework-aware context including UI5 CLI tools, linting, and API documentation through Claude Code or Cursor", "Accelerate SAP Fiori application development by grounding AI coding agents with official UI5 framework knowledge and best practices", "Validate and lint UI5 code through AI agents that have direct access to the UI5 toolchain via MCP integration" ], "health": "active" }, { "id": "sap-ui5-webcomponents-mcp", "name": "SAP UI5 Web Components MCP Server", "description": "Official MCP server from SAP for AI-assisted development with UI5 Web Components. Provides AI agents with access to UI5 Web Components API documentation, framework integration guides for React, Angular, Vue, and vanilla JavaScript, and theming documentation. Built in TypeScript. Works with VS Code GitHub Copilot, Claude Code, Cursor, and OpenCode. Part of the official SAP MCP server ecosystem. Enables building enterprise UIs with UI5 Web Components through agentic AI workflows.", "category": "code", "endpoint": "sap-ui5-webcomponents-mcp", "homepage_url": "https://github.com/UI5/webcomponents-mcp-server", "github_url": "https://github.com/UI5/webcomponents-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "sap", "ui5", "web-components", "react", "angular", "vue", "enterprise", "official", "typescript" ], "use_cases": [ "Build enterprise UIs with UI5 Web Components through AI-assisted development with access to component API docs and framework integration guides for React, Angular, and Vue", "Get AI-grounded theming and styling guidance for UI5 Web Components across different frontend frameworks through MCP-connected agents", "Accelerate cross-framework UI development by letting AI agents reference official UI5 Web Components documentation and best practices directly" ], "health": "active" }, { "id": "sap-mdk-mcp", "name": "SAP MDK MCP Server", "description": "Official MCP server from SAP for AI-assisted mobile application development with the Mobile Development Kit. Provides AI agents with tools for project creation, artifact generation, build and deploy, validation, migration, and documentation lookup. Published as @sap/mdk-mcp-server on npm. Works with Claude Code, Cursor, Cline, OpenCode, and GitHub Copilot. Open source under Apache 2.0. Early release with active development. Created by SAP.", "category": "code", "endpoint": "sap-mdk-mcp", "homepage_url": "https://github.com/SAP/mdk-mcp-server", "github_url": "https://github.com/SAP/mdk-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx @sap/mdk-mcp-server", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "sap", "mobile", "mdk", "cross-platform", "developer-tools", "official", "enterprise", "open-source" ], "use_cases": [ "Build cross-platform SAP mobile applications through AI-assisted development with MDK project creation, artifact generation, and build-deploy tools via MCP", "Migrate and validate existing MDK mobile applications using AI agents that have direct access to the MDK toolchain and documentation", "Accelerate SAP mobile development workflows by letting AI coding agents handle project scaffolding, code generation, and deployment through natural language" ], "health": "active" }, { "id": "fintalio-mcp", "name": "Fintalio", "description": "LinkedIn prospecting automation MCP server that manages contacts, launches outreach sequences, and tracks responses through 19 AI-callable tools. Automates the LinkedIn prospecting pipeline from contact discovery through follow-up tracking. Designed for sales teams and recruiters using AI agents to scale LinkedIn outreach workflows. Released June 2026. Commercial MCP server with managed hosting.", "category": "communication", "endpoint": "fintalio-mcp", "homepage_url": "https://fintalio.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-20", "updated": "2026-06-20", "tags": [ "linkedin", "prospecting", "outreach", "sales", "automation", "crm", "managed", "commercial" ], "use_cases": [ "Automate LinkedIn prospecting by managing contacts, launching outreach sequences, and tracking responses through AI agents connected via MCP", "Scale sales outreach by letting AI assistants discover prospects, send personalized connection requests, and manage follow-up cadences on LinkedIn", "Track and analyze LinkedIn prospecting campaign performance through natural language queries to the Fintalio MCP server from Claude or other AI clients" ], "health": "active" }, { "id": "allvoicelab-mcp", "name": "AllVoiceLab", "description": "AI voice toolkit MCP server with text-to-speech, voice cloning, and end-to-end video translation. Supports natural-sounding speech in 30+ languages, voice conversion, subtitle extraction, hard-subtitle removal, and one-click video dubbing. Designed for short drama localization, AI audiobooks, and film narration production. Works with Claude Desktop, Cursor, Windsurf, and OpenAI Agents. Open source on GitHub. Created by AllVoiceLab.", "category": "ai", "endpoint": "allvoicelab-mcp", "homepage_url": "https://allvoicelab.com/mcp", "github_url": "https://github.com/allvoicelab/AllVoiceLab-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "voice", "tts", "voice-cloning", "video-translation", "multilingual", "audio", "open-source", "media" ], "use_cases": [ "Generate natural-sounding speech in 30+ languages from AI agents using text-to-speech with voice cloning capabilities via MCP", "Automate end-to-end video localization workflows including subtitle extraction, hard-subtitle removal, and one-click dubbing through AI agent integration", "Produce AI-generated audiobooks and film narration with voice conversion and multilingual speech synthesis through a single MCP server connection" ], "health": "active" }, { "id": "mindsdb-mcp", "name": "MindsDB MCP Server", "description": "Federated data engine MCP server that lets AI agents query 200+ data sources using plain English or SQL through a single interface. Connects to Slack, Gmail, databases, data warehouses, and SaaS applications. Built on the MindsDB platform with 38.8K GitHub stars. Supports Minds SDK integration for LLM interaction through a standardized MCP interface. Open source. Created by MindsDB.", "category": "data", "endpoint": "mindsdb-mcp", "homepage_url": "https://mindsdb.com/unified-model-context-protocol-mcp-server-for-applications", "github_url": "https://github.com/mindsdb/minds-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "data-integration", "federated", "sql", "multi-source", "open-source", "slack", "gmail", "enterprise" ], "use_cases": [ "Query 200+ data sources including databases, Slack, Gmail, and SaaS applications through a single MCP server using plain English or SQL from AI agents", "Build AI agents that access federated data across your entire stack without custom API integrations by connecting to MindsDB's unified MCP endpoint", "Run cross-source analytics and data exploration through natural language by connecting AI coding agents to MindsDB's federated query engine via MCP" ], "health": "active" }, { "id": "medispan-mcp", "name": "Medi-Span Expert AI", "description": "MCP server from Wolters Kluwer Health connecting AI agents to expert-curated medication data from Medi-Span. Provides drug content, dosing guardrails, and advanced decision logic for healthcare AI workflows. Designed for medication management, clinical decision support, pharmacy automation, and patient engagement use cases. Commercial with managed hosting. From the makers of UpToDate. Available to select partners and early adopters.", "category": "data", "endpoint": "medispan-mcp", "homepage_url": "https://www.wolterskluwer.com/en/solutions/medi-span", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "healthcare", "medication", "clinical", "drug-data", "enterprise", "commercial", "managed", "pharma" ], "use_cases": [ "Connect AI agents to expert-curated medication data for clinical decision support with validated drug content and dosing guardrails via MCP", "Build pharmacy automation and medication management workflows powered by AI agents with real-time access to Medi-Span drug intelligence", "Integrate deterministic medication intelligence into patient engagement applications through AI agents connected to Wolters Kluwer's healthcare MCP server" ], "health": "active" }, { "id": "microsoft-mcp-gateway", "name": "Microsoft MCP Gateway", "description": "Reverse proxy and management layer for MCP servers from Microsoft enabling scalable, session-aware routing and lifecycle management in Kubernetes environments. Provides a data gateway with session affinity, control plane for deploying and managing MCP servers, and a management portal with in-browser JSON-RPC test console. Includes enterprise-ready telemetry, access control, and observability. Open source on GitHub. Built in C#.", "category": "infrastructure", "endpoint": "microsoft-mcp-gateway", "homepage_url": "https://microsoft.github.io/mcp-gateway/", "github_url": "https://github.com/microsoft/mcp-gateway", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "gateway", "reverse-proxy", "kubernetes", "microsoft", "enterprise", "session-routing", "open-source", "management" ], "use_cases": [ "Deploy and manage MCP servers at scale in Kubernetes with session-aware routing that ensures all requests for a given session reach the same server instance", "Manage MCP server lifecycle including deploy, update, and delete operations through a control plane with a built-in web management portal and test console", "Route traffic to multiple MCP servers with enterprise-grade telemetry, access control, and observability for production AI agent deployments" ], "health": "active" }, { "id": "prestashop-mcp", "name": "PrestaShop MCP Server", "description": "MCP server for complete management of PrestaShop e-commerce stores. Provides AI agents with tools to manage products, categories, customers, orders, modules, cache, themes, and navigation menus. Supports prompt templates and resources for contextual AI interactions. Includes token-based and guarded no-auth modes. Works with Claude Desktop, Cursor, and any MCP-compatible client. Open source on GitHub.", "category": "web", "endpoint": "prestashop-mcp", "homepage_url": "https://github.com/latinogino/prestashop-mcp", "github_url": "https://github.com/latinogino/prestashop-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "ecommerce", "prestashop", "store-management", "products", "orders", "open-source", "self-hosted" ], "use_cases": [ "Manage PrestaShop e-commerce stores through AI agents with tools for products, categories, customers, orders, modules, and theme configuration", "Automate e-commerce operations by letting AI assistants handle product catalog updates, order management, and customer support tasks in PrestaShop", "Monitor and optimize PrestaShop store performance through natural language queries covering sales data, inventory levels, and customer analytics" ], "health": "active" }, { "id": "lemmebuyit-mcp", "name": "LemmeBuyIt", "description": "Real-time retail product data MCP server providing inventory and pricing from 80+ major US retailers including Walmart, Target, Home Depot, and Nike. Aggregates product catalog, availability, and pricing data through a unified API and MCP endpoint. Designed for shopping agents, price comparison tools, gift finders, and reseller sourcing workflows. Commercial with tiered pricing. Created by LemmeBuyIt.", "category": "web", "endpoint": "lemmebuyit-mcp", "homepage_url": "https://www.lemmebuyit.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "retail", "ecommerce", "product-data", "pricing", "shopping", "commercial", "managed", "comparison" ], "use_cases": [ "Build AI shopping agents that search and compare real-time product inventory and pricing across 80+ major US retailers through a single MCP connection", "Create price comparison and deal-finding workflows for AI assistants with live product availability data from Walmart, Target, Home Depot, and more", "Power reseller sourcing and arbitrage workflows by giving AI agents access to real-time retail pricing and inventory data across multiple storefronts" ], "health": "active" }, { "id": "buywhere-mcp", "name": "BuyWhere", "description": "Cross-border e-commerce product catalog MCP server for AI agents. Aggregates 11M+ products from Singapore, Southeast Asia, and US markets including Shopee, Lazada, Amazon SG, Courts, and Challenger. Provides search, price comparison, product details, affiliate links, and catalog browsing tools. Semantic search with filtering by category, price, and region. Free developer beta access with rate limits. Open source on GitHub.", "category": "web", "endpoint": "buywhere-mcp", "homepage_url": "https://buywhere.ai/", "github_url": "https://github.com/BuyWhere/buywhere-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-21", "updated": "2026-06-21", "tags": [ "ecommerce", "product-catalog", "price-comparison", "cross-border", "shopping", "open-source", "southeast-asia", "affiliate" ], "use_cases": [ "Search and compare products across Singapore, Southeast Asia, and US markets from AI agents with semantic search and filtering by category, price, and region", "Build AI-powered price comparison and shopping recommendation agents with access to 11M+ products from 50+ merchants via a single MCP connection", "Generate affiliate links and product recommendations through AI assistants connected to BuyWhere's cross-border e-commerce catalog for monetized shopping workflows" ], "health": "active" }, { "id": "keboola-mcp", "name": "Keboola MCP Server", "description": "Data platform MCP server that lets AI agents build, automate, and manage production-grade data pipelines through natural language prompts. Connects to Keboola's full data platform with tools for components, transformations, storage, SQL queries, and job management. Includes a semantic layer as single source of truth for data objects and documentation. Free MCP server with standard Keboola usage billing. Open source on GitHub. Created by Keboola.", "category": "data", "endpoint": "keboola-mcp", "homepage_url": "https://www.keboola.com/mcp", "github_url": "https://github.com/keboola/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "data-pipelines", "etl", "data-platform", "transformations", "sql", "open-source", "automation", "semantic-layer" ], "use_cases": [ "Build and automate production-grade data pipelines using natural language prompts through AI agents connected to Keboola's full data platform via MCP", "Let AI agents manage data components, transformations, storage, and SQL queries with automated retries, governance, and monitoring for reliable pipeline execution", "Use AI coding agents to configure data extractors, schedule jobs, and debug execution flows through Keboola's semantic layer without manual API configuration" ], "health": "active" }, { "id": "exotel-mcp", "name": "Exotel MCP Server", "description": "Telephony and messaging MCP server that lets AI agents trigger voice calls, SMS, and automated customer outreach through structured prompts. Connects to Exotel's communication stack for real-time voice and text interactions without requiring API development. Supports call initiation, SMS with fallback logic, WhatsApp messaging, and conversation flow management. Works with Claude, ChatGPT, and other LLMs. Open source on GitHub. Created by Exotel.", "category": "communication", "endpoint": "exotel-mcp", "homepage_url": "https://exotel.com/blog/exotels-mcp-server-powering-agentic-ai-for-real-conversations/", "github_url": "https://github.com/exotel/exotelmcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "telephony", "sms", "voice", "communication", "whatsapp", "open-source", "customer-engagement", "outreach" ], "use_cases": [ "Enable AI agents to place voice calls and send SMS messages to customers using natural language prompts without telephony API development via MCP", "Automate customer outreach workflows including abandoned cart follow-ups, order status updates, and appointment reminders through AI agents connected to Exotel", "Build AI-driven customer engagement flows with call initiation, SMS fallback logic, and WhatsApp messaging through a single MCP server connection" ], "health": "active" }, { "id": "apigee-mcp", "name": "Apigee MCP Server", "description": "Google Cloud API governance layer that exposes existing APIs cataloged in Apigee API hub as MCP tools for AI agents. Provides 30+ built-in policies for authorization, authentication, and governance without requiring code changes or new MCP server deployments. Supports OAuth 2.1 and OIDC authentication, tool-level analytics, and MCP-specific traffic segmentation. Transcodes existing API specifications automatically. Commercial via Google Cloud. Created by Google.", "category": "infrastructure", "endpoint": "apigee-mcp", "homepage_url": "https://cloud.google.com/blog/products/ai-machine-learning/mcp-support-for-apigee", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "api-gateway", "governance", "google-cloud", "enterprise", "commercial", "managed", "oauth", "security" ], "use_cases": [ "Expose existing APIs as MCP tools for AI agents through Apigee without code changes, new server deployments, or manual API configuration", "Govern AI agent access to enterprise APIs with 30+ built-in authorization, authentication, and security policies including OAuth 2.1 and OIDC support", "Monitor and analyze MCP tool usage with per-tool analytics, traffic segmentation, and audit trails through Google Cloud Apigee's management console" ], "health": "active" }, { "id": "easyship-mcp", "name": "Easyship MCP Server", "description": "Global shipping and logistics MCP server that connects AI agents to 550+ couriers across 200+ countries. Provides tools for comparing shipping rates, generating labels, scheduling carrier pickups, calculating import taxes and duties, retrieving tracking information, and pulling shipping analytics. First cross-border shipping MCP with real-time duty calculation. Free for all Easyship accounts. Open source on GitHub and PyPI. Created by Easyship.", "category": "web", "endpoint": "easyship-mcp", "homepage_url": "https://www.easyship.com/blog/easyship-mcp-server", "github_url": "https://github.com/easyship/easyship-mcp-plugin", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "shipping", "logistics", "ecommerce", "cross-border", "rates", "tracking", "open-source", "customs" ], "use_cases": [ "Compare shipping rates, generate labels, and schedule pickups across 550+ couriers in 200+ countries through AI agents connected to Easyship via MCP", "Calculate real-time import taxes and duties for cross-border shipments and automate shipping integrations using AI coding agents with no manual API configuration", "Build agentic commerce workflows with shipping rate comparison, label generation, tracking updates, and analytics data accessible through natural language prompts" ], "health": "active" }, { "id": "openobserve-mcp", "name": "OpenObserve MCP Server", "description": "Open source observability platform MCP server that connects AI agents to logs, metrics, traces, and real user monitoring data. Enables natural language queries instead of SQL or PromQL, automated alert creation and stream management, and AI-powered analysis for error pattern detection and latency spike diagnosis. Unifies all observability data into a single conversational interface. 140x lower storage costs than alternatives. Open source. Created by OpenObserve.", "category": "infrastructure", "endpoint": "openobserve-mcp", "homepage_url": "https://openobserve.ai/mcp-server/", "github_url": "https://github.com/openobserve/openobserve", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "observability", "logs", "metrics", "traces", "monitoring", "open-source", "alerting", "infrastructure" ], "use_cases": [ "Query logs, metrics, and traces in natural language through AI agents connected to OpenObserve instead of writing SQL or PromQL queries manually", "Automate observability operations by letting AI agents create alerts, manage streams, and debug performance issues through conversational MCP interactions", "Detect error patterns, explain latency spikes, and correlate logs with traces automatically using AI-powered analysis through OpenObserve's MCP server" ], "health": "active" }, { "id": "noma-mcp", "name": "Noma Agent Access Control", "description": "Agentic access control platform from Noma Security that discovers, governs, and enforces policies for AI agents and MCP servers across the enterprise. Automatically inventories every agent and MCP server, enables tool-level approve/review/block controls, and monitors behavioral chains including prompts, tool calls, and data access in real time. Detects prompt injection, data exfiltration, and scope violations via AI Detection and Response (AI-DR). Integrates with existing identity providers. Commercial with managed hosting. Created by Noma Security.", "category": "identity", "endpoint": "noma-mcp", "homepage_url": "https://noma.security/platform/agentic-access-control/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "security", "access-control", "governance", "enterprise", "commercial", "managed", "compliance", "agent-security" ], "use_cases": [ "Discover and inventory all AI agents and MCP servers across an organization with automatic tool-level access governance and approve/review/block policies", "Monitor AI agent behavioral chains in real time to detect prompt injection, data exfiltration, and scope violations with AI Detection and Response", "Enforce granular access control policies for MCP connections at the tool, agent type, user, team, or environment level across enterprise AI deployments" ], "health": "active" }, { "id": "marqeta-mcp", "name": "Marqeta MCP Server", "description": "Agentic payments MCP server from Marqeta that enables AI agents to issue virtual cards, manage spend, complete transactions, and handle disputes autonomously. Provides a standardized integration layer for secure access to Marqeta's payment APIs including card provisioning, transaction retrieval, balance queries, and anomaly flagging. Designed for corporate expense management, checkout automation, and financial operations. Beta access available. Open source on GitHub. Created by Marqeta.", "category": "payments", "endpoint": "marqeta-mcp", "homepage_url": "https://www.marqeta.com/platform/mcp-server", "github_url": "https://github.com/marqeta/marqeta-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "payments", "fintech", "virtual-cards", "transactions", "expense-management", "open-source", "agentic-payments", "card-issuing" ], "use_cases": [ "Enable AI agents to autonomously issue virtual cards, manage spend policies, and complete checkout transactions through Marqeta's payment infrastructure via MCP", "Build corporate expense management workflows where AI agents provision cards, monitor transaction activity, flag anomalies, and submit disputes programmatically", "Integrate agentic payment capabilities into AI-driven commerce applications with real-time balance queries, transaction retrieval, and governed card operations" ], "health": "active" }, { "id": "pagos-mcp", "name": "Pagos MCP Server", "description": "Payments intelligence MCP server that gives AI agents conversational access to harmonized payment data across multiple processors. Provides transaction event data, approval rates, fee breakdowns, processor performance metrics, and decline analysis. Ingests data at the transaction level from all connected processors, normalizes against a unified data model, and enriches with ecosystem context. Over 16 billion transaction events processed. Commercial with managed hosting. Created by Pagos.", "category": "payments", "endpoint": "pagos-mcp", "homepage_url": "https://pagos.ai/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-22", "updated": "2026-06-22", "tags": [ "payments", "fintech", "analytics", "intelligence", "commercial", "managed", "multi-processor", "decline-analysis" ], "use_cases": [ "Query harmonized payment data across multiple processors through AI agents to analyze approval rates, fee breakdowns, and decline patterns via natural language", "Give payments teams instant answers about transaction performance, processor comparisons, and decline spikes without manual dashboard navigation through MCP-connected AI", "Automate payments analytics workflows by connecting AI agents to Pagos for real-time access to 16B+ harmonized transaction events with unified data models" ], "health": "active" }, { "id": "appviewx-mcp", "name": "AppViewX MCP Server", "description": "Certificate lifecycle management MCP server that delivers live, governed certificate intelligence to AI assistants. Provides tools for querying certificate inventories, checking expiration status, analyzing PKI health, and managing certificate workflows across enterprise environments. Supports 47-day certificate validity compliance and post-quantum cryptography readiness. Works with Claude Desktop, GitHub Copilot, and any MCP client. Commercial with managed hosting. Created by AppViewX.", "category": "identity", "endpoint": "appviewx-mcp", "homepage_url": "https://www.appviewx.com/blogs/introducing-appviewx-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "certificates", "pki", "security", "enterprise", "commercial", "managed", "compliance", "identity" ], "use_cases": [ "Query certificate inventories and check expiration status across enterprise environments through AI assistants connected to AppViewX via MCP", "Analyze PKI health, identify compliance gaps, and manage certificate lifecycle workflows using natural language prompts in Claude or GitHub Copilot", "Automate certificate discovery, renewal tracking, and 47-day validity compliance monitoring through AI agents with governed access to certificate infrastructure" ], "health": "active" }, { "id": "pgedge-postgres-mcp", "name": "pgEdge Postgres MCP Server", "description": "Production-grade PostgreSQL MCP server that connects AI tools to any Postgres database with full schema introspection, performance metrics, and multi-database support. Pulls detailed information about primary keys, foreign keys, indexes, column types, and constraints. Exposes pg_stat_statements for query optimization. Supports TLS, token auth, and read-only enforcement. Works with Postgres 14+, including community Postgres, Amazon RDS, and pgEdge distributions. Open source under PostgreSQL license. Created by pgEdge.", "category": "data", "endpoint": "pgedge-postgres-mcp", "homepage_url": "https://www.pgedge.com/blog/introducing-the-pgedge-postgres-mcp-server", "github_url": "https://github.com/pgEdge/pgedge-postgres-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "postgres", "database", "sql", "open-source", "schema-introspection", "performance", "multi-database", "query-optimization" ], "use_cases": [ "Connect Claude Code, Cursor, or any MCP-compatible AI tool directly to PostgreSQL databases for schema exploration, query writing, and migration assistance", "Analyze database performance by exposing pg_stat_statements and index usage metrics to AI agents for automated query optimization recommendations", "Support multi-database workflows across dev, staging, and production PostgreSQL instances from a single MCP server with full schema introspection and security controls" ], "health": "active" }, { "id": "avalara-cross-border-mcp", "name": "Avalara Cross-Border Trade Services MCP Server", "description": "Cross-border trade and tariff compliance MCP server that provides AI agents with tools to perform duty calculations, retrieve tariff data for HS codes, and access the Avalara Trade and Tariff Library. Supports cross-border transaction compliance including customs duties, import taxes, and landed cost calculations across 180+ countries. Open source on GitHub. Created by Avalara.", "category": "payments", "endpoint": "avalara-cross-border-mcp", "homepage_url": "https://developer.avalara.com/mcp-servers/cross-border/", "github_url": "https://github.com/avadev/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "tariffs", "customs", "cross-border", "trade", "compliance", "duties", "open-source", "tax" ], "use_cases": [ "Calculate customs duties and import taxes for cross-border shipments using AI agents connected to Avalara's Trade and Tariff Library via MCP", "Retrieve tariff data for specific HS codes and determine landed costs across 180+ countries through natural language queries in MCP-compatible AI assistants", "Automate cross-border trade compliance workflows including duty rate lookups, tariff classification, and import tax estimation through AI agent integrations" ], "health": "active" }, { "id": "couchbase-mcp", "name": "Couchbase MCP Server", "description": "NoSQL database MCP server that gives AI agents real-time access to Couchbase data for answering questions, executing N1QL queries, and exploring cluster data. Supports schema discovery, document operations, full-text search, and index management. Available as a Docker container for easy deployment. Works with Claude, ChatGPT, and any MCP-compatible client. Open source on GitHub. Created by Couchbase.", "category": "data", "endpoint": "couchbase-mcp", "homepage_url": "https://www.couchbase.com/blog/introducing-couchbase-mcp-server-ai-agents/", "github_url": "https://github.com/couchbase/mcp-server-couchbase", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "nosql", "database", "couchbase", "open-source", "n1ql", "full-text-search", "docker", "document-db" ], "use_cases": [ "Query and explore Couchbase cluster data using natural language through AI agents with real-time access to documents, indexes, and full-text search", "Build AI-powered applications that execute N1QL queries, manage documents, and perform schema discovery against Couchbase databases via MCP", "Enable AI coding agents to interact with Couchbase for data modeling, query optimization, and application development through a Docker-deployable MCP server" ], "health": "active" }, { "id": "reprise-mcp", "name": "Reprise MCP Server", "description": "Enterprise demo platform MCP server that turns AI assistants into on-demand demo engineers. Provides over 100 demo-authoring tools spanning HTML capture, data injection, full application cloning, conversational rebranding, and library management. Enables AI-driven demo customization including logo swapping, copy changes, synthetic data generation, and interactive guide creation. Works with Claude, ChatGPT, Microsoft Copilot, Gemini, and any MCP-compatible client. Commercial with zero-setup deployment. Created by Reprise.", "category": "productivity", "endpoint": "reprise-mcp", "homepage_url": "https://www.reprise.com/platform/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "demos", "presales", "sales-enablement", "enterprise", "commercial", "managed", "branding", "product-tours" ], "use_cases": [ "Build tailored sales demos from AI conversations by pulling CRM and call recording context to rebrand and customize demos with prospect-specific data and logos", "Manage and refresh entire demo libraries at scale through natural language prompts, keeping hundreds of assets current, on-brand, and accurate from a single AI conversation", "Generate interactive product tour guides, synthetic datasets, and account-specific narratives without leaving the AI chat using Reprise's 100+ demo-authoring tools via MCP" ], "health": "active" }, { "id": "ordergroove-mcp", "name": "Ordergroove MCP Server", "description": "Subscription commerce MCP server that plugs enterprise subscription data into AI tools for analytics, payment recovery, and retention workflows. Part of Ordergroove's Autonomous Subscriptions platform with AI agents for subscriber signal analysis, churn prediction, and recurring revenue optimization. Works with Claude, ChatGPT, and MCP-compatible clients. Commercial with managed hosting. Created by Ordergroove.", "category": "web", "endpoint": "ordergroove-mcp", "homepage_url": "https://www.globenewswire.com/news-release/2026/06/18/3314288/0/en/ordergroove-introduces-autonomous-subscriptions-ai-agents-built-to-compound-recurring-revenue.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "subscriptions", "ecommerce", "recurring-revenue", "retention", "commercial", "managed", "analytics", "payments" ], "use_cases": [ "Connect subscription commerce data to AI assistants for real-time analytics on subscriber behavior, churn signals, and recurring revenue trends via MCP", "Automate payment recovery and retention workflows using AI agents that analyze subscriber signals and take action to reduce involuntary churn", "Query subscription performance metrics, cohort analysis, and revenue forecasts through natural language prompts in Claude or ChatGPT connected to Ordergroove" ], "health": "active" }, { "id": "digi-mcp", "name": "Digi MCP Server", "description": "IoT device management MCP server from Digi International that connects AI assistants to Digi Remote Manager and Genesis platforms. Enables natural language interfaces to query device fleets, automate workflows, generate configuration insights, and monitor connected devices across enterprise IoT deployments. Supports device health monitoring, fleet analytics, and automated troubleshooting. Commercial with managed hosting. Created by Digi International.", "category": "infrastructure", "endpoint": "digi-mcp", "homepage_url": "https://www.digi.com/company/press-releases/2026/digi-launches-mcp-server-to-power-ai-workflows", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "iot", "device-management", "fleet-management", "monitoring", "commercial", "managed", "automation", "edge-computing" ], "use_cases": [ "Query and monitor IoT device fleets using natural language through AI assistants connected to Digi Remote Manager via MCP for real-time device health insights", "Automate IoT device configuration, troubleshooting, and workflow management across enterprise deployments using AI agents with access to Digi's management platform", "Generate fleet analytics reports and configuration insights for connected devices across Digi Remote Manager and Genesis platforms through conversational AI prompts" ], "health": "active" }, { "id": "microsoft-clarity-mcp", "name": "Microsoft Clarity MCP Server", "description": "Web analytics MCP server from Microsoft that provides AI-driven natural language access to website analytics data. Enables querying metrics like scroll depth, engagement time, total traffic, and session data filtered by dimensions such as browser, operating system, country, and device type. Integrates with Claude Desktop and other MCP-compatible clients. Free with Clarity project. Open source on GitHub and npm. Created by Microsoft.", "category": "data", "endpoint": "microsoft-clarity-mcp", "homepage_url": "https://learn.microsoft.com/en-us/clarity/third-party-integrations/clarity-mcp-server", "github_url": "https://github.com/microsoft/clarity-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx @microsoft/clarity-mcp-server --clarity_api_token=YOUR_TOKEN", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "analytics", "web-analytics", "microsoft", "open-source", "scroll-depth", "engagement", "traffic", "heatmaps" ], "use_cases": [ "Query website analytics data using natural language prompts to retrieve scroll depth, engagement time, and traffic metrics filtered by browser, device, or country", "Analyze user behavior patterns across devices and browsers to identify engagement trends and optimize web experiences through AI-assisted analytics", "Generate website performance reports with Microsoft Clarity data including session counts, page views, and engagement breakdowns without manual dashboard navigation" ], "health": "active" }, { "id": "microsoft-advertising-mcp", "name": "Microsoft Advertising MCP Server", "description": "Campaign management MCP server from Microsoft that connects AI workflows to live Microsoft Advertising campaign data. Provides read-only access to campaign performance, keyword analytics, conversion tracking, and budget metrics. Works with M365 Copilot, Claude, ChatGPT, and any MCP-compatible client. Currently in open pilot. Commercial via Microsoft Advertising. Created by Microsoft.", "category": "productivity", "endpoint": "microsoft-advertising-mcp", "homepage_url": "https://about.ads.microsoft.com/en/blog/post/june-2026/building-a-new-ai-economy-that-creates-value-for-everyone", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "advertising", "microsoft", "campaigns", "marketing", "commercial", "managed", "analytics", "search-ads" ], "use_cases": [ "Build custom AI workflows grounded in live Microsoft Advertising campaign data to simplify campaign management and performance analysis across M365 Copilot or Claude", "Audit campaign health, conversion goals, and audience signals adoption at scale using AI agents connected to Microsoft Advertising via MCP", "Analyze keyword performance, CPC, CTR, and ROAS across Microsoft Advertising campaigns through natural language queries in any MCP-compatible AI client" ], "health": "active" }, { "id": "canvas-mcp", "name": "Canvas LMS MCP", "description": "MCP server for Canvas Learning Management System with 90+ tools for students and educators. Manage courses, assignments, grades, enrollments, and run agent skills for course audits and accessibility checks.", "category": "productivity", "endpoint": "npx -y canvas-mcp", "homepage_url": "https://github.com/vishalsachdev/canvas-mcp", "github_url": "https://github.com/vishalsachdev/canvas-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y canvas-mcp", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "canvas", "lms", "education", "courses", "assignments", "grades" ], "use_cases": [ "Query and manage Canvas LMS courses, assignments, and grades via AI", "Run automated course quality audits and accessibility checks", "Let students and educators interact with Canvas through natural language" ], "health": "active" }, { "id": "mcp-ssh-manager", "name": "MCP SSH Manager", "description": "37-tool MCP server for remote SSH management. Execute commands, transfer files, manage databases, create backups, monitor server health, and automate DevOps tasks across multiple servers from Claude Code or Codex.", "category": "infrastructure", "endpoint": "npx -y mcp-ssh-manager", "homepage_url": "https://github.com/bvisible/mcp-ssh-manager", "github_url": "https://github.com/bvisible/mcp-ssh-manager", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y mcp-ssh-manager", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "ssh", "devops", "infrastructure", "remote", "database", "backup" ], "use_cases": [ "Execute remote commands and transfer files across multiple SSH servers", "Automate database backups for MySQL, PostgreSQL, and MongoDB via AI", "Monitor server health and run DevOps automation from Claude Code" ], "health": "active" }, { "id": "hashicorp-vault-mcp", "name": "HashiCorp Vault MCP Server", "description": "Official HashiCorp MCP server for Vault secrets management. Gives AI models access to Vault APIs for reading secrets, managing mounts, and performing auditable secret operations via stdio or streamable HTTP.", "category": "identity", "endpoint": "vault server -mcp-mode", "homepage_url": "https://developer.hashicorp.com/vault/docs/mcp-server/overview", "github_url": "https://github.com/hashicorp/vault-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "brew install vault", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "vault", "secrets", "hashicorp", "security", "infrastructure", "devops" ], "use_cases": [ "Give AI agents auditable, controlled access to HashiCorp Vault secrets", "Read and manage Vault mounts and secret paths via natural language", "Integrate Vault secret operations into AI-powered DevOps workflows" ], "health": "active" }, { "id": "mcp-gateway-registry", "name": "MCP Gateway Registry", "description": "Enterprise-ready MCP gateway and registry that centralizes AI tool access with OAuth authentication, dynamic tool discovery, and Keycloak/Entra identity provider integration. Turns scattered MCP servers into governed, auditable tool access.", "category": "identity", "endpoint": "https://github.com/agentic-community/mcp-gateway-registry", "homepage_url": "https://github.com/agentic-community/mcp-gateway-registry", "github_url": "https://github.com/agentic-community/mcp-gateway-registry", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "docker compose up -d", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "gateway", "registry", "oauth", "enterprise", "keycloak", "identity" ], "use_cases": [ "Centralize and govern access to multiple MCP servers with OAuth and audit logs", "Integrate enterprise identity providers like Keycloak or Entra into MCP tool access", "Enable dynamic tool discovery for AI coding assistants across an organization" ], "health": "active" }, { "id": "minimax-mcp", "name": "MiniMax MCP", "description": "Official MiniMax MCP server for text-to-speech, voice cloning, image generation, and video generation. Supports Claude Desktop, Cursor, and other MCP clients with multimodal AI generation capabilities.", "category": "media", "endpoint": "npx -y minimax-mcp", "homepage_url": "https://github.com/MiniMax-AI/MiniMax-MCP", "github_url": "https://github.com/MiniMax-AI/MiniMax-MCP", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y minimax-mcp", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "tts", "voice-cloning", "image-generation", "video-generation", "minimax", "multimodal" ], "use_cases": [ "Generate speech and clone voices from text using MiniMax TTS via AI agents", "Create images and videos from text prompts through MCP tool calls", "Add multimodal generation capabilities to Claude Desktop and Cursor workflows" ], "health": "active" }, { "id": "kyanitelabs-mcp-video", "name": "MCP Video (KyaniteLabs)", "description": "Guardrailed video editing MCP server powered by FFmpeg. Supports media analysis, subtitle generation, audio processing, effects, Hyperframes rendering, and repurposing tools. Local, fast, and free.", "category": "media", "endpoint": "uvx mcp-video", "homepage_url": "https://github.com/KyaniteLabs/mcp-video", "github_url": "https://github.com/KyaniteLabs/mcp-video", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx mcp-video", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "video", "ffmpeg", "editing", "audio", "subtitles", "media" ], "use_cases": [ "Edit and process video files locally via AI using FFmpeg under the hood", "Generate subtitles, apply effects, and convert media formats through Claude", "Repurpose video content with guardrailed AI-driven editing tools" ], "health": "active" }, { "id": "mcpauth", "name": "MCPAuth", "description": "Self-hostable OAuth 2.0 server built specifically for MCP servers. Provides flexible, developer-controlled authentication and authorization for securing MCP applications without depending on third-party auth providers.", "category": "identity", "endpoint": "https://github.com/mcpauth/mcpauth", "homepage_url": "https://github.com/mcpauth/mcpauth", "github_url": "https://github.com/mcpauth/mcpauth", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "npx -y mcpauth", "added": "2026-06-23", "updated": "2026-06-23", "tags": [ "oauth", "auth", "authentication", "security", "identity", "self-hosted" ], "use_cases": [ "Add self-hosted OAuth 2.0 authentication to any MCP server deployment", "Secure MCP applications without relying on third-party auth providers", "Implement developer-controlled access control for MCP tool ecosystems" ], "health": "active" }, { "id": "basecamp-mcp-server", "name": "Basecamp MCP Server", "description": "MCP server for Basecamp 3 with OAuth, FastMCP, and 79 tools for projects, todos, messages, card tables, docs, uploads, campfires, webhooks, and search. Works with Codex, Cursor, and Claude Desktop.", "category": "productivity", "endpoint": "python basecamp_fastmcp.py", "homepage_url": "https://github.com/georgeantonopoulos/Basecamp-MCP-Server", "github_url": "https://github.com/georgeantonopoulos/Basecamp-MCP-Server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/georgeantonopoulos/Basecamp-MCP-Server.git && cd Basecamp-MCP-Server && pip install -r requirements.txt", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "basecamp", "project-management", "productivity", "todos", "oauth", "fastmcp" ], "use_cases": [ "Manage Basecamp projects, todos, messages, and card tables via AI agents", "Search across projects, campfires, and documents with natural language", "Create and manage documents, uploads, and webhooks through Claude or Cursor" ], "health": "active" }, { "id": "gpt2agent-mcp", "name": "GPT2Agent", "description": "Integrate a full ChatGPT Plus/Pro account into Claude Code, Codex, Cursor, and other MCP clients. Access all OpenAI models and features through the Model Context Protocol.", "category": "ai", "endpoint": "npx -y gpt2agent", "homepage_url": "https://github.com/robotlearning123/gpt2agent", "github_url": "https://github.com/robotlearning123/gpt2agent", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y gpt2agent", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "chatgpt", "openai", "gpt", "multi-model", "ai-integration" ], "use_cases": [ "Access ChatGPT Plus/Pro models from within Claude Code or Cursor via MCP", "Use OpenAI models as a second opinion or specialized tool inside MCP workflows", "Bridge OpenAI capabilities into any MCP-compatible AI coding assistant" ], "health": "active" }, { "id": "predactiv-mcp", "name": "Predactiv MCP", "description": "Predactiv MCP server and Platform API for audience intelligence. Enables AI agents to access demographic, firmographic, and behavioral audience data directly within coding and analytics workflows.", "category": "data", "endpoint": "https://predactiv.com", "homepage_url": "https://predactiv.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "audience-intelligence", "data-platform", "analytics", "demographics", "marketing" ], "use_cases": [ "Access audience intelligence data directly within AI-powered analytics workflows", "Query demographic and firmographic data for market research via MCP", "Integrate Predactiv audience insights into agent-driven marketing pipelines" ], "health": "active" }, { "id": "courtroom-insight-mcp", "name": "Courtroom Insight MCP", "description": "MCP server for legal professional intelligence. Surface verified data on lawyers, judges, expert witnesses, and arbitrators through AI tools. Provides clean, structured legal intelligence for law firms.", "category": "data", "endpoint": "https://www.courtroominsight.com", "homepage_url": "https://www.courtroominsight.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "legal", "lawyers", "judges", "litigation", "legal-intelligence", "law" ], "use_cases": [ "Surface verified intelligence on lawyers, judges, and expert witnesses via AI", "Integrate legal professional data into AI-powered litigation research workflows", "Access structured courtroom data through MCP-compatible AI tools" ], "health": "active" }, { "id": "alpaca-mcp-server", "name": "Alpaca MCP Server", "description": "Official Alpaca MCP server for trading stocks, ETFs, crypto, and options. Run data analysis, build strategies, and execute trades in plain English from Claude Code, Cursor, or any MCP client.", "category": "payments", "endpoint": "npx -y @alpacahq/alpaca-mcp-server", "homepage_url": "https://github.com/alpacahq/alpaca-mcp-server", "github_url": "https://github.com/alpacahq/alpaca-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @alpacahq/alpaca-mcp-server", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "trading", "stocks", "crypto", "options", "finance", "alpaca" ], "use_cases": [ "Trade stocks, ETFs, crypto, and options via natural language through AI agents", "Run portfolio data analysis and build trading strategies from Claude or Cursor", "Execute and monitor trades with prompt-injection-resistant trust boundary envelopes" ], "health": "active" }, { "id": "ibm-context-forge", "name": "IBM MCP Context Forge", "description": "IBM's MCP server for intelligent context management. Provides Rust-based server with security-hardened build pipeline, supporting context windowing and retrieval for enterprise AI agent workflows.", "category": "code", "endpoint": "https://github.com/IBM/mcp-context-forge", "homepage_url": "https://github.com/IBM/mcp-context-forge", "github_url": "https://github.com/IBM/mcp-context-forge", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "cargo install mcp-context-forge", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "ibm", "context", "rust", "enterprise", "security", "agent-memory" ], "use_cases": [ "Manage and retrieve structured context for enterprise AI agent workflows", "Run a security-hardened Rust-based MCP server for context windowing", "Integrate IBM context management into Claude Code or Cursor pipelines" ], "health": "active" }, { "id": "graphpilot-mcp", "name": "GraphPilot", "description": "Structural memory MCP server for coding agents. Indexes TypeScript and JavaScript repositories to enable efficient querying of symbols, callers, and call-edges, giving agents deep codebase understanding.", "category": "code", "endpoint": "npx -y graphpilot", "homepage_url": "https://github.com/graphpilot-oss/graphpilot", "github_url": "https://github.com/graphpilot-oss/graphpilot", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y graphpilot", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "code-graph", "typescript", "javascript", "symbols", "call-graph", "agent-memory" ], "use_cases": [ "Give coding agents structural understanding of TypeScript/JavaScript codebases", "Query symbol definitions, callers, and call-edges across repositories", "Enable AI agents to make safer refactoring decisions with dependency awareness" ], "health": "active" }, { "id": "codeindex-mcp", "name": "Codeindex", "description": "Repo dependency analyzer with blast-radius impact scoring for AI-assisted development. Provides dependency graphs, semantic symbol search, and impact analysis to help coding agents understand change risk.", "category": "code", "endpoint": "uvx codeindex", "homepage_url": "https://github.com/scheidydude/codeindex", "github_url": "https://github.com/scheidydude/codeindex", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx codeindex", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "static-analysis", "dependency-graph", "blast-radius", "code-quality", "impact-scoring" ], "use_cases": [ "Analyze repository dependencies and blast-radius impact before making changes", "Search symbols semantically across a codebase for AI-assisted development", "Score the risk of code changes with dependency graph analysis" ], "health": "active" }, { "id": "ha-mcp", "name": "Home Assistant MCP", "description": "Unofficial MCP server for Home Assistant smart home control. Lets AI assistants interact with Home Assistant to manage devices, automations, scenes, and monitor sensor data through natural language.", "category": "infrastructure", "endpoint": "npx -y ha-mcp", "homepage_url": "https://github.com/homeassistant-ai/ha-mcp", "github_url": "https://github.com/homeassistant-ai/ha-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y ha-mcp", "added": "2026-06-24", "updated": "2026-06-24", "tags": [ "home-assistant", "smart-home", "iot", "automation", "devices", "sensors" ], "use_cases": [ "Control smart home devices and automations via AI assistants through MCP", "Monitor Home Assistant sensor data and trigger scenes with natural language", "Integrate smart home management into Claude Desktop or other MCP clients" ], "health": "active" }, { "id": "jcodemunch-mcp", "name": "jCodeMunch", "description": "Token-efficient MCP server for precise GitHub code retrieval via tree-sitter AST parsing. Reduces AI token costs 95%+ on code exploration by extracting symbol-level code instead of reading entire files. Supports 70+ languages.", "category": "code", "endpoint": "uvx jcodemunch-mcp", "homepage_url": "https://github.com/jgravelle/jcodemunch-mcp", "github_url": "https://github.com/jgravelle/jcodemunch-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install jcodemunch-mcp", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "code", "token-efficiency", "tree-sitter", "ast", "github", "code-retrieval" ], "use_cases": [ "Retrieve precise symbol-level code from GitHub repos without reading entire files", "Reduce AI agent token costs by 95%+ during code exploration tasks", "Index and query codebases across 70+ languages with structured AST parsing" ], "health": "active" }, { "id": "reddit-devvit-mcp", "name": "Reddit Devvit MCP", "description": "Official Reddit MCP server for writing Devvit applications on Reddit's developer platform. Provides tools for building Reddit apps, bots, and extensions with AI-assisted development via Claude Code, Cursor, or any MCP client.", "category": "code", "endpoint": "npx -y @devvit/mcp", "homepage_url": "https://github.com/reddit/devvit-mcp", "github_url": "https://github.com/reddit/devvit-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @devvit/mcp", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "reddit", "devvit", "social-media", "apps", "bots", "community" ], "use_cases": [ "Build Reddit apps, bots, and community extensions with AI-assisted development", "Scaffold and iterate on Devvit applications from Claude Code or Cursor", "Access Reddit developer platform documentation and APIs through MCP tools" ], "health": "active" }, { "id": "mcp-steroid", "name": "MCP Steroid", "description": "Open-source MCP server that runs inside JetBrains IDEs (IntelliJ, WebStorm, PyCharm, etc.) and exposes the full power of the IntelliJ Platform to AI agents. Provides visual IDE understanding, UI automation, and native IntelliJ APIs via Kotlin scripting.", "category": "code", "endpoint": "JetBrains plugin", "homepage_url": "https://github.com/jonnyzzz/mcp-steroid", "github_url": "https://github.com/jonnyzzz/mcp-steroid", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "Install via JetBrains plugin repository: https://mcp-steroid.jonnyzzz.com/updatePlugins.xml", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "jetbrains", "intellij", "ide", "kotlin", "ui-automation", "webstorm", "pycharm" ], "use_cases": [ "Give AI agents full access to JetBrains IDE features including refactoring, inspections, and navigation", "Automate IDE UI interactions and run Kotlin scripts through MCP tools", "Bridge AI coding assistants with IntelliJ Platform APIs for deep IDE integration" ], "health": "active" }, { "id": "meta-vr-cli-mcp", "name": "Meta VR CLI MCP", "description": "Official Meta MCP server connecting AI assistants to Meta Quest development tools. Provides documentation search, device debugging, performance trace analysis via Perfetto, screenshot capture, and access to Meta's 3D asset library.", "category": "code", "endpoint": "npx -y metavr mcp server", "homepage_url": "https://developers.meta.com/horizon/essentials/ai-tooling-mcp/", "github_url": "https://github.com/meta-quest/agentic-tools", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y metavr mcp server", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "meta", "quest", "vr", "xr", "3d-assets", "perfetto", "device-debugging" ], "use_cases": [ "Search Meta Horizon OS documentation and fetch page content for VR development", "Debug Meta Quest devices via ADB logcat, screenshots, and performance trace analysis", "Search and download 3D models from Meta's asset library for VR/MR applications" ], "health": "active" }, { "id": "sendoso-mcp", "name": "Sendoso MCP", "description": "Sendoso's MCP server for AI-powered personalized gifting and direct mail. Enables AI agents to send personalized gifts, eGifts, and direct mail based on intent signals. Works with Claude, ChatGPT, Salesforce Agentforce, and other MCP clients.", "category": "communication", "endpoint": "https://www.sendoso.com/platform/features/mcp", "homepage_url": "https://www.sendoso.com/platform/features/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "gifting", "direct-mail", "sales", "marketing", "personalization", "outreach" ], "use_cases": [ "Send personalized gifts and direct mail to prospects and customers via AI agents", "Automate gifting campaigns triggered by intent signals from CRM or engagement data", "Integrate physical gifting into AI-powered sales and marketing workflows" ], "health": "active" }, { "id": "infragistics-ignite-ui-mcp", "name": "Infragistics Ignite UI MCP", "description": "Enterprise MCP toolchain from Infragistics connecting AI coding assistants to the Ignite UI component library. Includes CLI MCP Server for scaffolding and docs, plus Theming MCP Server for palettes, typography, and design tokens across Angular, React, Blazor, and Web Components.", "category": "code", "endpoint": "Ignite UI CLI MCP Server", "homepage_url": "https://www.infragistics.com/ai-assisted-app-development", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm install -g igniteui-cli && ig ai-config", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "infragistics", "ignite-ui", "angular", "react", "blazor", "web-components", "ui-components", "theming", "enterprise" ], "use_cases": [ "Scaffold Ignite UI projects and generate components with AI-assisted code generation", "Search Ignite UI component docs and API references directly from Claude Code or Cursor", "Generate enterprise theming code including palettes, typography, and design tokens" ], "health": "active" }, { "id": "org-mcp", "name": "Org-mode MCP", "description": "Emacs Org-mode MCP server enabling AI assistants to interact with Org files through structured tools. Read file content, inspect hierarchical structure, update TODO states, and add new tasks. Available via MELPA.", "category": "productivity", "endpoint": "org-mcp (Emacs package)", "homepage_url": "https://github.com/laurynas-biveinis/org-mcp", "github_url": "https://github.com/laurynas-biveinis/org-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "M-x package-install RET org-mcp RET", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "emacs", "org-mode", "productivity", "task-management", "notes", "melpa" ], "use_cases": [ "Read and navigate Org-mode file hierarchies through AI assistants", "Update TODO states and add new tasks in Org files via MCP tools", "Integrate Emacs Org-mode workflows with AI coding assistants" ], "health": "active" }, { "id": "iobroker-mcp", "name": "ioBroker MCP", "description": "Official ioBroker MCP server adapter for smart home automation. Exposes ioBroker installations to MCP-capable AI clients via Streamable HTTP transport, enabling reading and controlling smart home devices, running diagnostics, and searching adapter repositories.", "category": "infrastructure", "endpoint": "ioBroker adapter", "homepage_url": "https://github.com/ioBroker/ioBroker.mcp", "github_url": "https://github.com/ioBroker/ioBroker.mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "Install via ioBroker admin interface", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "iobroker", "smart-home", "iot", "home-automation", "devices", "diagnostics" ], "use_cases": [ "Read and control smart home devices through AI assistants via MCP protocol", "Run network diagnostics and troubleshoot adapter connections in ioBroker", "Search and recommend installable adapters for ioBroker smart home setups" ], "health": "active" }, { "id": "fluree-mcp", "name": "Fluree MCP", "description": "MCP server for Fluree's verifiable knowledge graph database. Enables AI agents to query and interact with RDF-based knowledge graphs using SPARQL, supporting GraphRAG-powered accuracy for enterprise AI workflows with data provenance and trust.", "category": "data", "endpoint": "https://flur.ee/", "homepage_url": "https://flur.ee/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-25", "updated": "2026-06-25", "tags": [ "fluree", "knowledge-graph", "rdf", "sparql", "graphrag", "enterprise", "data-provenance" ], "use_cases": [ "Query RDF knowledge graphs with SPARQL through AI agents for enterprise data access", "Build GraphRAG pipelines with verifiable, provenance-tracked data from Fluree", "Connect AI workflows to structured knowledge graphs for accurate, grounded responses" ], "health": "active" }, { "id": "autodesk-revit-mcp", "name": "Autodesk Revit MCP", "description": "Official Autodesk MCP server for Revit 2027 providing read-only BIM model access to AI assistants. Query elements by category, family, level, and parameters, retrieve detailed element data, select and zoom to elements, open views, and export views to images or CSV. Ships as a Revit 2027 addon with auto-configuration for Claude Desktop and Cursor.", "category": "code", "endpoint": "RevitMCPServer.exe (Revit addon)", "homepage_url": "https://www.autodesk.com/blogs/aec/2026/06/17/revit-public-mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "Download from Autodesk Account under Revit 2027 Extensions", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "autodesk", "revit", "bim", "architecture", "aec", "construction", "3d-models", "building-design" ], "use_cases": [ "Query Revit BIM models by category, family, type, level, and parameter values via AI assistants", "Retrieve detailed element data including geometry, parameters, and bounding boxes for analysis", "Export views to images, PDFs, or CSV schedules as part of AI-driven documentation workflows" ], "health": "active" }, { "id": "lili-mcp", "name": "Lili MCP", "description": "MCP server from Lili connecting AI assistants to real-time business banking data for accountants. Enables portfolio-wide client monitoring, transaction analysis, tax position calculations, cash flow forecasting, and automated advisory workflows across multiple client accounts. Uses OAuth 2.0 with existing accountant permissions.", "category": "data", "endpoint": "https://lili.co/", "homepage_url": "https://lili.co/blog/your-ai-assistant-can-now-talk-to-your-clients-bank-accounts", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "banking", "fintech", "accounting", "small-business", "tax", "cash-flow", "financial-data" ], "use_cases": [ "Sweep an accountant's entire client book to surface who needs attention based on real-time banking data", "Calculate tax positions, model cash flow scenarios, and flag duplicate charges across client portfolios", "Automate recurring financial monitoring workflows with AI-generated client advisory drafts" ], "health": "active" }, { "id": "pinterest-ads-mcp", "name": "Pinterest Ads MCP", "description": "Official Pinterest MCP server providing read-only access to advertising campaign data for AI agents. Enables AI-native campaign analysis workflows, letting agents query live Pinterest ad performance metrics, audience insights, and campaign structure. Launched alongside Microsoft Advertising MCP as part of the growing ad platform MCP ecosystem.", "category": "data", "endpoint": "Pinterest Ads API MCP", "homepage_url": "https://www.digitalapplied.com/blog/advertising-mcp-servers-pinterest-microsoft-2026-guide", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "pinterest", "advertising", "ads", "marketing", "campaigns", "analytics", "social-media" ], "use_cases": [ "Query live Pinterest ad campaign performance data through AI assistants for automated reporting", "Analyze audience insights and campaign structure across Pinterest advertising accounts", "Build AI-native advertising workflows that pull real-time metrics from Pinterest's 631M MAU platform" ], "health": "active" }, { "id": "contentsquare-mcp", "name": "Contentsquare MCP", "description": "MCP server from Contentsquare providing AI agents with real-time access to behavioral analytics and digital experience data. Surfaces funnel conversion rates, friction scores, session replays, error monitoring, and revenue impact analysis. Works with Claude, ChatGPT, Copilot, and Dust AI agents for cross-functional UX optimization.", "category": "data", "endpoint": "https://contentsquare.com/platform/capabilities/mcp-server/", "homepage_url": "https://contentsquare.com/platform/capabilities/mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "analytics", "ux", "behavioral-data", "digital-experience", "funnel-analysis", "session-replay", "conversion" ], "use_cases": [ "Surface funnel conversion rates, friction scores, and revenue impact data through AI assistants", "Connect behavioral analytics to Dust AI agents for automated cross-functional UX insights", "Diagnose user experience issues by querying session replay and error monitoring data via MCP" ], "health": "active" }, { "id": "snaplogic-mcp", "name": "SnapLogic MCP", "description": "Enterprise integration platform MCP server from SnapLogic enabling teams to expose existing integrations, data flows, and workflows as MCP servers. Includes a MCP Server Pipeline Builder that walks through creating a functional MCP server pipeline in steps, allowing any SnapLogic integration to become AI-agent accessible.", "category": "infrastructure", "endpoint": "SnapLogic platform", "homepage_url": "https://www.snaplogic.com/blog/june-2026-product-release", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "integration", "ipaas", "workflow", "enterprise", "data-pipeline", "automation", "etl" ], "use_cases": [ "Expose existing SnapLogic integrations and data flows as MCP servers for AI agent consumption", "Build MCP server pipelines in minutes using the guided Pipeline Builder without custom code", "Connect enterprise data sources and SaaS applications to AI agents through standardized MCP protocol" ], "health": "active" }, { "id": "clickstack-mcp", "name": "ClickStack MCP (Managed)", "description": "Managed cloud MCP server from ClickHouse bringing ClickStack observability investigation capabilities to external AI agents. Enables Claude, Cursor, and Codex to query observability data, run diagnostic investigations, and analyze performance traces directly through the ClickHouse Cloud platform without local server setup.", "category": "infrastructure", "endpoint": "ClickHouse Cloud managed", "homepage_url": "https://clickhouse.com/blog/announcing-managed-clickstack-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "clickhouse", "observability", "monitoring", "diagnostics", "performance", "cloud", "traces" ], "use_cases": [ "Query ClickStack observability data through AI agents for automated incident investigation", "Run diagnostic analysis and performance trace queries via Claude, Cursor, or Codex", "Connect AI coding assistants to managed cloud observability without local MCP server setup" ], "health": "active" }, { "id": "flagsmith-mcp", "name": "Flagsmith MCP", "description": "Open-source MCP server from Flagsmith for feature flag and remote configuration management. Enables AI agents and coding assistants to query, toggle, and manage feature flags across environments. Installable locally with one click or deployable remotely for SaaS, private cloud, or self-hosted Flagsmith instances.", "category": "code", "endpoint": "Flagsmith MCP server", "homepage_url": "https://www.flagsmith.com/blog/flagsmith-mcp-server", "github_url": "https://github.com/Flagsmith/flagsmith-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx flagsmith-mcp-server", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "feature-flags", "remote-config", "release-management", "devops", "toggles", "experimentation" ], "use_cases": [ "Query and manage feature flags across environments through AI coding assistants", "Toggle feature flags and update remote configuration via natural language commands", "Integrate feature flag management into AI-driven release and deployment workflows" ], "health": "active" }, { "id": "moneris-mcp", "name": "Moneris MCP", "description": "Official MCP server from Moneris, Canada's leading payment processor, enabling AI agents to securely interact with Moneris APIs and commerce capabilities. Provides a standardized integration layer for agentic commerce, allowing AI-driven payment experiences while preserving existing fraud prevention and security controls. One of Canada's first domestically built AI-payment platforms.", "category": "payments", "endpoint": "https://developer.moneris.com/moneris-api/docs/model-context-protocol-mcp", "homepage_url": "https://www.moneris.com/en/media-room/news/moneris-launches-model-context-protocol-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-26", "updated": "2026-06-26", "tags": [ "payments", "commerce", "canada", "fintech", "agentic-commerce", "pos", "checkout" ], "use_cases": [ "Connect AI agents to Moneris payment APIs for secure, AI-driven commerce transactions", "Build once and scale payment-enabled AI experiences across multiple AI ecosystems via MCP", "Enable agentic commerce workflows with enterprise-grade security and existing fraud controls" ], "health": "active" }, { "id": "lucidlink-mcp", "name": "LucidLink MCP", "description": "MCP server from LucidLink exposing its distributed streaming file system to AI agents. Gives multi-agent systems a persistent, writable file layer with shared state across clouds, on-premises, and edge environments. Supports block-level streaming, global file locking, and zero-knowledge AES-256 encryption so agents, applications, and humans work from the same files without copying or moving data.", "category": "infrastructure", "endpoint": "LucidLink filespace MCP", "homepage_url": "https://siliconangle.com/2026/06/25/exclusive-lucidlink-launches-mcp-server-give-ai-agents-shared-access-distributed-files/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "file-system", "distributed-storage", "cloud-storage", "multi-agent", "collaboration", "nas", "object-storage" ], "use_cases": [ "Give multi-agent workflows a persistent shared file layer across cloud, on-prem, and edge environments", "Enable agents to read and write large files with global locking to prevent concurrent write conflicts", "Preserve context, outputs, and working state across agent sessions without moving or duplicating data" ], "health": "active" }, { "id": "br-automation-mcp", "name": "B&R Automation MCP", "description": "Official MCP server from B&R (ABB group) providing AI assistants with direct access to B&R automation knowledge and community data. Integrates with Automation Studio Code 6.7 using JWT authentication, enabling AI tools like GitHub Copilot and Continue Dev to work with industrial automation context.", "category": "code", "endpoint": "B&R MCP Server", "homepage_url": "https://community.br-automation.com/t/news-official-b-r-mcp-sever-was-released/11707", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "industrial-automation", "plc", "abb", "manufacturing", "iot", "automation-studio", "ot" ], "use_cases": [ "Access B&R automation knowledge and documentation directly from AI coding assistants", "Integrate industrial automation context into GitHub Copilot and Continue Dev via JWT from AS Code 6.7", "Query B&R Community data and automation best practices through AI assistant workflows" ], "health": "active" }, { "id": "owncloud-ocis-mcp", "name": "ownCloud oCIS MCP", "description": "Open-source MCP server exposing ownCloud Infinite Scale as 80 tools across users, spaces, files, shares, search, notifications, federated OCM sharing, and multi-step workflows. Apache 2.0 licensed Go binary. Supports OIDC and app token auth. Designed for sovereign file infrastructure where AI operates on your authentication against your data without it leaving your server.", "category": "productivity", "endpoint": "ownCloud oCIS MCP Server", "homepage_url": "https://owncloud.com/blogs/ocis-mcp-server-v1-0-0-your-ai-assistant-just-got-a-key-to-owncloud/", "github_url": "https://github.com/owncloud/ocis-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/owncloud/ocis-mcp-server && cd ocis-mcp-server && make build", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "file-management", "self-hosted", "sovereign", "open-source", "collaboration", "webdav", "federated-sharing" ], "use_cases": [ "Manage users, spaces, files, and shares in ownCloud Infinite Scale through AI assistants via 80 tools", "Run federated Open Cloud Mesh sharing operations and multi-step file workflows through natural language", "Deploy sovereign AI file management where data never leaves your infrastructure using local models like Ollama" ], "health": "active" }, { "id": "invintory-mcp", "name": "InVintory MCP", "description": "MCP server from InVintory connecting wine cellar and collection data to AI assistants including Claude, ChatGPT, and Gemini. Enables natural language queries against your actual wine inventory for pairing recommendations, drinking window analysis, collection valuation, and gap analysis. OAuth-secured, available on all paid InVintory plans.", "category": "data", "endpoint": "https://api.invintory.com/mcp", "homepage_url": "https://invintory.com/blog/invintory-mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "wine", "cellar-management", "inventory", "lifestyle", "consumer", "sommelier", "collection" ], "use_cases": [ "Query your actual wine collection from Claude, ChatGPT, or Gemini for food pairing and drinking window recommendations", "Run portfolio-style gap analysis and valuation reports on wine holdings via natural language", "Integrate cellar data into home automation, financial planning, and hospitality workflows through MCP" ], "health": "active" }, { "id": "docebo-mcp", "name": "Docebo MCP", "description": "Enterprise MCP server from Docebo integrating its learning management system with AI assistants including ChatGPT, Claude, Copilot Studio, and Gemini Enterprise. Enables natural language interaction with courses, learner data, and training content without navigating the LMS. Supports custom server configurations with selectable tool sets and OAuth2 authentication.", "category": "productivity", "endpoint": "https://[instance].docebosaas.com/mcp/servers/[path]/http", "homepage_url": "https://developer.docebo.com/docs/configuring-the-docebo-mcp-server-beta", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "lms", "learning", "training", "education", "enterprise", "e-learning", "hr" ], "use_cases": [ "Query learner progress, course completion, and training data from enterprise AI assistants without opening the LMS", "Configure custom MCP server instances with specific tool sets for different organizational personas and use cases", "Connect Docebo learning data to ChatGPT, Claude, Copilot Studio, and Gemini Enterprise via OAuth2" ], "health": "active" }, { "id": "proofpilot-mcp", "name": "ProofPilot MCP", "description": "MCP connector from ProofPilot enabling enterprise AI tools to access clinical trial intelligence from the STUDY RAIDAR platform. Connects AI assistants to protocol analysis, enrollment forecasting, site performance data, and document intelligence for clinical operations. Supports natural language queries against study data and automated reporting workflows.", "category": "data", "endpoint": "ProofPilot STUDY RAIDAR MCP", "homepage_url": "https://www.prnewswire.com/news-releases/proofpilot-launches-study-raidar-and-new-model-context-protocol-mcp-for-the-next-generation-of-agentic-use-cases-302808364.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "clinical-trials", "healthcare", "pharma", "biotech", "enrollment", "protocol-analysis", "life-sciences" ], "use_cases": [ "Connect enterprise AI assistants to live clinical trial performance data for enrollment forecasting and site monitoring", "Query protocol risk scores, amendment likelihood, and operational benchmarks through natural language", "Surface cited answers from study documents for site staff during patient visits via AI assistant integration" ], "health": "active" }, { "id": "propel-plm-mcp", "name": "Propel PLM MCP", "description": "First production MCP server for product lifecycle management from Propel Software. Provides bidirectional connectivity: inbound lets Claude, ChatGPT, and Copilot query live product records inside Propel, while outbound lets Propel agents reach third-party MCP servers for supplier intelligence, component data, and ERP records from NetSuite and SAP.", "category": "data", "endpoint": "Propel PLM MCP", "homepage_url": "https://www.propelsoftware.com/products/propel-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "plm", "manufacturing", "product-lifecycle", "erp", "salesforce", "supply-chain", "engineering" ], "use_cases": [ "Query live product records, BOMs, and quality data from Claude, ChatGPT, or Copilot without logging into the PLM", "Build custom agents that connect Propel to third-party MCP servers for supplier risk and ERP data from NetSuite or SAP", "Enable bidirectional product data access between enterprise AI platforms and Propel's product value management system" ], "health": "active" }, { "id": "factset-portfolio-mcp", "name": "FactSet Portfolio Analytics MCP", "description": "MCP server from FactSet (NYSE: FDS) distributing pre-calculated, governed portfolio analytics into conversational and agentic AI workflows. Delivers performance, attribution, and risk outputs to buy-side investment professionals through natural language interfaces inside private LLM environments. Includes a semantic metadata layer that keeps AI queries anchored to audit-ready, book-of-record results.", "category": "data", "endpoint": "FactSet Portfolio Analytics MCP", "homepage_url": "https://www.factset.com/marketplace/catalog/product/portfolio-analytics-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "portfolio-analytics", "finance", "buy-side", "risk", "attribution", "investment", "financial-data" ], "use_cases": [ "Query governed performance, attribution, and risk analytics conversationally from private LLM environments", "Build proprietary AI agents on top of FactSet's portfolio analytics without custom data pipeline integrations", "Connect portfolio analytics to fundamental and quantitative research solutions through AI-native workflows" ], "health": "active" }, { "id": "prodoscore-mcp", "name": "Prodoscore MCP", "description": "MCP server from Prodoscore making workforce intelligence and employee productivity analytics available to enterprise AI assistants. Read-only connector that applies existing role-based permissions, works with Claude, ChatGPT, Gemini, and Copilot alongside Salesforce, Jira, Asana, HubSpot, and Slack data. Customer data is not used to train external AI models.", "category": "data", "endpoint": "Prodoscore MCP Server", "homepage_url": "https://telconews.com.au/story/prodoscore-launches-mcp-server-for-enterprise-ai-assistants", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-27", "updated": "2026-06-27", "tags": [ "workforce-analytics", "productivity", "employee-intelligence", "hr", "enterprise", "hybrid-work", "engagement" ], "use_cases": [ "Query workforce productivity patterns and employee engagement metrics from enterprise AI assistants alongside CRM and project data", "Compare sales performance with daily work patterns across distributed teams through natural language queries", "Identify software licence usage, team engagement trends, and workforce signals without dedicated dashboards" ], "health": "active" }, { "id": "cdata-connect-ai-mcp", "name": "CData Connect AI MCP", "description": "MCP server from CData Software providing governed, real-time access to enterprise data across 400+ sources including databases, SaaS applications, ERPs, and data warehouses. Free Developer Edition includes full enterprise feature set with per-user authentication passthrough, query logging, and user-level attribution. Python SDK and CLI included for building AI-native data pipelines.", "category": "data", "endpoint": "CData Connect AI MCP", "homepage_url": "https://www.cdata.com/connect-ai/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "data-access", "enterprise", "etl", "database", "saas-connectors", "governance", "sql" ], "use_cases": [ "Give AI agents governed, real-time access to 400+ enterprise data sources including databases, ERPs, and SaaS applications through a single MCP interface", "Build AI-native data pipelines with per-user authentication passthrough and query logging for audit trails", "Enable natural language queries against enterprise data with user-level attribution and governance controls" ], "health": "active" }, { "id": "geotab-mcp", "name": "Geotab MyGeotab MCP", "description": "Industry-first MCP connector from Geotab enabling organizations to securely access live fleet data through AI assistants. Connects MyGeotab telematics platform to ChatGPT, Claude, and enterprise AI tools for natural language queries against vehicle tracking, driver behavior, fuel usage, maintenance schedules, and compliance data across commercial fleets.", "category": "data", "endpoint": "Geotab MyGeotab MCP Connector", "homepage_url": "https://support.geotab.com/product-updates/release-notes/mygeotab-updates-june-2026", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "fleet-management", "telematics", "logistics", "vehicle-tracking", "iot", "transportation", "compliance" ], "use_cases": [ "Query live fleet telematics data including vehicle locations, driver behavior, and fuel usage through enterprise AI assistants", "Monitor maintenance schedules, compliance status, and fleet health metrics via natural language without opening the MyGeotab dashboard", "Build custom fleet intelligence workflows by connecting Geotab data to Claude, ChatGPT, or internal AI tools" ], "health": "active" }, { "id": "voipstudio-mcp", "name": "VoIPstudio MCP", "description": "MCP server from VoIPstudio connecting business VoIP and telephony data to AI assistants including Claude. Provides access to call records, voicemail transcriptions, call analytics, and communication workflows. Requires the CX Addon on any VoIPstudio account. Enables AI-driven call analysis, routing optimization, and customer experience insights.", "category": "communication", "endpoint": "VoIPstudio MCP Server", "homepage_url": "https://voipstudio.com/blog/voipstudio-launches-mcp-server-for-claude-or-other-ai-platforms/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "voip", "telephony", "call-analytics", "business-phone", "customer-experience", "ucaas", "communication" ], "use_cases": [ "Access call records, voicemail transcriptions, and call analytics from AI assistants for customer experience insights", "Optimize call routing and staffing decisions by querying VoIP communication patterns through natural language", "Automate call log analysis and generate communication reports from VoIPstudio data via Claude or other MCP clients" ], "health": "active" }, { "id": "daloopa-mcp", "name": "Daloopa MCP", "description": "MCP connector from Daloopa bringing trusted, machine-verified financial data directly into Microsoft 365 Copilot and other AI workflows. Surfaces earnings data, financial statements, KPIs, and company metrics from Daloopa's verified dataset. Designed for equity research analysts and portfolio managers who need accurate, auditable financial intelligence inside their AI tools.", "category": "data", "endpoint": "Daloopa MCP Connector", "homepage_url": "https://daloopa.com/blog/press-release/daloopa-microsoft-365-copilot-mcp-connector", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "financial-data", "equity-research", "finance", "earnings", "buy-side", "sell-side", "copilot" ], "use_cases": [ "Surface machine-verified earnings data, financial statements, and KPIs inside Microsoft 365 Copilot for equity research workflows", "Query auditable company financial metrics from AI assistants without switching to a separate terminal or data platform", "Build investment analysis workflows with trusted Daloopa data flowing into Claude, Copilot, or custom AI tools" ], "health": "active" }, { "id": "redox-mcp", "name": "Redox MCP", "description": "MCP server from Redox, the healthcare interoperability platform, enabling AI tools to access clinical and operational healthcare data through standardized integrations. Part of a broader AI launch including an AI Assistant Suite and intelligent in-flight data processing. Connects EHR, scheduling, billing, and patient data to AI workflows while maintaining HIPAA compliance and healthcare data governance.", "category": "data", "endpoint": "Redox MCP Server", "homepage_url": "https://www.prnewswire.com/news-releases/redox-launches-ai-capabilities-built-to-scale-integration-teams-and-serve-as-the-data-foundation-for-ai-in-healthcare-302807041.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "healthcare", "ehr", "hipaa", "interoperability", "clinical-data", "health-it", "fhir" ], "use_cases": [ "Connect AI assistants to EHR, scheduling, billing, and patient data through Redox's healthcare interoperability layer", "Build HIPAA-compliant AI workflows that process clinical and operational healthcare data with proper governance controls", "Scale healthcare integration teams by enabling AI tools to query and transform health data in-flight across partner systems" ], "health": "active" }, { "id": "beyond-pricing-mcp", "name": "Beyond Revenue Management MCP", "description": "MCP server from Beyond (formerly Beyond Pricing) connecting live vacation rental and property management data to AI assistants. Enables AI tools like Claude, ChatGPT, and custom enterprise agents to access pricing intelligence, market analytics, occupancy data, and revenue optimization insights for short-term rental portfolios.", "category": "data", "endpoint": "Beyond MCP Server", "homepage_url": "https://www.prnewswire.com/news-releases/beyond-announces-ai-innovations-to-empower-property-managers--grow-revenue-302806901.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "property-management", "vacation-rental", "revenue-management", "pricing", "hospitality", "airbnb", "str" ], "use_cases": [ "Query live pricing intelligence and market analytics for vacation rental portfolios from AI assistants", "Monitor occupancy rates, revenue performance, and competitive positioning across short-term rental properties via natural language", "Connect Beyond revenue optimization data to custom enterprise agents for automated pricing strategy recommendations" ], "health": "active" }, { "id": "bandwidth-mcp", "name": "Bandwidth Build MCP", "description": "MCP server from Bandwidth (NYSE: BAND) giving AI agents autonomous access to the Bandwidth Communications Cloud. Once authenticated, agents can provision phone numbers, manage messaging services, configure voice routing, and automate telecom workflows through Bandwidth APIs. Part of the Bandwidth Build platform for AI-native communications.", "category": "communication", "endpoint": "Bandwidth Build MCP Server", "homepage_url": "https://www.prnewswire.com/news-releases/bandwidth-launches-build-giving-ai-agents-autonomous-access-to-the-bandwidth-communications-cloud-302807039.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "telecom", "cpaas", "voice", "messaging", "sms", "phone-numbers", "communications" ], "use_cases": [ "Give AI agents autonomous access to provision phone numbers, configure voice routing, and manage messaging services via Bandwidth APIs", "Automate telecom infrastructure workflows including number porting, call routing, and SMS campaign setup through natural language", "Build AI-native communications applications by connecting agents to Bandwidth's enterprise-grade voice and messaging cloud" ], "health": "active" }, { "id": "displayce-dooh-mcp", "name": "Displayce DOOH MCP", "description": "Suite of three MCP-accessible AI agents from Displayce for digital out-of-home advertising. Transforms DOOH campaign workflows from brief to post-campaign analysis. First agent converts natural language briefs into actionable media plans with programmatically available screen selections. Second agent generates editable sales presentations from audience and screen data. Third agent produces narrative performance reports. Backed by 10+ years of programmatic DOOH data across 2M+ screens in 80 countries. JCDecaux majority-owned.", "category": "media", "endpoint": "Displayce DOOH MCP", "homepage_url": "https://www.displayce.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "dooh", "digital-out-of-home", "advertising", "programmatic", "media-planning", "cannes-lions", "adtech" ], "use_cases": [ "Transform a natural language campaign brief into an actionable DOOH media plan with screen selections, budgets, and audience targeting in minutes", "Generate editable sales presentations from audience and screen data for agency pitch decks and campaign proposals", "Produce narrative post-campaign performance reports that translate DOOH results into insights for advertisers" ], "health": "active" }, { "id": "equixly-mcp", "name": "Equixly MCP", "description": "MCP integration from Equixly bringing continuous offensive API security testing directly into AI coding assistants. Enables developers to run automated penetration tests against APIs from within their IDE, get real-time vulnerability findings, and remediate security issues during development rather than post-deployment.", "category": "code", "endpoint": "Equixly MCP", "homepage_url": "https://equixly.com/blog/2026/06/25/equixly-june-2026-product-update/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-28", "updated": "2026-06-28", "tags": [ "api-security", "penetration-testing", "offensive-security", "devsecops", "vulnerability-scanning", "appsec" ], "use_cases": [ "Run continuous offensive security tests against APIs directly from AI coding assistants during development", "Identify and remediate API vulnerabilities in real-time within IDE workflows before deployment", "Automate penetration testing of REST and GraphQL APIs through natural language commands in Claude or Copilot" ], "health": "active" }, { "id": "esphome-mcp", "name": "ESPHome MCP", "description": "MCP server for ESPHome providing AI assistants with direct access to ESPHome device management and the new Device Builder functionality introduced in ESPHome 2026.6. Enables creating, editing, and managing ESPHome device configurations through natural language. Built for the Home Assistant ecosystem, supports the latest ESPHome API methods.", "category": "infrastructure", "endpoint": "ESPHome MCP", "homepage_url": "https://esphome.io", "github_url": "https://github.com/loryanstrant/ESPHome-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "esphome", "home-assistant", "iot", "smart-home", "device-builder", "embedded", "esp32" ], "use_cases": [ "Create and manage ESPHome device configurations through AI assistants using the new Device Builder API", "Interact with ESPHome sensors, switches, and automations directly from Claude Code or Cursor", "Generate ESPHome YAML configurations for ESP32/ESP8266 devices via natural language" ], "health": "active" }, { "id": "coocon-data-hub-mcp", "name": "COOCON Data Hub MCP", "description": "MCP server platform from COOCON (KOSDAQ: 294570), a South Korean business data platform company with 20+ years of data connectivity expertise across finance, public sector, logistics, and telecommunications. Transforms existing financial and public data APIs into MCP-native format so AI agents can query and utilize external data directly. Member of the Linux Foundation AAIF consortium alongside Anthropic, OpenAI, Google, Microsoft, and Stripe. Launching 30+ MCP products in July 2026, expanding to 100+ by year-end.", "category": "data", "endpoint": "https://coocon.net", "homepage_url": "https://www.coocon.net/en_corp.act", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "fintech", "data-platform", "financial-data", "public-data", "korea", "enterprise", "aaif" ], "use_cases": [ "Give AI agents direct access to Korean financial, public sector, logistics, and telecom data through standardized MCP interfaces", "Enable AI-driven workflow automation with real-time financial data feeds without manual API integration", "Build agent-to-agent data pipelines using MCP-native data products from a certified Korean data platform" ], "health": "active" }, { "id": "debugbear-mcp", "name": "DebugBear MCP", "description": "MCP server from DebugBear providing AI assistants with access to web performance monitoring and testing capabilities. Create projects, configure page monitoring, run performance tests, analyze Core Web Vitals, and automate bulk changes. Supports the same functionality as the existing DebugBear API. Works with Claude, ChatGPT, Gemini, and Cursor.", "category": "web", "endpoint": "DebugBear MCP", "homepage_url": "https://www.debugbear.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "web-performance", "core-web-vitals", "monitoring", "lighthouse", "rum", "page-speed" ], "use_cases": [ "Run web performance tests and analyze Core Web Vitals through AI assistants without leaving the IDE", "Automate bulk monitoring configuration changes across hundreds of pages using natural language", "Investigate page speed regressions by querying DebugBear project data conversationally" ], "health": "active" }, { "id": "sas-viya-mcp", "name": "SAS Viya MCP", "description": "Official MCP server from SAS Institute for SAS Viya environments. Provides 40+ tools for executing SAS code, training AutoML projects, scoring models, managing data, and much more. Supports SAS program execution, CAS table management, ML pipeline operations, and compute session management. Built in Python with comprehensive tool coverage across the SAS Viya analytics platform.", "category": "ai", "endpoint": "SAS Viya MCP Server", "homepage_url": "https://www.sas.com/en_us/software/viya.html", "github_url": "https://github.com/sassoftware/sas-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "sas", "analytics", "automl", "machine-learning", "data-science", "enterprise", "statistical-computing" ], "use_cases": [ "Execute SAS programs and manage CAS analytical tables through AI coding assistants", "Train and score AutoML models on SAS Viya directly from Claude or Cursor using natural language", "Build end-to-end ML pipelines combining SAS analytics with AI-assisted data exploration" ], "health": "active" }, { "id": "smartbear-mcp", "name": "SmartBear MCP", "description": "Official MCP server from SmartBear exposing their suite of API development and testing tools to AI assistants. Provides access to SwaggerHub for API design and documentation, ReadyAPI for functional and load testing, and other SmartBear products. Enables AI agents to search API definitions, run test suites, analyze results, and manage API lifecycle workflows through standardized MCP tools.", "category": "code", "endpoint": "SmartBear MCP Server", "homepage_url": "https://smartbear.com", "github_url": "https://github.com/SmartBear/smartbear-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "api-testing", "swagger", "openapi", "test-automation", "api-design", "quality-assurance", "devtools" ], "use_cases": [ "Search and explore SwaggerHub API definitions directly from AI coding assistants for faster integration work", "Run ReadyAPI test suites and analyze results through natural language commands in Claude or Cursor", "Manage the full API lifecycle from design to testing using AI-assisted SmartBear workflows" ], "health": "active" }, { "id": "mcp4acumatica", "name": "MCP4Acumatica", "description": "Open-source remote MCP server connecting AI assistants to Acumatica ERP through the contract-based REST API and OData. Runs on Cloudflare Workers with per-user credential authentication. Ships 38+ read-only entity lookups plus Generic Inquiry, schema-discovery, and utility tools. Features sensitive field redaction, call logging, opt-in GI exposure gates, and parameterized query safety. Apache-2.0 licensed.", "category": "data", "endpoint": "MCP4Acumatica (Cloudflare Workers)", "homepage_url": "https://community.acumatica.com/develop-customizations-288/mcp4acumatica-open-source-mcp-server-update-36242", "github_url": "https://github.com/hallboys/MCP4Acumatica", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "erp", "acumatica", "accounting", "enterprise", "odata", "cloudflare-workers", "open-source" ], "use_cases": [ "Query Acumatica ERP entities like customers, invoices, and inventory through AI assistants with per-user auth", "Run Generic Inquiries against Acumatica data with parameterized safety and opt-in exposure controls", "Discover and explore Acumatica entity schemas and field definitions from AI coding tools" ], "health": "active" }, { "id": "gramps-web-mcp", "name": "Gramps Web MCP", "description": "MCP server for Gramps Web genealogy platform, written in .NET 8. Provides AI agents with structured, tool-based access to family tree data through the official Gramps Web API. Supports CRUD operations for people, families, events, places, sources, citations, notes, media, repositories, and tags. Includes kinship-oriented tools for ancestors, descendants, relationships, and timelines. Features local-first deployment for privacy of sensitive genealogy data. Supports stdio, Streamable HTTP, and SSE transports with optional read-only mode.", "category": "data", "endpoint": "Gramps Web MCP", "homepage_url": "https://gramps-project.org", "github_url": "https://github.com/Scormave/gramps-web-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "genealogy", "family-tree", "gramps", "dotnet", "local-first", "privacy", "open-source" ], "use_cases": [ "Explore family trees through natural language queries for ancestors, descendants, and relationship paths", "Create and update genealogy records including people, events, sources, and citations from AI assistants", "Run kinship analysis and generate family timelines using AI-powered genealogy research workflows" ], "health": "active" }, { "id": "zoho-analytics-mcp", "name": "Zoho Analytics MCP", "description": "MCP server from Zoho enabling AI agents and assistants to work with Zoho Analytics business intelligence platform. Available through Zoho MCP for easy discovery and connection. Lets AI tools query dashboards, explore datasets, generate reports, and interact with analytics workspaces through the Model Context Protocol.", "category": "data", "endpoint": "Zoho Analytics MCP", "homepage_url": "https://www.zoho.com/analytics/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-29", "updated": "2026-06-29", "tags": [ "zoho", "analytics", "business-intelligence", "dashboards", "reporting", "data-visualization" ], "use_cases": [ "Query Zoho Analytics dashboards and datasets through AI assistants for conversational business intelligence", "Generate and customize reports from Zoho Analytics workspaces using natural language prompts", "Integrate Zoho Analytics insights into AI-driven decision-making workflows across the Zoho ecosystem" ], "health": "active" }, { "id": "x-hosted-mcp", "name": "X Hosted MCP", "description": "Official hosted MCP server from X (formerly Twitter), announced June 30, 2026. Gives AI agents like Grok, Cursor, and Claude instant real-time access to X platform data through the v2 API. Hosted by X Developers so there is no local server to run. Supports searching posts, reading user profiles, fetching timelines, and accessing trending topics. Designed for AI-native workflows where agents need live social data without managing API wrappers.", "category": "data", "endpoint": "X Hosted MCP", "homepage_url": "https://devcommunity.x.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "twitter", "x", "social-media", "real-time", "hosted", "official", "social-data" ], "use_cases": [ "Give AI agents real-time access to X posts, user profiles, and trending topics without managing local API wrappers", "Build social listening and sentiment analysis workflows powered by live X data through MCP-compatible AI tools", "Enable AI coding assistants to search and reference X conversations for research and content creation" ], "health": "active" }, { "id": "meta-astryx-mcp", "name": "Meta Astryx MCP", "description": "MCP server from Meta's open-source Astryx React design system, announced June 27, 2026. Astryx ships 90+ production-grade React components built with StyleX, ten themes, and agent-ready MCP tooling. The MCP server lets AI coding assistants scaffold UIs, look up component APIs, generate themed layouts, and document patterns directly from the design system. Token-optimized CLI included for context-efficient agent workflows.", "category": "code", "endpoint": "Meta Astryx MCP", "homepage_url": "https://github.com/facebook/astryx", "github_url": "https://github.com/facebook/astryx", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "react", "design-system", "meta", "stylex", "ui-components", "frontend", "open-source" ], "use_cases": [ "Scaffold production-grade React UIs from Meta's component library using AI coding assistants with full API context", "Look up Astryx component props, variants, and theme tokens directly from Claude Code or Cursor while building interfaces", "Generate themed layouts and document design patterns using agent-ready MCP tooling optimized for token efficiency" ], "health": "active" }, { "id": "oracle-goldengate-mcp", "name": "Oracle GoldenGate MCP", "description": "Open-source MCP server for Oracle GoldenGate, the enterprise data integration and replication platform. Enables AI agents to manage GoldenGate extract and replicat processes, monitor replication lag, inspect trail files, and automate data pipeline operations through natural language. Supports both assistant-driven and fully agentic workflows for database replication management. Published under oracle/mcp on GitHub.", "category": "data", "endpoint": "Oracle GoldenGate MCP Server", "homepage_url": "https://blogs.oracle.com/dataintegration/enabling-agent-driven-operations-in-oracle-goldengate-with-mcp-an-open-source-mcp-server", "github_url": "https://github.com/oracle/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "oracle", "goldengate", "data-replication", "data-integration", "enterprise", "database", "open-source" ], "use_cases": [ "Monitor and manage Oracle GoldenGate replication processes through AI assistants using natural language commands", "Automate data pipeline operations like starting extracts, checking replication lag, and inspecting trail files via MCP", "Build agentic workflows for enterprise data integration that combine GoldenGate operations with other MCP tools" ], "health": "active" }, { "id": "proxima-mcp", "name": "Proxima", "description": "Open-source, local-first MCP server that connects multiple AI providers (ChatGPT, Claude, Gemini, Perplexity) to your development environment without API keys. Acts as a unified AI gateway at the browser level, letting MCP-compatible coding tools like Cursor and Claude Code access multiple models through a single local server. No cloud dependency or API billing required. MIT-licensed.", "category": "ai", "endpoint": "Proxima MCP Server", "homepage_url": "https://www.proximamcp.in/", "github_url": "https://github.com/Zen4-bit/Proxima", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "multi-model", "local-first", "ai-gateway", "no-api-key", "chatgpt", "gemini", "perplexity", "open-source" ], "use_cases": [ "Access ChatGPT, Claude, Gemini, and Perplexity from Cursor or Claude Code through a single local MCP gateway with no API keys", "Run multi-model comparison workflows locally by routing prompts to different AI providers without managing separate integrations", "Add AI capabilities to development environments on air-gapped or cost-sensitive setups using browser-level provider connections" ], "health": "active" }, { "id": "stibo-systems-mcp", "name": "Stibo Systems MCP", "description": "MCP server from Stibo Systems, the largest independent provider of master data management (MDM). Announced June 30, 2026, it connects enterprise master data to AI agents at scale. Enables AI tools to query, enrich, and validate product, customer, supplier, and location master data through the STEP platform. Designed for enterprise MDM workflows where AI agents need governed, high-quality data access.", "category": "data", "endpoint": "Stibo Systems MCP", "homepage_url": "https://www.stibosystems.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "mdm", "master-data", "enterprise", "product-data", "data-governance", "data-quality", "step-platform" ], "use_cases": [ "Give AI agents governed access to enterprise master data for products, customers, suppliers, and locations through MCP", "Automate master data enrichment and validation workflows by connecting AI assistants to the STEP MDM platform", "Build AI-driven data quality pipelines that query and cross-reference master data records at enterprise scale" ], "health": "active" }, { "id": "dynamics-365-commerce-mcp", "name": "Dynamics 365 Commerce MCP", "description": "Official MCP server from Microsoft for Dynamics 365 Commerce, announced June 29, 2026. Enables AI agents to power product discovery, checkout flows, inventory management, and retail operations through the Commerce platform. Supports agentic commerce scenarios where AI handles end-to-end retail workflows including product search, cart management, order processing, and store inventory queries.", "category": "data", "endpoint": "Dynamics 365 Commerce MCP", "homepage_url": "https://www.microsoft.com/en-us/dynamics-365/products/commerce", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "microsoft", "dynamics-365", "commerce", "retail", "e-commerce", "inventory", "enterprise" ], "use_cases": [ "Enable AI agents to handle end-to-end retail workflows including product discovery, checkout, and order processing via Dynamics 365", "Automate inventory queries and store operations through AI assistants connected to the Commerce platform", "Build agentic commerce experiences where AI manages cart operations, product search, and customer interactions at scale" ], "health": "active" }, { "id": "ashby-mcp", "name": "Ashby MCP", "description": "Official MCP server from Ashby, the all-in-one recruiting platform. Launched in open beta, available on all Ashby plans. Gives AI tools a standard interface to interact with Ashby's ATS data including job postings, candidate pipelines, interview schedules, and hiring analytics. Enables AI assistants to search candidates, review applications, and pull recruiting metrics through MCP.", "category": "productivity", "endpoint": "Ashby MCP Server", "homepage_url": "https://www.ashbyhq.com/product-updates/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "recruiting", "ats", "hr", "hiring", "talent-acquisition", "applicant-tracking", "open-beta" ], "use_cases": [ "Search and review candidate pipelines through AI assistants connected to Ashby's recruiting platform via MCP", "Pull hiring analytics and interview data from Ashby into AI-driven recruiting workflows without manual exports", "Automate job posting management and candidate screening by giving AI agents direct access to ATS data" ], "health": "active" }, { "id": "crossbeam-mcp", "name": "Crossbeam MCP", "description": "MCP server from Crossbeam, the partner ecosystem intelligence platform. Currently in limited availability for Supernode and Enterprise customers. Enables AI agents to query partner overlap data, account mapping results, and ecosystem insights through MCP. Designed for partnership and revenue teams who want AI assistants to surface co-selling opportunities and partner intelligence without switching tools.", "category": "data", "endpoint": "Crossbeam MCP Server", "homepage_url": "https://help.crossbeam.com/en/articles/12601327-crossbeam-mcp-server-limited-availability", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-06-30", "updated": "2026-06-30", "tags": [ "partnerships", "ecosystem", "account-mapping", "co-selling", "revenue", "b2b", "partner-data" ], "use_cases": [ "Query partner overlap data and account mapping results through AI assistants for faster co-selling decisions", "Surface ecosystem intelligence and partner insights in AI workflows without switching to the Crossbeam dashboard", "Build AI-driven partner revenue workflows that combine Crossbeam data with CRM and other MCP-connected tools" ], "health": "active" }, { "id": "siteimprove-mcp", "name": "Siteimprove MCP", "description": "Official MCP server from Siteimprove, announced June 30, 2026. Embeds Siteimprove's Accessibility Agent into AI coding and design environments including Claude, VS Code, Lovable, and Figma. Enables real-time accessibility audits and remediation during content creation rather than post-publish. Supports agent-to-agent workflows where coding agents trigger autonomous accessibility checks. Also ships a Figma plug-in with in-canvas audits and color-blindness simulation.", "category": "code", "endpoint": "Siteimprove MCP Server", "homepage_url": "https://www.siteimprove.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "accessibility", "a11y", "wcag", "design-tools", "figma", "vscode", "content-quality", "compliance" ], "use_cases": [ "Run real-time accessibility audits inside Claude, VS Code, and Figma while building interfaces instead of scanning after deployment", "Enable agent-to-agent workflows where AI coding agents automatically trigger accessibility validation during content generation", "Catch WCAG compliance issues at the authoring layer to reduce downstream QA burden and remediation costs" ], "health": "active" }, { "id": "grist-mcp", "name": "Grist MCP", "description": "Official MCP server from Grist Labs for the open-source Grist spreadsheet-database platform, announced June 30, 2026. Available for all hosted Grist users and self-hosters running the full edition. Lets AI agents and assistants read, query, and modify Grist documents through MCP. Uses OAuth-based connected apps so access can be scoped to specific documents, workspaces, or organizations and revoked at any time. Supports agentic workflows like automated PR triage based on Grist data.", "category": "productivity", "endpoint": "Grist MCP Server", "homepage_url": "https://www.getgrist.com", "github_url": "https://github.com/gristlabs/grist-core", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "spreadsheet", "database", "open-source", "self-hosted", "oauth", "data-management", "productivity" ], "use_cases": [ "Give AI agents structured read and write access to Grist spreadsheet-databases with OAuth-scoped permissions per document or workspace", "Build agentic workflows that combine Grist data with GitHub and other MCP tools for automated triage, reporting, and data-driven operations", "Connect self-hosted Grist instances to AI coding assistants for querying and updating project data without leaving the development environment" ], "health": "active" }, { "id": "snap-ads-mcp", "name": "Snap Ads MCP", "description": "MCP server from Snap Inc. for its advertising platform, announced June 18, 2026. Enables AI agents and agentic workflows to interact with Snap's ad management APIs for campaign setup, optimization, and reporting. Part of Snap's broader push into AI-powered advertising automation alongside a new chat assistant and creator matching tools. Designed for advertisers and agencies building custom AI workflows around Snapchat campaign management.", "category": "data", "endpoint": "Snap Ads MCP Server", "homepage_url": "https://forbusiness.snapchat.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "advertising", "snapchat", "social-media", "campaign-management", "ad-tech", "marketing", "automation" ], "use_cases": [ "Automate Snapchat ad campaign setup and management through AI agents connected to Snap's advertising platform via MCP", "Build custom AI workflows that optimize Snapchat ad spend, targeting, and creative selection without manual dashboard interaction", "Integrate Snapchat campaign data and reporting into multi-platform advertising automation pipelines alongside other MCP-connected ad tools" ], "health": "active" }, { "id": "sabre-mcp", "name": "Sabre MCP", "description": "MCP server from Sabre Corporation (NASDAQ: SABR) for the Sabre Mosaic travel platform, announced June 17, 2026 with a production deployment at Linex Travel. Acts as a secure translation layer enabling autonomous AI agents to interact with complex travel workflows including shopping, booking, and servicing. Handles post-booking tasks like ticket reissues, dynamic exchanges, and servicing updates. Built for travel agencies, airlines, and loyalty programs running agentic AI workflows at scale.", "category": "data", "endpoint": "Sabre MCP Server", "homepage_url": "https://www.sabre.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "travel", "airlines", "booking", "loyalty", "enterprise", "gds", "travel-servicing", "agentic-ai" ], "use_cases": [ "Enable AI agents to manage complex travel post-booking tasks like ticket reissues, exchanges, and servicing updates through Sabre's platform", "Build autonomous travel retailing workflows that handle shopping, booking, and servicing across airlines and loyalty programs at scale", "Connect travel loyalty platforms to AI agents for intelligent redemption, dynamic offers, and end-to-end digital travel experiences" ], "health": "active" }, { "id": "govspend-mcp", "name": "GovSpend MCP", "description": "MCP server from GovSpend, the public sector procurement intelligence platform, launched June 16, 2026. Provides AI agents and custom workflows with direct access to government procurement data including 2 billion+ purchase orders, 96 million+ contracts, 10 million+ agency contacts, and 2.3 million+ public meeting transcripts. Works with Claude, ChatGPT, and internally built agents. Designed for sellers, buyers, and consultants operating in the government procurement ecosystem.", "category": "data", "endpoint": "GovSpend MCP Server", "homepage_url": "https://www.govspend.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "government", "procurement", "public-sector", "contracts", "intelligence", "b2g", "data-platform" ], "use_cases": [ "Query billions of government purchase orders and contracts through AI agents to surface procurement opportunities and track agency spending", "Build custom AI agents that monitor public sector procurement signals and surface actionable sales intelligence for government vendors", "Integrate government procurement data into AI-powered dashboards and agentic workflows without manual searches or static reports" ], "health": "active" }, { "id": "vorlon-guardian-mcp", "name": "Vorlon Guardian", "description": "Real-time enforcement gateway from Vorlon for securing AI agent interactions with MCP servers, SaaS apps, and data stores. Announced June 30, 2026. Sits at the protocol layer between AI agents and connected systems to block policy violations, mask sensitive data in transit, and enforce read-only access before transactions complete. Covers agent-specific threats including indirect prompt injection, credential abuse, OAuth token abuse, and agent-to-agent manipulation. Works with any app or data store that has an API or MCP server.", "category": "infrastructure", "endpoint": "Vorlon Guardian", "homepage_url": "https://vorlon.io", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "security", "ai-governance", "runtime-security", "data-masking", "policy-enforcement", "agent-security", "enterprise" ], "use_cases": [ "Enforce real-time security policies on AI agent actions across MCP servers, SaaS apps, and cloud data stores before transactions complete", "Mask sensitive data in transit and restrict AI agents to read-only access to prevent unauthorized writes or data exfiltration", "Detect and block agent-specific threats like indirect prompt injection, credential abuse, and agent-to-agent manipulation at the protocol layer" ], "health": "active" }, { "id": "pentera-mcp", "name": "Pentera MCP", "description": "MCP server from Pentera, the exposure validation and offensive security platform, announced June 16, 2026. Enables AI assistants and agents to trigger Pentera security tests, access validated attack findings, and pull remediation guidance directly within AI-powered SecOps workflows. Security teams can validate whether specific vulnerabilities represent real exploitable exposure and prioritize fixes based on proven cyber risk. Integrates with any MCP-compatible environment.", "category": "infrastructure", "endpoint": "Pentera MCP Server", "homepage_url": "https://pentera.io", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "security", "penetration-testing", "vulnerability-validation", "offensive-security", "secops", "ctem", "remediation" ], "use_cases": [ "Trigger automated security validation tests from AI SecOps workflows to confirm whether vulnerabilities are genuinely exploitable", "Pull validated attack findings and remediation guidance into AI assistants for faster, evidence-based security prioritization", "Integrate offensive security validation into agentic SecOps pipelines for continuous threat exposure management across the enterprise" ], "health": "active" }, { "id": "snyk-evo-mcp", "name": "Snyk Evo ADS", "description": "Agentic Development Security platform from Snyk, announced June 24, 2026. Goes beyond the existing Snyk MCP server by governing AI agents in real time, securing MCP server connections, monitoring agent behavior, and scanning AI-generated code across the full development lifecycle. Provides runtime governance for agentic coding workflows in tools like Claude Code, Cursor, and GitHub Copilot. Enforces security policies on which MCP servers agents can connect to and what actions they can take.", "category": "infrastructure", "endpoint": "Snyk Evo ADS", "homepage_url": "https://snyk.io/product/agentic-development-security/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-01", "updated": "2026-07-01", "tags": [ "security", "devsecops", "ai-governance", "code-scanning", "agent-security", "runtime-governance", "enterprise" ], "use_cases": [ "Govern which MCP servers AI coding agents can connect to and enforce security policies on agent actions in real time", "Scan AI-generated code for vulnerabilities across the full development lifecycle in Claude Code, Cursor, and GitHub Copilot workflows", "Monitor and control agentic coding behavior to prevent insecure code patterns, unauthorized tool use, and supply chain risks" ], "health": "active" }, { "id": "homesage-mcp", "name": "Homesage.ai Real Estate MCP", "description": "MCP server from Homesage.ai providing investor-grade real estate intelligence, announced July 1, 2026. Gives AI assistants access to 155M+ US property records through 33 specialized investor tools covering valuations, comparable sales, fix-and-flip return modeling, rental projections, renovation cost estimates, and property condition assessments. Compatible with Claude, ChatGPT, and Gemini. Credit-based pricing starting at $160/month.", "category": "data", "endpoint": "Homesage.ai MCP Server", "homepage_url": "https://homesage.ai/products/real-estate-mcps/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "real-estate", "property-data", "investing", "valuations", "comps", "rental-analysis", "proptech" ], "use_cases": [ "Query 155M+ US property records for instant valuations, comparable sales, and investment potential scores through AI assistants", "Model fix-and-flip returns, renovation budgets, and rental income projections via natural language conversations in Claude or ChatGPT", "Run property condition assessments, location risk analysis, and deal discovery searches across the US real estate market through MCP" ], "health": "active" }, { "id": "xbtfx-mcp", "name": "XBTFX MCP Server", "description": "MCP server from XBTFX for crypto and CFD trading workflows, announced July 1, 2026. Enables AI agents to interact with XBTFX trading infrastructure for market analysis, trade execution, and portfolio management across crypto and CFD instruments. Part of a broader agent stack including a Skills Hub and Trading API. Available without separate API subscription fees beyond normal trading spreads and commissions.", "category": "data", "endpoint": "XBTFX MCP Server", "homepage_url": "https://xbtfx.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "crypto", "cfd", "trading", "forex", "finance", "agent-stack", "market-data" ], "use_cases": [ "Connect AI agents to XBTFX trading infrastructure for executing crypto and CFD trades through agentic workflows", "Build automated trading strategies using AI agents with access to market data, order management, and portfolio analytics via MCP", "Integrate XBTFX trading capabilities into multi-agent systems alongside other MCP-connected financial tools" ], "health": "active" }, { "id": "amazon-sp-api-mcp", "name": "Amazon SP-API MCP Server", "description": "Official self-hosted MCP server from Amazon for the Selling Partner API (SP-API), enabling AI agents to interact with Amazon marketplace operations. Provides tools for managing product listings, inventory, orders, fulfillment, and reporting across Amazon seller and vendor accounts. Designed for e-commerce sellers, agencies, and developers building AI-powered Amazon marketplace automation.", "category": "data", "endpoint": "amazon-sp-api-mcp", "homepage_url": "https://developer-docs.amazon.com/sp-api", "github_url": "https://github.com/amzn/selling-partner-api-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "amazon", "e-commerce", "marketplace", "sp-api", "selling-partner", "inventory", "orders", "fulfillment" ], "use_cases": [ "Manage Amazon product listings, inventory levels, and pricing through AI agents connected to the Selling Partner API via MCP", "Build agentic e-commerce workflows that monitor orders, track fulfillment, and generate seller performance reports using natural language", "Automate Amazon marketplace operations including catalog management, advertising, and financial reporting through AI-powered SP-API interactions" ], "health": "active" }, { "id": "moonlit-mcp", "name": "Moonlit Connect MCP", "description": "MCP server from Moonlit, the legal data platform, announced June 2026. Provides AI agents with access to continuously updated laws, regulations, and case law from 30+ jurisdictions worldwide. Enables legal research, regulatory monitoring, and compliance workflows through AI assistants. Used by 7,000+ judges, lawyers, prosecutors, and researchers. Trusted by KPMG, Deloitte, LexisNexis, and government institutions.", "category": "data", "endpoint": "Moonlit Connect MCP", "homepage_url": "https://www.moonlit.ai", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "legal", "law", "regulations", "case-law", "compliance", "legal-research", "multi-jurisdiction", "legaltech" ], "use_cases": [ "Search and analyze laws, regulations, and case law across 30+ jurisdictions through AI assistants connected to Moonlit's continuously updated legal database", "Monitor legal and regulatory developments across multiple countries for compliance and horizon scanning through agentic workflows", "Integrate structured global legal data into AI-powered legal research, drafting, and advisory workflows via MCP" ], "health": "active" }, { "id": "finos-aigf-mcp", "name": "FINOS AIGF MCP Server", "description": "Open-source MCP server from FINOS (Fintech Open Source Foundation) for operationalizing the AI Governance Framework inside AI agents, announced June 22, 2026. Supplies structured governance context to AI agents operating in financial services, enabling them to meet industry-specific risk assessment, compliance, and audit requirements. Designed for banks, asset managers, and financial institutions deploying agentic AI systems.", "category": "infrastructure", "endpoint": "FINOS AIGF MCP Server", "homepage_url": "https://www.finos.org/blog/operationalizing-ai-governance-finos-aigf-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "ai-governance", "financial-services", "compliance", "risk-assessment", "fintech", "open-source", "finos", "audit" ], "use_cases": [ "Supply structured AI governance context to agents operating in financial services for compliance with industry-specific risk frameworks", "Accelerate AI risk assessments in banks and asset managers by embedding FINOS governance guardrails directly into agentic workflows via MCP", "Enable financial institutions to operationalize AI governance policies at the agent level with standardized compliance context and audit trails" ], "health": "active" }, { "id": "openehr-mcp", "name": "openEHR MCP Server", "description": "MCP server for connecting AI agents to openEHR-based clinical data repositories (CDRs). Enables AI assistants to query patient health records, create clinical compositions for any template available on the server, and interact with structured health data following the openEHR standard. Supports archetype queries and template-based data entry for vital signs, lab results, and other clinical data types.", "category": "data", "endpoint": "openEHR MCP Server", "homepage_url": "https://discourse.openehr.org/t/openehr-mcp-server-a-plugin-to-connect-llms-with-cdrs/6869", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-02", "updated": "2026-07-02", "tags": [ "healthcare", "clinical-data", "ehr", "openehr", "health-records", "medical", "interoperability" ], "use_cases": [ "Query patient health records stored in openEHR-based clinical data repositories through AI assistants using natural language", "Create and submit clinical compositions for vital signs, lab results, and other health data types via AI agents connected to openEHR servers", "Enable AI-powered clinical decision support by giving agents structured access to archetype-based health data across openEHR-compliant systems" ], "health": "active" }, { "id": "safari-webkit-mcp", "name": "Safari MCP Server", "description": "Official MCP server from Apple/WebKit, introduced in Safari Technology Preview 247 on July 1, 2026. Gives AI coding agents direct access to a live Safari browser tab for web development and debugging. Agents can take screenshots, read the DOM, check network logs, run JavaScript, test forms, inspect accessibility failures, resize the viewport, and monitor console errors. Runs entirely on the local machine with no data sent to Apple. Compatible with Claude, Codex, and other MCP clients.", "category": "code", "endpoint": "Safari MCP Server", "homepage_url": "https://webkit.org/blog/18136/introducing-the-safari-mcp-server-for-web-developers/", "github_url": "https://github.com/WebKit/WebKit", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "safari", "apple", "webkit", "browser", "debugging", "web-development", "accessibility", "screenshots" ], "use_cases": [ "Debug websites in Safari with AI coding agents that can inspect the DOM, read console logs, capture network requests, and take screenshots directly from a live browser tab", "Identify Safari-specific compatibility issues, accessibility failures, and performance problems through AI-assisted analysis without manual browser switching", "Test forms, verify page states, and resize viewports programmatically through AI agents connected to Safari via MCP for automated web development workflows" ], "health": "active" }, { "id": "leverate-mcp", "name": "Leverate Back-Office MCP Server", "description": "MCP server from Leverate for connecting AI assistants to broker back-office operational data, announced June 30, 2026. Provides read-only access to permissioned data across CRM, Broker Portal, and Trading Platform through a single standardized interface. Designed for forex, crypto, and CFD brokers to explore marketing, risk, and operations data conversationally. Deliberately excludes trade execution and money movement for safety. Compatible with Claude, ChatGPT, and other MCP clients.", "category": "data", "endpoint": "Leverate MCP Server", "homepage_url": "https://leverate.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "forex", "broker", "back-office", "crm", "trading", "fintech", "read-only", "risk-management" ], "use_cases": [ "Connect AI assistants to broker CRM, portal, and trading platform data for conversational exploration of marketing, risk, and operations metrics", "Surface patterns across trading, marketing, and risk activity and receive context-aware suggestions for running and scaling brokerage businesses", "Enable compliance and operations teams at forex and CFD brokerages to query permissioned back-office data through natural language without touching execution" ], "health": "active" }, { "id": "unreal-engine-mcp", "name": "Unreal Engine MCP Server", "description": "Official experimental MCP server plugin from Epic Games, shipped with Unreal Engine 5.8. Enables AI assistants and coding agents to connect directly to the Unreal Editor through the Model Context Protocol. AI agents can navigate Blueprints, manipulate assets, build levels, adjust materials, and work with meshes through a standardized interface. Features a Tool Search mechanism for discovering available toolsets dynamically. Runs inside the editor process on localhost:8000/mcp with auto-start support.", "category": "code", "endpoint": "unreal-engine-mcp", "homepage_url": "https://dev.epicgames.com/documentation/unreal-engine/unreal-mcp-in-unreal-editor", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "unreal-engine", "epic-games", "game-development", "3d", "editor", "blueprints", "level-design", "materials" ], "use_cases": [ "Control the Unreal Editor through AI coding agents to navigate Blueprints, manipulate assets, build levels, and adjust materials via natural language", "Automate game development workflows by letting AI assistants discover and invoke Unreal Engine tools dynamically through the MCP Tool Search mechanism", "Integrate AI-assisted level design, material editing, and mesh manipulation into Unreal Engine 5.8 projects using Claude, Cursor, or other MCP-compatible clients" ], "health": "active" }, { "id": "navan-mcp", "name": "Navan MCP Server", "description": "MCP server from Navan for corporate travel and expense management, announced July 1, 2026. Enables administrators and finance leaders to analyze spend, booking, and policy data through natural language queries in their preferred AI tools. Provides read-only access to aggregate program insights, live transaction timelines, expense reconciliation, compliance monitoring with in-policy flags, and cost breakdowns including currency and tax details. Compatible with Claude, ChatGPT, Cursor, and other MCP clients.", "category": "productivity", "endpoint": "Navan MCP Server", "homepage_url": "https://navan.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "travel", "expense-management", "corporate", "finance", "compliance", "booking", "spend-analytics" ], "use_cases": [ "Analyze corporate travel spend, booking patterns, and policy compliance across global teams through natural language queries in Claude or ChatGPT", "Reconcile expenses by sweeping bookings for trailing periods, grouping by traveler and booking type, and cross-joining with expense data via AI assistants", "Monitor out-of-policy spend and flagged expenses with real-time compliance data including policy reasons, approval status, and cost breakdowns through MCP" ], "health": "active" }, { "id": "facilio-mcp", "name": "Facilio CMMS MCP Server", "description": "MCP server from Facilio, the connected CMMS platform, announced July 1, 2026 as part of the AI-native evolution of their facility management platform. Makes CMMS data and actions reachable from Claude, ChatGPT, or Gemini, enabling facilities teams to manage operations through AI interfaces instead of traditional dashboards. Supports service request handling, vendor coordination, invoice validation, compliance tracking, and report generation through AI agents.", "category": "infrastructure", "endpoint": "Facilio MCP Server", "homepage_url": "https://facilio.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "cmms", "facility-management", "building-operations", "maintenance", "iot", "work-orders", "compliance" ], "use_cases": [ "Manage facility maintenance operations through AI assistants by querying CMMS data, handling service requests, and coordinating vendor activities via natural language", "Track compliance, validate invoices, and generate operational reports for multi-site facility portfolios through AI agents connected to Facilio via MCP", "Enable facilities teams to log, update, and close work requests through AI interfaces like Claude or ChatGPT instead of navigating traditional CMMS dashboards" ], "health": "active" }, { "id": "flowhub-mcp", "name": "Flowhub MCP Connector", "description": "MCP server from Flowhub for cannabis retail dispensary operations, announced July 1, 2026. Connects dispensary operator accounts directly to AI tools including ChatGPT, Claude, Gemini, Grok, Perplexity, and Cursor. AI agents can perform approved actions such as updating pricing, moving inventory, and creating promotions through natural language. Maintains complete audit trails with operator approval required before changes are applied.", "category": "data", "endpoint": "Flowhub MCP Server", "homepage_url": "https://www.flowhub.com/learn/ai-changing-cannabis-retail", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "cannabis", "dispensary", "retail", "pos", "inventory", "pricing", "promotions", "compliance" ], "use_cases": [ "Manage dispensary inventory, pricing, and promotions through AI assistants using natural language commands with operator approval before changes are applied", "Analyze slow-moving products and create targeted deals to sell through excess inventory while maintaining margin thresholds via conversational AI workflows", "Connect cannabis retail POS and inventory data to any MCP-compatible AI tool for operational analytics, compliance tracking, and automated retail management" ], "health": "active" }, { "id": "helix-genosphere-mcp", "name": "Helix GenoSphere MCP Connector", "description": "MCP connector from Helix for population-scale clinico-genomic data, launched in Claude Science on July 1, 2026. First MCP connector enabling AI-accelerated exploration of linked clinico-genomic records, providing access to over 500,000 de-identified records drawn from health systems across North America. Supports queries on genetic variants, disease incidence, prevalence, and longitudinal disease states. Returns only de-identified aggregate statistics with small counts automatically suppressed for privacy. Available to approved enterprise health system and life sciences partners.", "category": "data", "endpoint": "Helix GenoSphere MCP Connector", "homepage_url": "https://www.helix.com/what-we-do/helix-genosphere", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-03", "updated": "2026-07-03", "tags": [ "genomics", "genetics", "healthcare", "clinical-data", "research", "life-sciences", "biotech", "population-health" ], "use_cases": [ "Explore population-scale clinico-genomic data across 500,000+ linked records through AI assistants to identify pathogenic variants and disease associations", "Accelerate genetic research and drug discovery by querying de-identified aggregate genomic statistics through natural language in Claude Science", "Analyze disease incidence, prevalence, and longitudinal health patterns across North American health system data via MCP-connected AI workflows" ], "health": "active" }, { "id": "pressable-mcp", "name": "Pressable MCP Server", "description": "MCP server from Pressable for managed WordPress hosting operations, with a major expansion shipped June 30, 2026. Enables AI assistants to manage WordPress sites through natural language including cache management, backups, WP-CLI commands, SSL certificates, environment transfers, and password resets. Supports running commands across individual sites or entire portfolios simultaneously. Includes team permission controls for governing who can trigger operational commands through AI agents.", "category": "infrastructure", "endpoint": "Pressable MCP Server", "homepage_url": "https://pressable.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "wordpress", "hosting", "devops", "cache", "backups", "ssl", "wp-cli", "site-management" ], "use_cases": [ "Manage WordPress hosting operations through AI assistants including clearing cache, downloading backups, running WP-CLI commands, and resetting passwords without opening a dashboard", "Run operational commands across multiple WordPress sites simultaneously through AI agents with portfolio-wide WP-CLI and shell command support", "Monitor SSL certificate status, transfer environments, and toggle defensive mode across managed WordPress sites using natural language through Claude, ChatGPT, or Gemini" ], "health": "active" }, { "id": "featured-mcp", "name": "Featured MCP Server", "description": "MCP server from Featured, the AI co-pilot for PR, connecting AI coding agents directly to PR workflows and opportunity search. Unlike chat-based PR tools that just layer AI on media databases, Featured's MCP server lets agents take structured actions across the PR workflow without manual copy-paste between systems. Compatible with Claude, Cursor, VS Code, and other MCP-compatible clients.", "category": "productivity", "endpoint": "Featured MCP Server", "homepage_url": "https://featured.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "pr", "public-relations", "media", "marketing", "content", "journalism", "outreach" ], "use_cases": [ "Search for PR and media placement opportunities through AI agents connected to Featured's platform without switching between tools or copying data manually", "Automate PR workflows by letting AI coding agents in Claude Code, Cursor, or VS Code take structured actions across media outreach and opportunity management", "Connect PR agency workflows to AI assistants for streamlined journalist pitching, opportunity tracking, and content placement through the Model Context Protocol" ], "health": "active" }, { "id": "chrome-webmcp", "name": "Chrome WebMCP", "description": "WebMCP from Google Chrome, available in early preview for Chrome Canary. A proposed web standard that turns any web page into a structured MCP-compatible tool for AI agents. Provides both a Declarative API for standard HTML form actions and an Imperative API for complex dynamic interactions via JavaScript. Instead of screenshot-analyze-click loops, AI agents call declared tools directly with typed parameters. Backed by Booking.com, Expedia, Instacart, Intuit, Shopify, and Redfin. Native browser support expected across Chrome and Edge in H2 2026.", "category": "code", "endpoint": "Chrome WebMCP", "homepage_url": "https://developer.chrome.com/docs/ai/webmcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "chrome", "google", "browser", "web-standard", "agent-ready", "forms", "automation", "web-interaction" ], "use_cases": [ "Enable AI agents to interact with websites through structured tool calls instead of slow screenshot-analyze-click loops by declaring page actions as MCP-compatible tools", "Build agent-ready web applications using the Declarative API for HTML form actions and the Imperative API for complex JavaScript interactions that AI agents can invoke directly", "Make e-commerce, travel, and service websites natively accessible to AI agents like Claude and ChatGPT through Google's WebMCP standard without building separate API integrations" ], "health": "active" }, { "id": "x-official-mcp", "name": "X (Twitter) Official MCP Server", "description": "Official hosted MCP server from X (formerly Twitter), announced June 30, 2026. Provides AI assistants and coding agents with direct access to the X API through a single endpoint at api.x.com/mcp using Streamable HTTP. Supports 26 tools covering timelines, search, posting, engagement (likes, retweets, bookmarks), user lookup, follower export, mentions, articles, and lists. Users authenticate with their own X account permissions via OAuth. Compatible with Claude, Cursor, Grok Build, and other MCP clients.", "category": "communication", "endpoint": "https://api.x.com/mcp", "homepage_url": "https://developer.x.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "twitter", "x", "social-media", "posting", "search", "timelines", "engagement", "official" ], "use_cases": [ "Search the X full archive, pull trends, manage bookmarks, and draft and publish posts and Articles through AI assistants using your own account permissions", "Monitor mentions, track engagement metrics, export follower lists, and manage lists programmatically through Claude, Cursor, or other MCP-compatible agents", "Automate social media research and content workflows by connecting X data directly to AI coding agents via the hosted MCP endpoint at api.x.com/mcp" ], "health": "active" }, { "id": "visualping-mcp", "name": "Visualping MCP Server", "description": "Official MCP server from Visualping, the website change monitoring platform used by 85% of Fortune 500 companies, launched in public beta July 1, 2026. Gives AI coding agents the ability to create, edit, and view web page monitors in plain language and get clear summaries of what changed each time a page updates. Available on every Visualping plan including the free tier. Compatible with Claude, ChatGPT, Cursor, and other MCP clients.", "category": "web", "endpoint": "https://visualping.io/mcp/sse", "homepage_url": "https://visualping.io", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "sse", "auth": "api-key", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "monitoring", "website-changes", "alerts", "web-scraping", "change-detection", "notifications" ], "use_cases": [ "Monitor competitor websites, pricing pages, and product listings for changes through AI agents that create and manage Visualping monitors via natural language", "Track regulatory updates, policy changes, and compliance documents across government and industry websites with AI-powered change summaries", "Set up automated monitoring of job boards, documentation pages, and release notes so AI coding agents can alert you to relevant updates" ], "health": "active" }, { "id": "snaplogic-mcp-builder", "name": "SnapLogic MCP Builder", "description": "Enterprise MCP server creation tool from SnapLogic, made generally available July 1, 2026. Automatically generates ready-to-run MCP servers from existing integration pipelines, OpenAPI specifications, and API Management services through templates. Organizations can publish MCP tools without rebuilding workflows, writing code, or manually constructing MCP implementations. Designed for enterprise AI adoption at scale with governance controls built in.", "category": "infrastructure", "endpoint": "SnapLogic MCP Builder", "homepage_url": "https://www.snaplogic.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "enterprise", "integration", "ipaas", "no-code", "api-management", "automation", "governance" ], "use_cases": [ "Convert existing SnapLogic integration pipelines into governed MCP tools that AI agents can discover and invoke without rebuilding any workflows", "Generate MCP servers from OpenAPI specifications and API Management services through templates for rapid enterprise AI agent deployment", "Enable enterprise teams to operationalize AI by turning business processes into agent-ready MCP tools with built-in governance and access controls" ], "health": "active" }, { "id": "expensify-mcp", "name": "Expensify MCP Server", "description": "Official MCP server from Expensify for AI-powered expense management, launched June 8, 2026. Allows AI assistants to securely access and analyze Expensify data through natural language queries. Supports expense filtering, receipt finding, approval tracking, and spend summarization. Read-only at launch with only the Search tool exposed, scoped to existing user permissions. Secured through OAuth 2.1 for enterprise-grade security. First bring-your-own-card expense management MCP server. Compatible with ChatGPT, Claude, Cursor, OpenClaw, and other MCP clients.", "category": "data", "endpoint": "Expensify MCP Server", "homepage_url": "https://use.expensify.com/blog/expensify-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-04", "updated": "2026-07-04", "tags": [ "expense-management", "finance", "receipts", "approval", "spend-analytics", "corporate", "accounting" ], "use_cases": [ "Query expense data through natural language in AI assistants to find specific receipts, filter expenses by category or date, and summarize travel or team spending", "Track expense report approval status and identify pending approvals across teams through conversational AI without logging into the Expensify dashboard", "Analyze corporate spending patterns and generate ad-hoc expense reports through Claude, ChatGPT, or Cursor with OAuth 2.1 secured read-only access to Expensify data" ], "health": "active" }, { "id": "publora-mcp", "name": "Publora MCP Server", "description": "MCP server from Publora for unified social media publishing across 10 platforms. Exposes 18 tools that let AI assistants like Claude, Cursor, and Codex manage social media in plain language including posting, scheduling, reading feeds, commenting, reacting to mentions, and replying to messages across Instagram, LinkedIn, X, TikTok, YouTube, Facebook, Threads, Bluesky, Mastodon, and Telegram with a single call. Starter plan free for 9 platforms.", "category": "communication", "endpoint": "Publora MCP Server", "homepage_url": "https://publora.com", "github_url": "https://github.com/publora", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "social-media", "publishing", "scheduling", "instagram", "linkedin", "tiktok", "bluesky", "mastodon", "multi-platform" ], "use_cases": [ "Publish content to 10 social media platforms simultaneously from AI assistants like Claude or Cursor using natural language commands without switching between dashboards", "Schedule posts, read feeds, comment on industry posts, and reply to mentions across Instagram, LinkedIn, X, TikTok, YouTube, and more through a single MCP endpoint", "Automate social media workflows by connecting AI coding agents to Publora for content creation, cross-platform publishing, and engagement management" ], "health": "active" }, { "id": "gravitee-apim-mcp", "name": "Gravitee APIM MCP Server", "description": "MCP server from Gravitee for API management and AI agent governance. Converts existing REST APIs into MCP-compatible tools automatically from OpenAPI specifications without writing code. Includes three capabilities: MCP Tool Server for turning APIs into agent tools, MCP Proxy for governing upstream MCP servers with OAuth 2.1, and APIM MCP Server for managing the Gravitee platform via natural language. Part of Gravitee's AI Agent Management platform with centralized control of agent traffic across MCP and A2A protocols.", "category": "infrastructure", "endpoint": "Gravitee APIM MCP Server", "homepage_url": "https://www.gravitee.io/platform/ai-gateway", "github_url": "https://github.com/gravitee-io/gravitee-apim-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "api-gateway", "api-management", "openapi", "governance", "oauth", "proxy", "a2a", "enterprise", "rest-to-mcp" ], "use_cases": [ "Convert existing REST APIs into AI-agent-ready MCP tools automatically from OpenAPI specifications without writing new code using Gravitee's embedded MCP server", "Govern and secure upstream MCP server traffic with OAuth 2.1 authentication, rate limiting, and access control through Gravitee's centralized MCP Proxy", "Manage API infrastructure through natural language by letting AI agents provision APIs, update policies, rotate credentials, and deploy across federated gateways via MCP" ], "health": "active" }, { "id": "block-xcode-index-mcp", "name": "Block Xcode Index MCP Server", "description": "Open-source MCP server from Block (Square) that gives AI agents direct access to Xcode's project index store through Apple's IndexStoreDB. Enables precise code navigation and refactoring operations on iOS and macOS projects with tools for loading project indexes, finding symbol occurrences, retrieving symbol references, and pattern-based symbol searching. Agents can find all call sites of a function and perform exhaustive refactoring across large Swift and Objective-C codebases.", "category": "code", "endpoint": "Block Xcode Index MCP Server", "homepage_url": "https://github.com/block/xcode-index-mcp", "github_url": "https://github.com/block/xcode-index-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install xcode-index-mcp", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "xcode", "ios", "macos", "swift", "objective-c", "code-navigation", "refactoring", "indexstoredb", "apple" ], "use_cases": [ "Navigate and refactor large iOS and macOS codebases by giving AI agents access to Xcode's project index for exhaustive symbol search and call site discovery", "Find all references and occurrences of functions, types, and variables across Swift and Objective-C projects through AI assistants without manual Xcode interaction", "Perform safe large-scale refactoring operations by leveraging IndexStoreDB to ensure all call sites and references are updated when renaming or modifying APIs" ], "health": "active" }, { "id": "searchcraft-mcp", "name": "Searchcraft MCP Server", "description": "Official MCP server from Searchcraft, the developer-first vertical search engine built in Rust. Provides tools for setting up search indexes, managing access keys, ingesting documents, viewing analytics, and performing advanced searches with fuzzy and exact matching, facet filtering, and date range queries. Layers semantic intent detection over a keyword engine for fast, explainable, and tunable search results. Compatible with Claude Desktop, Cursor, and other MCP clients.", "category": "data", "endpoint": "Searchcraft MCP Server", "homepage_url": "https://www.searchcraft.io", "github_url": "https://github.com/searchcraft-inc/searchcraft-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "search", "search-engine", "rust", "semantic-search", "indexing", "faceted-search", "document-retrieval" ], "use_cases": [ "Set up and manage search indexes through AI agents using plain English commands to configure access keys, ingest documents, and tune search relevance", "Perform advanced document retrieval with fuzzy matching, facet filtering, and date range queries across indexed content repositories via AI assistants", "Build AI-powered search applications using Searchcraft's MCP server for real-time document indexing, analytics monitoring, and semantic search from coding agents" ], "health": "active" }, { "id": "xcodebuild-mcp", "name": "XcodeBuildMCP Server", "description": "Open-source MCP server from Sentry (originally created by Cameron Cooke) that gives AI agents full control over Xcode for building, testing, debugging, and deploying iOS and macOS apps. Provides 82 MCP tools covering simulators, physical devices over USB and Wi-Fi, LLDB debugging with breakpoints and variable inspection, UI automation with screenshot capture, and project scaffolding. AI agents can independently build projects, fix compilation errors, and iterate on solutions. 5,400+ GitHub stars.", "category": "code", "endpoint": "XcodeBuildMCP Server", "homepage_url": "https://www.xcodebuildmcp.com", "github_url": "https://github.com/getsentry/XcodeBuildMCP", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "brew install xcodebuildmcp", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "xcode", "ios", "macos", "swift", "build", "test", "debug", "simulator", "lldb", "sentry", "mobile-development" ], "use_cases": [ "Build, run, and test iOS and macOS apps directly from AI coding agents like Claude Code or Cursor without leaving the agent, with automatic compilation error detection and fixing", "Debug iOS apps through AI agents using LLDB integration for setting breakpoints, inspecting variables, and executing debugger commands on simulators and physical devices", "Automate UI testing workflows by capturing screenshots, interacting with simulator UI elements, and deploying to physical devices over USB or Wi-Fi through MCP-compatible clients" ], "health": "active" }, { "id": "speakeasy-mcp-gateway", "name": "Speakeasy MCP Gateway", "description": "AI control plane from Speakeasy for generating, deploying, and governing MCP servers. Generates production-ready MCP servers from OpenAPI specifications through the Speakeasy CLI. Provides a centralized gateway for organizations rolling out MCP across their org with enterprise-grade OAuth 2.1 authentication, API key and bearer token support. Servers can be deployed to Cloudflare Workers, Docker, or any custom infrastructure. Includes full MCP release notes tracking and spec compliance tooling.", "category": "infrastructure", "endpoint": "Speakeasy MCP Gateway", "homepage_url": "https://www.speakeasy.com/mcp", "github_url": "https://github.com/speakeasy-api/speakeasy", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "sdk-generation", "openapi", "gateway", "governance", "cloudflare-workers", "docker", "oauth", "api-management", "cli" ], "use_cases": [ "Generate production-ready MCP servers from existing OpenAPI specifications using the Speakeasy CLI for rapid deployment of AI-agent-ready tool interfaces", "Centralize MCP server governance across an organization with a unified gateway providing OAuth 2.1 authentication, API key management, and bearer token support", "Deploy generated MCP servers to Cloudflare Workers, Docker, or custom infrastructure with full control over the server code and distribution" ], "health": "active" }, { "id": "contextual-ai-mcp", "name": "Contextual AI MCP Server", "description": "Official MCP server from Contextual AI for enterprise search and retrieval-augmented generation. Provides multi-agent routing with automatic reranking and intelligent document navigation that leverages hierarchical structure analysis for conversational access to knowledge bases and complex documents. Connects enterprise data sources to AI agents through grounded retrieval with source attribution. Designed for regulated industries requiring auditable, secure AI-powered search.", "category": "data", "endpoint": "Contextual AI MCP Server", "homepage_url": "https://contextual.ai", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "enterprise-search", "rag", "retrieval", "document-navigation", "reranking", "knowledge-base", "grounded-ai" ], "use_cases": [ "Connect enterprise knowledge bases to AI agents for grounded retrieval with source attribution and automatic reranking across large document collections", "Navigate complex documents through conversational AI using hierarchical structure analysis that understands document sections, tables, and cross-references", "Deploy auditable enterprise search for regulated industries where AI responses must be traceable to specific source documents with full provenance tracking" ], "health": "active" }, { "id": "datadome-mcp", "name": "DataDome MCP Protection Server", "description": "MCP server from DataDome for securing MCP infrastructure against malicious AI agents. Provides real-time protection against bot attacks, prompt injection, data exfiltration, agentic denial of service, session hijacking, and tool poisoning targeting MCP servers. Integrates via standard server-side module starting with Node.js and AWS CloudFront Lambda@Edge. Includes native FastMCP integration for Python-based MCP servers. Establishes trust scoring for agentic traffic with autopilot protection at the edge.", "category": "infrastructure", "endpoint": "DataDome MCP Server", "homepage_url": "https://datadome.co/products/mcp-protection/", "github_url": "https://github.com/DataDome/datadome-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-05", "updated": "2026-07-05", "tags": [ "security", "bot-protection", "agent-trust", "prompt-injection", "fraud-prevention", "edge-security", "fastmcp" ], "use_cases": [ "Protect MCP servers from malicious AI agents, prompt injection attacks, and data exfiltration attempts with real-time edge-level detection and blocking", "Establish trust scoring for agentic traffic to distinguish legitimate AI agent requests from automated abuse, scraping, and account takeover attempts", "Integrate MCP security into existing infrastructure using DataDome's FastMCP Python integration or Node.js server-side module for production MCP deployments" ], "health": "active" }, { "id": "mcptotal-mcp", "name": "MCPTotal Enterprise MCP Platform", "description": "Enterprise MCP security and governance platform from MCPTotal with a hub-and-gateway architecture. The Secure Hub provides centralized hosting, credential vaulting, and a vetted catalog of hundreds of curated MCP servers that employees can connect to AI models like Claude and Cursor. The Gateway acts as an AI-native firewall that monitors MCP traffic in real time and enforces access policies. Supports instant zero-conf server deployment, authentication management, and compliance controls for organizations adopting MCP at scale. Founded by security experts Gil Dabah and Dr. Ariel Shiftan.", "category": "infrastructure", "endpoint": "MCPTotal Platform", "homepage_url": "https://go.mcptotal.io", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "security", "governance", "enterprise", "gateway", "hub", "credential-vaulting", "firewall", "compliance", "zero-conf" ], "use_cases": [ "Deploy and manage secure MCP servers instantly with zero configuration, connecting AI agents to 100+ business tools through a vetted catalog with built-in credential vaulting and policy enforcement", "Monitor and govern all MCP traffic in real time using the AI-native gateway firewall to enforce access policies, audit agent-to-tool interactions, and maintain compliance across enterprise deployments", "Enable employees to safely connect Claude, Cursor, and other AI assistants to business-critical systems like Slack, Gmail, and CRMs while security teams maintain full visibility and guardrails" ], "health": "active" }, { "id": "davinci-resolve-mcp", "name": "DaVinci Resolve MCP Server", "description": "Open-source MCP server that gives AI agents full control over DaVinci Resolve Studio through the official Scripting API. Provides comprehensive tools for video editing, color grading, media pool organization, render queue management, Fusion compositing, Fairlight audio, and project lifecycle operations. Includes a local browser control panel for inspecting Resolve state and running source-safe media analysis. AI agents can browse projects, swap clips, apply color grades, set up renders, and analyze frames with AI vision. Compatible with Claude, Cursor, and other MCP clients.", "category": "media", "endpoint": "DaVinci Resolve MCP Server", "homepage_url": "https://github.com/samuelgursky/davinci-resolve-mcp", "github_url": "https://github.com/samuelgursky/davinci-resolve-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "video-editing", "davinci-resolve", "color-grading", "rendering", "fusion", "fairlight", "media-production", "post-production" ], "use_cases": [ "Edit video projects through AI agents by browsing timelines, swapping clips, setting transitions, and managing media pool assets in DaVinci Resolve via natural language commands", "Automate color grading and rendering workflows by letting AI assistants apply grades, configure render settings, and manage the render queue without manual DaVinci Resolve interaction", "Analyze video frames with AI vision through the MCP server's screenshot capture and inspection tools to identify scenes, detect issues, and guide editing decisions programmatically" ], "health": "active" }, { "id": "octotrip-mcp", "name": "OctoTrip MCP Server", "description": "Free, no-login MCP server from OctoTrip for discovering and comparing rental cars with real-time pricing from multiple providers worldwide. Enables AI agents to search rental car availability, compare prices across providers, and surface options based on location, dates, and vehicle preferences. No external data files or API keys required. Designed for AI travel planning workflows alongside hotel and flight MCP servers.", "category": "data", "endpoint": "OctoTrip MCP Server", "homepage_url": "https://octotrip.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "travel", "rental-cars", "price-comparison", "booking", "travel-planning", "no-auth" ], "use_cases": [ "Search and compare rental car availability and pricing across multiple providers worldwide through AI assistants without requiring API keys or user accounts", "Build AI-powered travel planning workflows that combine rental car discovery with hotel and flight searches for comprehensive trip planning via MCP-compatible clients", "Let AI agents surface the best rental car deals by filtering on location, pickup and return dates, vehicle type, and provider preferences in real time" ], "health": "active" }, { "id": "billingserv-mcp", "name": "BillingServ MCP Server", "description": "MCP server for the BillingServ cloud billing and invoicing platform. Allows AI assistants to look up customers, invoices, orders, packages, and reports from BillingServ installations. Designed for SaaS, hosting, VPN, and service teams that use BillingServ for subscription management, recurring payments, and direct debits. Integrates with the BillingServ REST API to surface billing data through natural language queries.", "category": "productivity", "endpoint": "BillingServ MCP Server", "homepage_url": "https://www.billingserv.com", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "billing", "invoicing", "subscription", "saas", "payments", "recurring-billing", "customer-management" ], "use_cases": [ "Query customer accounts, invoices, and subscription statuses from BillingServ through AI assistants using natural language instead of navigating billing dashboards", "Generate billing reports and surface payment data for SaaS and hosting businesses by connecting AI agents directly to BillingServ installations via MCP", "Automate billing operations by letting AI agents look up orders, packages, and recurring payment details across BillingServ accounts for customer support and financial analysis" ], "health": "active" }, { "id": "sap-gui-mcp", "name": "SAP GUI MCP Server", "description": "Open-source MCP server that exposes the SAP GUI Scripting API via FastMCP, enabling AI assistants to automate SAP GUI for Windows. Provides 57 tools covering screen discovery, field input and output, navigation between transactions, table and tree operations, and screenshot capture. Client-agnostic and works with any MCP client that can launch a local stdio server. Supports programmatic control of SAP transactions for workflow automation, data entry, and testing.", "category": "productivity", "endpoint": "SAP GUI MCP Server", "homepage_url": "https://github.com/kts982/mcp-sap-gui", "github_url": "https://github.com/kts982/mcp-sap-gui", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "sap", "erp", "gui-automation", "enterprise", "scripting-api", "windows", "fastmcp", "rpa" ], "use_cases": [ "Automate SAP GUI transactions through AI agents by navigating screens, filling fields, reading tables, and executing business workflows via natural language commands", "Perform regression testing and data validation across SAP transactions by letting AI assistants interact with the SAP GUI Scripting API programmatically without manual screen interaction", "Capture screenshots and inspect SAP GUI state through AI assistants for documentation, troubleshooting, and training purposes across enterprise SAP deployments" ], "health": "active" }, { "id": "ibm-cloud-mcp", "name": "IBM Cloud MCP Servers", "description": "Official collection of MCP servers from IBM for IBM Cloud services, announced at Think 2026. Built directly into the IBM Cloud CLI native binaries with experimental MCP features. Includes servers for IBM Cloud Logs, Cloud Object Storage, watsonx.ai, and core IBM Cloud platform operations. Enables AI assistants to interact with IBM Cloud infrastructure, query services, manage resources, and access platform capabilities through standardized MCP tools. Part of IBM's broader agentic AI strategy with watsonx.", "category": "infrastructure", "endpoint": "IBM Cloud MCP Servers", "homepage_url": "https://ibm-cloud.github.io/mcp/", "github_url": "https://github.com/IBM-Cloud/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "ibm-cloud", "cloud-platform", "watsonx", "cloud-logs", "object-storage", "enterprise", "cli" ], "use_cases": [ "Manage IBM Cloud infrastructure through AI assistants by querying services, provisioning resources, and monitoring deployments using natural language via MCP-compatible clients", "Interact with IBM Cloud Logs and Object Storage through AI agents for log analysis, troubleshooting, and data management across IBM Cloud environments", "Connect AI assistants to IBM watsonx.ai and IBM Cloud platform capabilities for agentic workflows that span machine learning, data, and cloud operations" ], "health": "active" }, { "id": "alecs-akamai-mcp", "name": "ALECS Akamai MCP Server", "description": "Community-driven MCP server for managing Akamai's edge platform through natural language. Provides tools for Property Manager configuration, Edge DNS zone and record management, certificate provisioning via CPS, WAF policy management, cache purging by URL or CP code, and reporting. Supports multi-customer Akamai account management via EdgeGrid authentication. Built with TypeScript with modular architecture and comprehensive testing. Compatible with Claude Desktop, Cursor, and VS Code.", "category": "infrastructure", "endpoint": "ALECS Akamai MCP Server", "homepage_url": "https://github.com/gamittal-ak/alecs-mcp-server-akamai", "github_url": "https://github.com/gamittal-ak/alecs-mcp-server-akamai", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "akamai", "cdn", "edge-computing", "dns", "waf", "cache-purge", "certificate-management", "edgegrid", "devops" ], "use_cases": [ "Manage Akamai CDN properties, configurations, and activation workflows through AI assistants using natural language instead of the Akamai Control Center or CLI", "Automate Edge DNS zone management, record creation, and DNS change activation across multiple Akamai accounts via EdgeGrid authentication through MCP-compatible clients", "Purge cached content by URL or CP code, manage WAF policies, and provision SSL certificates through AI agents for streamlined edge platform operations" ], "health": "active" }, { "id": "sap-concur-mcp", "name": "SAP Concur MCP Server", "description": "MCP server for SAP Concur expense management built with FastMCP and fast-agent integration. Provides tools to create, update, and delete expense entries, list expense reports, retrieve detailed report information, and perform AI-powered expense analysis via Claude. Covers the full expense lifecycle from report submission to receipt matching and corporate card charge reconciliation. Also supports travel request management and reference data lookups. Credentials configurable via command-line arguments or environment variables.", "category": "productivity", "endpoint": "SAP Concur MCP Server", "homepage_url": "https://github.com/thisislance98/concur-mcp-server", "github_url": "https://github.com/thisislance98/concur-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-06", "updated": "2026-07-06", "tags": [ "sap-concur", "expense-management", "travel", "receipts", "corporate-card", "fastmcp", "finance", "enterprise" ], "use_cases": [ "Manage expense reports through AI assistants by creating, updating, and submitting expenses to SAP Concur using natural language commands instead of the Concur web interface", "Perform AI-powered analysis of expense data by querying report details, matching receipts, and reconciling corporate card charges through Claude and other MCP-compatible clients", "Automate travel request workflows and reference data lookups by connecting AI agents directly to the SAP Concur Expense API for streamlined corporate travel and expense management" ], "health": "active" }, { "id": "nexxen-mcp", "name": "Nexxen MCP Server", "description": "MCP server from Nexxen that connects the nexAI advertising platform to external AI agents via Model Context Protocol and Agent-to-Agent (A2A) protocols. Enables AI assistants to access cross-campaign reporting, anomaly flagging, pre-launch QA, incremental spend suggestions, and audience segment queries across Nexxen's DSP, SSP, and DMP. Teams can ask plain-language questions about campaign performance and audience insights through any MCP-compatible client. One of the first adtech platforms to support both native in-platform AI and external agent integration via open protocols.", "category": "data", "endpoint": "Nexxen MCP Server", "homepage_url": "https://nexxen.com/nexxen-launches-mcp-agent-to-agent-ai-integrations-to-platform/", "x402": false, "verified": true, "protocols": [ "MCP", "A2A" ], "transport": "http", "auth": "oauth", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "advertising", "adtech", "dsp", "ssp", "dmp", "campaign-management", "audience-analytics", "programmatic", "a2a" ], "use_cases": [ "Query cross-campaign performance data and audience segments through AI assistants using natural language instead of navigating the Nexxen platform dashboard", "Automate pre-launch campaign QA and anomaly detection by connecting external AI agents to Nexxen's DSP via MCP for real-time flagging of configuration issues and spend anomalies", "Build multi-platform advertising workflows where AI agents access Nexxen's reporting, audience research, and optimization capabilities alongside other MCP-connected marketing tools" ], "health": "active" }, { "id": "codesys-mcp", "name": "CODESYS MCP Server", "description": "MCP server for the CODESYS V3 industrial automation development environment that enables AI agents to generate, analyze, and optimize IEC 61131-3 PLC code via natural language. Exposes the CODESYS Scripting Engine so AI assistants can open projects, create program organization units (POUs), write Structured Text implementations, trigger compilation, and read back errors. Supports both cloud-hosted and local LLMs. Won first place in the Software and IT category for Product of the Year 2026 by Computer and Automation magazine. Compatible with Claude Desktop, Cursor, and other MCP clients.", "category": "code", "endpoint": "CODESYS MCP Server", "homepage_url": "https://www.codesys.com/products/engineering/ai-supported-engineering/", "github_url": "https://github.com/johannesPettersson80/codesys-mcp-toolkit", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "industrial-automation", "plc", "iec-61131-3", "structured-text", "codesys", "manufacturing", "scada", "engineering" ], "use_cases": [ "Generate IEC 61131-3 PLC code from natural language descriptions through AI assistants that interact with the CODESYS development environment via MCP tools", "Automate CODESYS project scaffolding and POU creation by letting AI agents open projects, write variable declarations, and trigger compilation with automatic error correction", "Analyze and optimize existing PLC programs by connecting AI assistants to the CODESYS Scripting Engine for code review, syntax checking, and structural improvement suggestions" ], "health": "active" }, { "id": "eventify-mcp", "name": "Eventify MCP Server", "description": "MCP server from Eventify, the event management platform, enabling AI agents to create and configure events, manage attendees, build agendas, set up tickets, generate reports, handle RSVPs, and work with speakers, sponsors, and exhibitors through natural language. The server runs inside Eventify infrastructure with data staying internal under the same security and compliance framework. Launched at IMEX 2026 as the first event management platform to ship production MCP integration. Compatible with Claude, ChatGPT, and other MCP clients.", "category": "productivity", "endpoint": "Eventify MCP Server", "homepage_url": "https://eventify.io/blog/introducing-eventify-mcp-agent", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "events", "event-management", "ticketing", "attendees", "conferences", "rsvp", "speakers", "sponsors" ], "use_cases": [ "Create and configure events through AI assistants by setting up agendas, ticketing, speaker profiles, and sponsor details using natural language instead of the Eventify dashboard", "Manage attendee workflows including RSVPs, check-ins, and reporting by connecting AI agents to the Eventify platform via MCP for automated event operations", "Generate event analytics and reports through AI assistants that query attendee data, ticket sales, and engagement metrics directly from Eventify via MCP" ], "health": "active" }, { "id": "eventsourcingdb-mcp", "name": "EventSourcingDB MCP Server", "description": "Official MCP server for EventSourcingDB that connects AI agents directly to event sourcing database instances. Provides tools for reading and writing events, browsing subjects, inspecting event types, registering schemas, executing EventQL queries, and querying built-in documentation. Runs as a standalone process alongside the database with TLS encryption and token-based authentication. Available as a Docker image. Built for interactive and exploratory workflows including onboarding, prototyping, and ad-hoc event analysis.", "category": "data", "endpoint": "EventSourcingDB MCP Server", "homepage_url": "https://docs.eventsourcingdb.io/blog/2026/03/16/introducing-the-mcp-server-10-for-eventsourcingdb/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "event-sourcing", "database", "eventql", "cqrs", "event-store", "docker", "schema-registry" ], "use_cases": [ "Explore and query event sourcing data through AI assistants using natural language to read events, browse subjects, and run EventQL queries without writing code", "Onboard new team members to event-sourced systems by letting AI agents explain event types, schemas, and data flows directly from a live EventSourcingDB instance", "Prototype event-driven features by having AI assistants write events, register schemas, and validate event flows interactively through the MCP server" ], "health": "active" }, { "id": "nocobase-mcp", "name": "NocoBase MCP Server", "description": "Official MCP server for NocoBase, the open-source AI plus no-code platform for building business systems. Enables external coding agents like Claude Code, Codex, and OpenCode to perform NocoBase installation, data modeling, interface building, workflow configuration, and plugin development through MCP tools. AI agents get business context automatically and execute tasks directly inside the system with permissions, workflows, and data models. Users describe business requirements in natural language and AI creates data models, configures pages, and orchestrates workflows.", "category": "productivity", "endpoint": "NocoBase MCP Server", "homepage_url": "https://www.nocobase.com/", "github_url": "https://github.com/nocobase/mcp-server-nocobase", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "no-code", "low-code", "business-systems", "data-modeling", "workflow", "open-source", "crud", "plugins" ], "use_cases": [ "Build business applications through AI agents by describing requirements in natural language and having the agent create data models, configure pages, and set up workflows in NocoBase", "Automate NocoBase deployment and configuration using coding agents like Claude Code that install, model data, build interfaces, and configure workflows via MCP tools", "Extend NocoBase with custom plugins and integrations by letting AI assistants interact with the platform API through MCP for rapid prototyping and development" ], "health": "active" }, { "id": "complyai-mcp", "name": "ComplyAI MCP Server", "description": "Enterprise MCP server from Comply for financial services compliance, connecting compliance intelligence to any major AI platform. Enables compliance officers, advisors, and operations teams to build custom AI compliance agents using orchestrators like Claude, Microsoft Copilot, or ChatGPT without developers. Supports policy guidance agents for firm-specific answers, morning briefing agents for daily compliance summaries, and certification and onboarding agents for employee attestation workflows. Described as financial services RegTech first enterprise-grade MCP server.", "category": "productivity", "endpoint": "ComplyAI MCP Server", "homepage_url": "https://www.comply.com/solutions/firm-compliance/complyai/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "compliance", "fintech", "regtech", "financial-services", "governance", "policy", "certification", "audit" ], "use_cases": [ "Build policy guidance agents that let advisors ask compliance questions and receive instant firm-specific answers grounded in approved policies through AI assistants connected via MCP", "Automate daily compliance briefings by connecting AI agents to Comply for summaries of open pre-clearance requests, certification gaps, and regulatory alerts delivered in Slack or email", "Create certification and onboarding workflows where AI agents walk new employees through code of ethics attestations and flag exceptions using MCP-connected compliance data" ], "health": "active" }, { "id": "bitmovin-stream-lab-mcp", "name": "Bitmovin Stream Lab MCP Server", "description": "MCP server from Bitmovin that enables AI agents to perform automated video playback tests and analyze results in real time through the Stream Lab testing platform. AI agents can create and manage test setups, run tests, and analyze playback on over 30 physical test targets including Samsung, LG, and Vizio TVs, web browsers, and gaming consoles using natural language commands. Built in partnership with Alpic. Launched at CES 2026. Compatible with Claude, Codex, Cursor, Windsurf, GitHub Copilot, and ChatGPT.", "category": "media", "endpoint": "Bitmovin Stream Lab MCP Server", "homepage_url": "https://developer.bitmovin.com/playback/docs/bitmovin-stream-lab-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "video-streaming", "testing", "playback", "quality-assurance", "smart-tv", "broadcast", "ott", "ces-2026" ], "use_cases": [ "Automate video playback testing across physical devices by letting AI agents create test setups, run tests on Samsung, LG, and Vizio TVs, and analyze results through natural language via MCP", "Combine Stream Lab testing with Bitmovin Observability data to let AI agents prioritize test runs on devices experiencing the most viewer issues and measure impact of optimizations", "Speed up video QA workflows by enabling AI assistants to manage the full test lifecycle from device selection to result analysis without manual setup or integration code" ], "health": "active" }, { "id": "bitmovin-observability-mcp", "name": "Bitmovin Observability MCP Server", "description": "MCP server from Bitmovin that provides natural language access to video playback metrics, license usage, and viewer experience insights from the Bitmovin Observability analytics platform. AI agents can explore Quality of Experience data, query performance metrics, and render interactive charts and visualizations directly alongside queries. Pairs with the Stream Lab MCP Server for AI-driven testing guided by real-world QoE data. Compatible with Claude, Codex, Cursor, Windsurf, GitHub Copilot, ChatGPT, and other MCP clients.", "category": "media", "endpoint": "Bitmovin Observability MCP Server", "homepage_url": "https://developer.bitmovin.com/playback/docs/bitmovin-observability-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-07", "updated": "2026-07-07", "tags": [ "video-analytics", "observability", "qoe", "streaming", "playback-metrics", "viewer-experience", "broadcast", "monitoring" ], "use_cases": [ "Explore video playback quality metrics and viewer experience data through AI assistants using natural language queries against the Bitmovin Observability platform", "Generate interactive visualizations and charts of streaming performance data by connecting AI agents to Bitmovin Observability via MCP for real-time analytics", "Identify and prioritize viewer experience issues by letting AI agents correlate QoE data across devices, regions, and content types to guide optimization decisions" ], "health": "active" }, { "id": "revenera-mcp", "name": "Revenera MCP Server", "description": "MCP server from Revenera that connects AI agents to the FlexNet Operations entitlement management system. Enables software producers to retrieve, query, and interpret customer entitlements, product usage, and account data through natural-language questions. AI agents can identify growth opportunities, improve renewals, and reduce churn by accessing data from Revenera and connected quote-to-cash systems including billing and CRM platforms. Moves teams from reactive renewal management to proactive, data-driven decision-making.", "category": "data", "endpoint": "Revenera MCP Server", "homepage_url": "https://www.globenewswire.com/news-release/2026/07/07/3323256/0/en/Revenera-Launches-MCP-Server-to-Connect-AI-Agents-with-Monetization-Data.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "software-monetization", "entitlements", "licensing", "renewals", "churn", "flexnet", "quote-to-cash" ], "use_cases": [ "Query customer entitlement and usage data through AI assistants to identify upsell opportunities and at-risk renewals without navigating the FlexNet Operations dashboard", "Automate renewal management workflows by connecting AI agents to Revenera for proactive churn detection and data-driven account health monitoring", "Surface monetization insights across connected billing and CRM systems through natural-language questions to support cross-functional decision-making" ], "health": "active" }, { "id": "bitgo-mcp", "name": "BitGo MCP Server", "description": "Official MCP server from BitGo that integrates institutional-grade crypto infrastructure into AI-native development workflows. Enables AI agents and coding assistants to search, read, and interact with BitGo developer resources using natural language. Developers can explore wallet functionality, review transaction flows, understand staking documentation, configure webhooks, and navigate policy features. Retrieves full pages from official BitGo documentation, generates code snippets, and explains API functionality on demand. Compatible with Claude Desktop, Cursor, ChatGPT, JetBrains IDEs, VS Code, and Windsurf.", "category": "payments", "endpoint": "BitGo MCP Server", "homepage_url": "https://www.bitgo.com/en-eu/resources/blog/bitgo-launches-mcp-server-ai-powered-developer-workflows/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "crypto", "bitcoin", "wallets", "custody", "institutional", "staking", "webhooks", "blockchain" ], "use_cases": [ "Explore BitGo wallet creation, transaction flows, and staking endpoints through AI coding assistants using natural language instead of manually searching documentation", "Generate code snippets and API integration examples for BitGo custody and wallet services directly within MCP-compatible IDEs like Cursor and VS Code", "Navigate BitGo policy features and webhook configuration through AI agents to accelerate crypto application development workflows" ], "health": "active" }, { "id": "lucidworks-mcp", "name": "Lucidworks MCP Server", "description": "MCP server from Lucidworks that connects AI agents to the Lucidworks enterprise search and commerce platform. Enables AI assistants to process queries through existing relevance models, query pipelines, and security controls. E-commerce companies can launch AI assistants that work with live product information including part numbers, compatibility data, contract pricing, and technical documents. Early results show enterprises reducing AI integration timelines by up to 10x. All queries respect existing access controls and governance policies.", "category": "data", "endpoint": "Lucidworks MCP Server", "homepage_url": "https://lucidworks.com/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "enterprise-search", "commerce", "product-catalog", "relevance", "e-commerce", "query-pipelines" ], "use_cases": [ "Build AI shopping assistants that query live product catalogs with accurate part numbers, pricing, and compatibility information through the Lucidworks search platform via MCP", "Connect AI agents to enterprise search infrastructure so they can answer product and technical document questions using existing relevance models and security controls", "Reduce AI integration timelines by using the Lucidworks MCP server as a single connection point for product data, technical docs, and commerce workflows" ], "health": "active" }, { "id": "mcpsnoop-mcp", "name": "mcpsnoop", "description": "Open-source transparent proxy and terminal UI for debugging MCP traffic between AI clients and MCP servers. Described as Wireshark for MCP, it inserts into the data path and shows every JSON-RPC call, response, notification, and server stderr live in a TUI. Features include latency tracking, error highlighting, request replay against fresh server copies, stream filtering by tool, status, direction, and kind, search within frames, and a live timer on pending calls. Single-binary Go tool requiring zero configuration changes to servers. MIT licensed.", "category": "infrastructure", "endpoint": "mcpsnoop", "homepage_url": "https://github.com/kerlenton/mcpsnoop", "github_url": "https://github.com/kerlenton/mcpsnoop", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "go install github.com/kerlenton/mcpsnoop@latest", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "debugging", "proxy", "developer-tools", "monitoring", "json-rpc", "tui", "observability" ], "use_cases": [ "Debug MCP server integrations by transparently proxying all JSON-RPC traffic between AI clients and servers with live latency tracking and error highlighting", "Replay captured MCP tool calls against fresh server instances to reproduce and diagnose issues without reconnecting the AI client", "Monitor MCP server health and performance in real time through the terminal UI with filtering by tool name, request status, and call direction" ], "health": "active" }, { "id": "tronscan-mcp", "name": "TronScan MCP Server", "description": "Official MCP server for TronScan, the TRON blockchain explorer, providing AI agents with comprehensive on-chain data query capabilities. Exposes 119 tool interfaces covering blocks, accounts, contracts, transactions, tokens, super representatives, wallets, and deep analysis. Supports streamable HTTP transport with the production endpoint at mcp.tronscan.org. AI assistants like Claude and ChatGPT can query TRON blockchain data directly through natural language for seamless blockchain data interaction. Rate-limited by default with API key available for high-frequency use.", "category": "data", "endpoint": "https://mcp.tronscan.org/mcp", "homepage_url": "https://mcpdoc.tronscan.org/en/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "blockchain", "tron", "cryptocurrency", "block-explorer", "on-chain-data", "smart-contracts", "defi" ], "use_cases": [ "Query TRON blockchain data including block details, account balances, transaction histories, and smart contract states through AI assistants using natural language", "Analyze token transfers, super representative voting, and wallet activity on the TRON network via MCP-connected AI agents for research and monitoring", "Build automated blockchain monitoring workflows that access TronScan on-chain analytics and deep analysis tools through any MCP-compatible client" ], "health": "active" }, { "id": "godot-ai-mcp", "name": "Godot AI MCP Server", "description": "Production-grade MCP server for the Godot game engine that connects AI assistants directly to a live Godot editor. Provides over 120 operations across 41 MCP tools enabling AI agents to build scenes, edit nodes and scripts, wire signals, and configure UI, materials, animations, particles, cameras, and environments. Supports Claude Code, Cursor, and other MCP clients. Snap-to-install with no complex setup required. Open source and free.", "category": "code", "endpoint": "Godot AI MCP Server", "homepage_url": "https://github.com/hi-godot/godot-ai", "github_url": "https://github.com/hi-godot/godot-ai", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "game-development", "godot", "game-engine", "3d", "2d", "scenes", "scripting", "gdscript" ], "use_cases": [ "Build game scenes and configure nodes through AI assistants connected to a live Godot editor via MCP instead of manually navigating the editor UI", "Generate and edit GDScript implementations, wire signals, and set up animations by describing game behavior to AI agents in natural language", "Prototype game mechanics rapidly by letting AI agents create materials, particles, cameras, and environment setups directly in the Godot editor through MCP tools" ], "health": "active" }, { "id": "personetics-mcp", "name": "Personetics MCP Server", "description": "MCP server from Personetics that enables banks to develop agentic AI applications using customer financial intelligence data. Provides secure access to AI-driven financial behavior analysis, predictive analytics, and contextual engagement frameworks. Banks can power autonomous conversational agents, predictive nudging, and goal-based coaching experiences through MCP-connected AI assistants. Built for enterprise-grade deployment with privacy-by-design, auditability, and compliance with global financial regulations. Dramatically shortens development cycles by exposing market-proven actionable insights to AI agents.", "category": "data", "endpoint": "Personetics MCP Server", "homepage_url": "https://personetics.com/resource-center/personetics-launches-mcp-server-for-ai-driven-banking-solutions/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "banking", "fintech", "financial-intelligence", "predictive-analytics", "customer-engagement", "compliance" ], "use_cases": [ "Build AI-powered virtual financial advisors that access Personetics customer intelligence data via MCP to deliver personalized banking insights and coaching", "Deploy predictive nudging and proactive engagement features by connecting AI agents to Personetics financial behavior analysis through the MCP server", "Accelerate banking AI application development by leveraging Personetics market-proven insights via MCP instead of building financial intelligence models from scratch" ], "health": "active" }, { "id": "veeam-intelligence-mcp", "name": "Veeam Intelligence MCP Server", "description": "Open-source MCP server from Veeam that brings backup, recovery, malware detection, and compliance information into AI-driven operational workflows. Deployed locally as a Docker container with full customer governance. Integrates with Veeam Backup and Replication, Veeam ONE, and Veeam Service Provider Console. Provides a conversational interface for day-to-day operations, planned infrastructure changes, and incident response. No raw operational data is sent to external services unless explicitly chosen. Available on GitHub under open-source license.", "category": "infrastructure", "endpoint": "Veeam Intelligence MCP Server", "homepage_url": "https://www.veeam.com/blog/veeam-intelligence-mcp-server.html", "github_url": "https://github.com/veeam-ai/veeam-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "docker pull veeam/veeam-mcp-server", "added": "2026-07-08", "updated": "2026-07-08", "tags": [ "backup", "recovery", "ransomware", "compliance", "infrastructure", "monitoring", "docker", "disaster-recovery" ], "use_cases": [ "Run morning health checks on backup infrastructure through AI assistants that query Veeam Backup and Replication status via MCP for automated operational reporting", "Perform ransomware triage and root cause analysis by connecting AI agents to Veeam malware detection and compliance data through the MCP server", "Validate infrastructure changes before execution by letting AI agents check backup policies, recovery points, and compliance status across Veeam environments via MCP" ], "health": "active" }, { "id": "safari-mcp", "name": "Safari MCP Server", "description": "Official MCP server from Apple released with Safari Technology Preview 247 that connects AI coding agents to a live Safari browser window. Provides 16 built-in tools enabling agents to open pages, inspect page structure, read console output, review network activity, and capture screenshots. AI assistants like Claude and Codex can debug websites, identify Safari compatibility issues, analyze performance, check accessibility, and verify page states without relying on screenshots or manual explanations. Requires Safari Technology Preview 247 or later.", "category": "code", "endpoint": "Safari MCP Server", "homepage_url": "https://www.macrumors.com/2026/07/01/apple-releases-safari-technology-preview-247/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-09", "updated": "2026-07-09", "tags": [ "apple", "safari", "browser", "web-development", "debugging", "accessibility", "performance", "screenshots" ], "use_cases": [ "Debug web pages in Safari by connecting AI coding agents to a live browser window that can inspect DOM structure, console output, and network activity via MCP", "Identify Safari-specific compatibility issues and rendering bugs by letting AI agents compare actual browser behavior against expected page states through 16 built-in inspection tools", "Run automated accessibility and performance audits in Safari Technology Preview through AI assistants that can capture screenshots and analyze Core Web Vitals via MCP" ], "health": "active" }, { "id": "x-platform-mcp", "name": "X Platform MCP Server", "description": "Official hosted MCP server from X (formerly Twitter) that lets AI tools communicate with the X API using a user's own account permissions. Provides read access to posts, full-archive search reaching back across X's entire history, user search, and news search. Compatible with Claude, Cursor, Grok Build, and other MCP-compatible clients. Authentication uses the user's own X account permissions via OAuth, eliminating the need to build and host a custom MCP server. Launched June 30, 2026.", "category": "data", "endpoint": "X Platform MCP Server", "homepage_url": "https://techcrunch.com/2026/06/30/x-now-offers-an-mcp-server-to-make-its-platform-easier-for-ai-tools-to-use/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-09", "updated": "2026-07-09", "tags": [ "social-media", "twitter", "x", "search", "posts", "news", "full-archive" ], "use_cases": [ "Search X's full post archive through AI assistants using natural language to find historical conversations, trends, and public discourse on any topic", "Connect AI coding tools like Claude and Cursor to live X platform data for building social media analytics and monitoring applications via MCP", "Access X user search and news search capabilities through MCP-compatible clients without building custom API integrations or hosting infrastructure" ], "health": "active" }, { "id": "google-agent-platform-mcp", "name": "Google Gemini Enterprise Agent Platform MCP Server", "description": "Fully managed remote MCP server from Google Cloud that securely connects external AI agents to resources inside a Google Cloud environment. Acts as a bridge between external development tools like Claude Code and Antigravity CLI and Google Cloud architecture. Agents can call models from Model Garden, pull shared prompt templates, and manage Notebooks directly within a project. Protected by Cloud IAM Deny policies ensuring external frameworks only interact with authorized resources. Automatically enabled when the Gemini Enterprise Agent Platform API is enabled. Launched June 30, 2026.", "category": "infrastructure", "endpoint": "Google Gemini Enterprise Agent Platform MCP Server", "homepage_url": "https://cloud.google.com/blog/products/ai-machine-learning/gemini-enterprise-agent-platform-remote-mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-09", "updated": "2026-07-09", "tags": [ "google-cloud", "gemini", "enterprise", "model-garden", "notebooks", "iam", "agent-platform" ], "use_cases": [ "Connect external AI coding agents to Google Cloud resources including Model Garden models and Notebooks through a managed MCP server with IAM-based access control", "Use Claude Code or Antigravity CLI to interact with Google Cloud infrastructure via MCP without leaving the IDE, pulling prompt templates and managing notebooks", "Enforce enterprise governance on external AI agent access to Google Cloud by leveraging native IAM Deny policies through the Agent Platform MCP server" ], "health": "active" }, { "id": "press-ranger-mcp", "name": "Press Ranger MCP Server", "description": "MCP server from Press Ranger, the AI-first press release distribution platform, that connects AI assistants to a complete press release workflow. Users describe an announcement in plain language and receive an on-brand press release written directly into their Press Ranger account, formatted to distribution standards and ready to review and publish. Supports the full lifecycle from drafting to distribution. Compatible with Claude, ChatGPT, OpenAI Codex, and other MCP-compatible clients. Available on every Press Ranger account including free plans with one-click OAuth setup. Launched July 9, 2026.", "category": "data", "endpoint": "Press Ranger MCP Server", "homepage_url": "https://www.globenewswire.com/news-release/2026/07/09/3325174/0/en/Press-Ranger-Launches-the-First-MCP-Server-for-Press-Release-Distribution.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "press-release", "pr", "distribution", "media", "communications", "content-creation", "publishing" ], "use_cases": [ "Draft and distribute press releases through AI assistants by describing announcements in natural language, with output formatted to distribution standards in the Press Ranger account via MCP", "Manage the full press release lifecycle from creation through distribution using Claude, ChatGPT, or other MCP-compatible AI clients connected to Press Ranger", "Automate PR workflows by connecting AI coding and writing tools to Press Ranger via MCP for rapid press release generation and publication" ], "health": "active" }, { "id": "oshyn-mcp", "name": "Oshyn MCP Server", "description": "Free MCP server from Oshyn, the digital technology agency, that provides AI assistants with access to 25 years of digital experience platform implementation expertise. Includes the Discoverability Assessment tool previously reserved for advisory clients, Site Reliability Reports that scan websites for performance, accessibility, and security issues, the DXP MatchMaker for narrowing down platform shortlists, and a Budget Estimator for generating realistic project requirements. Compatible with Claude, ChatGPT, Cursor, and other MCP-compatible clients. Launched July 7, 2026.", "category": "data", "endpoint": "Oshyn MCP Server", "homepage_url": "https://www.newswire.com/news/oshyn-launches-mcp-server-bringing-no-cost-dxp-strategy-tools-directly-22820375", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "dxp", "digital-experience", "website-audit", "accessibility", "performance", "consulting", "cms" ], "use_cases": [ "Run website reliability audits covering performance, discoverability, accessibility, and security through AI assistants connected to Oshyn's diagnostic tools via MCP", "Navigate the DXP MatchMaker questionnaire through natural language to identify the best digital experience platform for your organization's needs via MCP", "Generate realistic budget estimates for website implementations and migrations using Oshyn's Budget Estimator through AI assistants connected via MCP" ], "health": "active" }, { "id": "figma-dev-mode-mcp", "name": "Figma Dev Mode MCP Server", "description": "Official MCP server from Figma that brings design context directly into developer coding workflows. Enables agentic coding tools like Claude Code, Cursor, Windsurf, and VS Code Copilot to read Figma designs and generate design-informed code. Agents can access component information, design tokens, variables, stylings, and multi-layer application flows from Figma files. Supports creating new atomic components with proper variables and building out complex design-to-code workflows. Expanded with skills and MCP connectors at Config 2026 on June 24, 2026.", "category": "code", "endpoint": "Figma Dev Mode MCP Server", "homepage_url": "https://www.figma.com/blog/introducing-figma-mcp-server/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "figma", "design", "design-to-code", "ui", "components", "developer-tools", "frontend" ], "use_cases": [ "Generate design-informed frontend code by connecting AI coding agents to Figma designs via MCP, accessing component structures, tokens, and styling information directly", "Build new UI components with proper variables, stylings, and design system compliance by letting AI agents read Figma design specs through the Dev Mode MCP server", "Streamline design-to-code handoff by enabling Claude Code, Cursor, or Windsurf to inspect multi-layer Figma application flows and produce accurate implementations via MCP" ], "health": "active" }, { "id": "mini-course-generator-mcp", "name": "Mini Course Generator MCP Server", "description": "MCP server from Mini Course Generator, the AI-powered course creation platform, that turns AI assistants into an agentic LMS. AI agents can create entire courses, add interactive learning activities, analyze learner progress, update lessons, and email learners automatically. Users describe what they want to teach in natural language, and the AI builds it including genuinely interactive elements personalized to learner needs. Supports SCORM content generation and upload. Compatible with Claude, ChatGPT, and other MCP-compatible clients. Launched June 11, 2026.", "category": "data", "endpoint": "Mini Course Generator MCP Server", "homepage_url": "https://minicoursegenerator.com/blog/product-update-mini-course-generator-mcp-server-is-live/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "lms", "e-learning", "courses", "education", "training", "scorm", "interactive" ], "use_cases": [ "Create complete interactive online courses through AI assistants by describing learning objectives in natural language, with the MCP server handling course structure and interactive elements", "Analyze learner progress and engagement data through AI assistants connected to Mini Course Generator via MCP for data-driven course improvement", "Generate and upload SCORM-compliant content directly from AI tools into the Mini Course Generator platform via MCP for integration with existing LMS systems" ], "health": "active" }, { "id": "aws-roda-mcp", "name": "AWS Registry of Open Data MCP Server", "description": "Open source MCP server from AWS that brings AI-powered dataset discovery to the Registry of Open Data on AWS (RODA). Researchers can ask questions in natural language and get back relevant datasets, metadata, and data previews from over 1,100 high-value datasets spanning satellite imagery, life sciences, climate, geospatial, and more from 400+ organizations. Exposes tools for discovery, exploration, and evaluation of open datasets. Compatible with Kiro, Claude Code, and any MCP-compatible AI assistant. Released under Apache 2.0 license. Announced July 2026.", "category": "data", "endpoint": "AWS Registry of Open Data MCP Server", "homepage_url": "https://aws.amazon.com/blogs/opensource/introducing-mcp-server-for-registry-of-open-data-on-aws/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "aws", "open-data", "datasets", "research", "science", "climate", "genomics", "satellite" ], "use_cases": [ "Discover open datasets for research by asking natural language questions like 'find datasets to study ocean temperature' and getting matching results from the Registry of Open Data on AWS via MCP", "Explore dataset metadata, list S3 bucket contents, and preview sample files from 1,100+ open datasets through AI assistants connected to the RODA MCP server", "Evaluate datasets for research projects by inspecting licensing, schema details, and data samples through Claude Code or Kiro without manual browsing of the AWS open data catalog" ], "health": "active" }, { "id": "granola-mcp", "name": "Granola MCP Server", "description": "Official MCP server from Granola, the AI-powered meeting notepad, that connects meeting notes to AI assistants. Once connected, AI tools can access and query meeting notes in real time, including notes in folders and notes shared by teammates. Eliminates the need to manually copy and paste meeting context between applications. AI agents can search across meeting history, extract action items, and reference discussion details from within Claude, ChatGPT, or any MCP-compatible client. Launched February 2026 with ongoing updates including folder and shared note support.", "category": "data", "endpoint": "Granola MCP Server", "homepage_url": "https://www.granola.ai/blog/granola-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "meetings", "notes", "productivity", "ai-notetaker", "collaboration", "action-items", "search" ], "use_cases": [ "Query meeting notes in real time from Claude, ChatGPT, or other AI assistants to reference discussion context without switching to the Granola app via MCP", "Search across meeting history and extract action items, decisions, and follow-ups through AI assistants connected to Granola meeting data via MCP", "Access shared team meeting notes and folder-organized notes through AI workflows for cross-project context and preparation via the Granola MCP server" ], "health": "active" }, { "id": "aws-healthlake-mcp", "name": "AWS HealthLake MCP Server", "description": "Open source MCP server from AWS Labs that provides natural language interfaces to AWS HealthLake FHIR resources for healthcare AI agents. Supports full CRUDS operations on FHIR resources with advanced search including chained parameters, _include, and _revinclude. Automatically discovers available HealthLake datastores and exposes them as MCP resources without manual configuration. Includes a read-only mode for safe data inspection. Healthcare agents can summarize patient information, manage clinical records, and coordinate across health systems. Released under Apache 2.0 license.", "category": "data", "endpoint": "AWS HealthLake MCP Server", "homepage_url": "https://aws.amazon.com/blogs/industries/building-healthcare-ai-agents-with-open-source-aws-healthlake-mcp-server/", "github_url": "https://github.com/awslabs/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-10", "updated": "2026-07-10", "tags": [ "aws", "healthcare", "fhir", "hl7", "clinical", "ehr", "patient-data", "medical" ], "use_cases": [ "Summarize patient information for physicians using natural language through AI agents connected to AWS HealthLake FHIR resources via MCP", "Search and retrieve clinical records using FHIR-compliant queries including chained parameters through AI assistants without writing manual API calls via the HealthLake MCP server", "Build healthcare AI agents that can read, create, and update FHIR resources across automatically discovered HealthLake datastores with read-only safety mode via MCP" ], "health": "active" }, { "id": "omneky-mcp", "name": "Omneky MCP Server", "description": "MCP server from Omneky, the autonomous AI advertising platform, that opens its creative generation engine to AI agents and developer pipelines. Send a brand URL and receive finished, on-brand ad creatives rendered in every major aspect ratio including 1:1, 4:5, 9:16, and 16:9. Supports multi-variant output with UGC-style and short-form video, automatic regeneration driven by performance data and creative scoring, and zero-prompt operation. Compatible with Claude, ChatGPT, and any MCP-compatible client. Launched July 10, 2026.", "category": "data", "endpoint": "Omneky MCP Server", "homepage_url": "https://www.prnewswire.com/news-releases/omneky-launches-public-api-and-mcp-server-bringing-autonomous-ad-creative-generation-to-any-platform-or-ai-agent-302822766.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "advertising", "creative", "ad-generation", "marketing", "video", "ugc", "brand", "commerce" ], "use_cases": [ "Generate on-brand ad creatives in every major aspect ratio by passing a brand URL to the Omneky MCP server, receiving finished multi-format ads without any prompt engineering", "Embed autonomous ad creative generation into commerce platforms and agency pipelines by connecting to Omneky via MCP for white-label multi-variant output with performance-driven regeneration", "Ask an AI assistant to create launch ads for a product page and receive finished multi-format creative including UGC-style and short-form video through the Omneky MCP server" ], "health": "active" }, { "id": "salesloft-mcp", "name": "Salesloft MCP Server", "description": "Official MCP server from Salesloft, the revenue workflow platform, that opens live revenue execution and forecasting intelligence to AI agents. Integrates Clari forecasting and pipeline insights directly with Salesloft execution data, enabling AI assistants to query deal health, pipeline status, forecast accuracy, and engagement metrics. Native in Claude's connector directory with no custom setup required. Also supports ChatGPT, Microsoft Copilot, and Google Gemini. Launched April 2026, expanded with native connectors July 9, 2026.", "category": "data", "endpoint": "Salesloft MCP Server", "homepage_url": "https://www.salesloft.com/company/newsroom/clari-salesloft-forecasting-execution-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "sales", "revenue", "forecasting", "crm", "pipeline", "engagement", "clari" ], "use_cases": [ "Query live deal health, pipeline status, and forecast accuracy through AI assistants connected to Salesloft revenue data via MCP without switching to the Salesloft dashboard", "Connect Clari forecasting insights with Salesloft execution workflows through AI agents to identify at-risk deals and take corrective action in the same conversation via MCP", "Analyze sales engagement metrics and revenue pipeline trends using natural language in Claude, ChatGPT, or Copilot connected to the Salesloft MCP server" ], "health": "active" }, { "id": "affinity-mcp", "name": "Affinity MCP Server", "description": "Official MCP server from Affinity, the relationship intelligence CRM for private capital. Provides AI assistants with read and write access to deal flow, relationship data, companies, people, opportunities, interactions, and notes. Supports creating and updating records, logging meetings and calls, retrieving saved list views, auditing field update history, and surfacing relationship intelligence. Available through Claude's Anthropic Connector directory and ChatGPT App Store with no API keys or local setup required. Launched April 28, 2026 with major tool expansion in June 2026.", "category": "data", "endpoint": "Affinity MCP Server", "homepage_url": "https://www.affinity.co/blog/affinity-mcp-server-beta", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "crm", "private-equity", "venture-capital", "relationship-intelligence", "deal-flow", "contacts", "finance" ], "use_cases": [ "Query deal flow and relationship data across your private capital firm through AI assistants connected to Affinity CRM via MCP for instant pipeline visibility", "Create and update company, person, and opportunity records and log meetings and calls directly in Affinity through natural language commands in Claude or ChatGPT via MCP", "Surface relationship intelligence, audit field update history, and search notes and files across the firm using AI agents connected to Affinity via the MCP server" ], "health": "active" }, { "id": "dollhouse-mcp", "name": "DollhouseMCP Server", "description": "Free open source MCP server for dynamic custom persona management with a public GitHub collection of personas, skills, templates, agents, memories, and ensembles for AI models. Create and manage custom personas, skills, and agent configurations that work across platforms and follow users wherever they work. Includes a local portfolio system at ~/.dollhouse/portfolio/ for organizing elements. Compatible with Claude Code, Claude Desktop, Cursor, Gemini, Codex, and local LLMs. Licensed under AGPL-3.0 with commercial licensing available.", "category": "code", "endpoint": "DollhouseMCP Server", "homepage_url": "https://dollhousemcp.com/", "github_url": "https://github.com/DollhouseMCP/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "persona", "skills", "templates", "agents", "memory", "customization", "open-source" ], "use_cases": [ "Create and manage custom AI personas, skills, and agent configurations that persist across sessions and platforms using the DollhouseMCP local portfolio system via MCP", "Browse and install community-contributed personas, skills, templates, and agent configurations from the DollhouseMCP public collection directly through AI assistants via MCP", "Build ensemble configurations combining multiple personas, skills, and memories for specialized AI workflows across Claude Code, Cursor, Gemini, and other MCP-compatible clients" ], "health": "active" }, { "id": "buildbetter-mcp", "name": "BuildBetter MCP Server", "description": "Official MCP server from BuildBetter, the customer evidence platform for product teams, that provides AI assistants with secure read-only access to customer calls, signals, contacts, and insights. Unifies internal data from call recordings, Slack conversations, and team meetings with external customer signals across 100+ data sources. No API keys or local setup required. Connect with OAuth, sign in, and start querying in 2 minutes. Compatible with Claude, ChatGPT, and other MCP-compatible clients.", "category": "data", "endpoint": "BuildBetter MCP Server", "homepage_url": "https://docs.buildbetter.ai/pages/MCP/overview", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "product-management", "customer-evidence", "meetings", "calls", "insights", "feedback", "saas" ], "use_cases": [ "Query customer call recordings, meeting transcripts, and feedback signals through AI assistants connected to BuildBetter via MCP for instant product research context", "Search across 100+ integrated data sources including Slack conversations, support tickets, and team meetings to surface customer evidence for product decisions via the BuildBetter MCP server", "Ground AI assistants in real customer conversations and signals for product roadmap planning and feature prioritization using BuildBetter's customer evidence platform via MCP" ], "health": "active" }, { "id": "meeting-baas-mcp", "name": "Meeting BaaS MCP Server", "description": "Open source MCP server from Meeting BaaS (Bots as a Service) that enables AI assistants to create meeting bots, search transcripts, and manage meeting recordings. Supports creating and joining meeting bots with automatic recording and transcription, searching and analyzing transcripts for specific content or speakers, connecting Google and Microsoft calendars for event management, and generating AI-powered QR code images for bot avatars. Deployable locally or on your own infrastructure. Compatible with Claude Desktop, Cursor, and other MCP clients.", "category": "data", "endpoint": "Meeting BaaS MCP Server", "homepage_url": "https://www.meetingbaas.com/en/projects/mcp-tools", "github_url": "https://github.com/Meeting-Baas/meeting-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "meetings", "transcription", "recording", "bots", "calendar", "video-conferencing", "open-source" ], "use_cases": [ "Deploy meeting bots to automatically record and transcribe video conferences through AI assistants connected to Meeting BaaS via MCP with calendar integration", "Search and analyze meeting transcripts for specific content, speakers, or action items through Claude or Cursor connected to Meeting BaaS recordings via MCP", "Automate meeting intelligence workflows including bot scheduling, transcript analysis, and highlight extraction using AI agents connected to Meeting BaaS via MCP" ], "health": "active" }, { "id": "azure-devops-mcp", "name": "Azure DevOps MCP Server", "description": "Official MCP server from Microsoft that brings Azure DevOps data directly to AI agents. Available as both a local stdio server and a hosted remote server using streamable HTTP transport with Microsoft Entra authentication. Provides AI agents with access to work items, pull requests, pipelines, repos, wikis, and test plans. The remote server requires no local installation and is available inside Microsoft Foundry. Supports scoping which tools agents can access for controlled operations. Open source under MIT license. Remote server entered public preview March 2026.", "category": "code", "endpoint": "Azure DevOps MCP Server", "homepage_url": "https://devblogs.microsoft.com/devops/azure-devops-remote-mcp-server-public-preview/", "github_url": "https://github.com/microsoft/azure-devops-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "azure", "devops", "microsoft", "ci-cd", "work-items", "pull-requests", "pipelines", "developer-tools" ], "use_cases": [ "Query and manage Azure DevOps work items, pull requests, and pipeline runs through AI coding agents connected via the remote MCP server with Microsoft Entra authentication", "Access repos, wikis, and test plans from Azure DevOps through Claude Code, Cursor, or VS Code Copilot via the hosted MCP server without any local installation", "Build AI-powered DevOps workflows that inspect pipeline status, create work items, and review pull requests using the Azure DevOps MCP server inside Microsoft Foundry" ], "health": "active" }, { "id": "featured-pr-mcp", "name": "Featured MCP Server", "description": "Official MCP server from Featured, the AI co-pilot for PR professionals, that connects AI assistants directly to Featured accounts for earned media workflows. PR teams can manage media opportunities, draft expert responses, track placements, and streamline pitching workflows through natural language. Supports the full PR lifecycle from opportunity discovery through response submission. Compatible with Claude, Cursor, VS Code, and other MCP-compatible clients. Launched with general availability on July 7, 2026.", "category": "data", "endpoint": "Featured MCP Server", "homepage_url": "https://www.globenewswire.com/news-release/2026/07/07/3323391/0/en/Featured-Launches-an-MCP-Server-Bringing-AI-Agents-to-PR-Agencies.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-11", "updated": "2026-07-11", "tags": [ "public-relations", "pr", "earned-media", "pitching", "media", "communications", "journalism" ], "use_cases": [ "Discover and respond to media opportunities through AI assistants connected to Featured via MCP for streamlined PR pitching and expert response workflows", "Draft expert responses to journalist queries and manage the full earned media lifecycle using natural language in Claude, Cursor, or VS Code connected to Featured via MCP", "Track media placements and manage PR agency workflows across multiple clients through AI assistants connected to Featured accounts via the MCP server" ], "health": "active" }, { "id": "incident-io-mcp", "name": "incident.io MCP Server", "description": "Official remote MCP server from incident.io, the incident management platform, that gives AI assistants direct access to incident data, alerts, on-call schedules, escalation paths, and operational analysis. Exposes 30+ tools across incident analysis, alert management, on-call operations, and AI investigation access. Supports OAuth2 for interactive users and API key auth for programmatic agents. No local setup required. Available on Team, Pro, and Enterprise plans. Public beta since March 2026.", "category": "data", "endpoint": "https://mcp.incident.io/mcp", "homepage_url": "https://incident.io/changelog/remote-mcp-server", "github_url": "https://github.com/incident-io/incidentio-mcp-golang", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "incident-management", "on-call", "alerts", "escalation", "devops", "sre", "observability" ], "use_cases": [ "Query incidents, analyse alerts, and check who is on call through AI assistants connected to incident.io via the remote MCP server with OAuth or API key authentication", "Run deep operational analysis across incident history, alert noise patterns, and escalation paths using natural language in Claude or other MCP-compatible clients connected to incident.io", "Manage escalations and acknowledge pages directly from AI coding assistants connected to incident.io via MCP without switching to the incident.io dashboard" ], "health": "active" }, { "id": "api-to-mcp", "name": "API to MCP", "description": "Hosted platform that turns any REST, GraphQL, SaaS, or internal API into a production remote MCP server in minutes. Build visually from a dashboard or let an AI agent create, test, and deploy tools from API docs. Supports OAuth2 Authorization Code, Client Credentials, Bearer token, API key, and Basic Auth for upstream APIs. Includes workflow tools that compose multiple API calls into a single MCP tool, response shaping for cleaner agent output, encrypted credential storage, forkable snapshots, and usage tracking. End users connect live MCP servers to Claude, ChatGPT, Codex, Cursor, VS Code, or custom agents.", "category": "infrastructure", "endpoint": "API to MCP", "homepage_url": "https://apitomcp.ai/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "api", "rest", "graphql", "hosted", "no-code", "platform", "saas", "infrastructure" ], "use_cases": [ "Convert any existing REST or GraphQL API into a hosted remote MCP server without writing backend code using the API to MCP visual builder or AI agent builder", "Compose multi-step API workflows into single MCP tools with response shaping so AI agents receive clean structured output from complex upstream API orchestration", "Deploy authenticated MCP servers with OAuth, API key, or Bearer token upstream auth and share forkable snapshots with team members for rapid iteration on agent tooling" ], "health": "active" }, { "id": "apollo-graphql-mcp", "name": "Apollo MCP Server", "description": "Official MCP server from Apollo GraphQL that bridges AI applications and GraphQL APIs by translating GraphQL operations into MCP tools that AI models can discover and use. Supports zero-code MCP tool creation from GraphQL schema or operations, native REST and GraphQL support via Apollo Connectors, deterministic execution with built-in policy enforcement limiting AI to pre-approved operations, and AI-native development for automatically discovering new capabilities across API footprints. Also supports MCP Apps and the OpenAI Apps SDK. Open source under MIT license.", "category": "code", "endpoint": "Apollo MCP Server", "homepage_url": "https://www.apollographql.com/apollo-mcp-server", "github_url": "https://github.com/apollographql/apollo-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "graphql", "api", "apollo", "schema", "developer-tools", "open-source", "ai-native" ], "use_cases": [ "Instantly expose GraphQL schema operations as MCP tools for AI agents without writing procedural code using Apollo MCP Server's zero-code tool creation from schema introspection", "Connect AI assistants to enterprise APIs through Apollo's unified GraphQL layer with policy enforcement ensuring agents only invoke pre-approved operations and surface area", "Build AI-powered developer workflows that automatically discover and orchestrate GraphQL and REST APIs across an organization's complete API footprint via Apollo MCP Server" ], "health": "active" }, { "id": "zuplo-mcp-gateway", "name": "Zuplo MCP Gateway", "description": "Enterprise MCP gateway from Zuplo that sits in front of multiple MCP servers, adding OAuth authorization, upstream credential brokering, tool curation, governance, and observability through a single governed endpoint. Ships a complete OAuth 2.0 authorization server written to the MCP spec with PKCE S256 enforcement. Supports per-user credential brokering where end-users complete upstream OAuth flows while the gateway refreshes tokens per session with per-user revocation and audit logging. Public beta since June 2, 2026.", "category": "infrastructure", "endpoint": "Zuplo MCP Gateway", "homepage_url": "https://zuplo.com/mcp-gateway", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "gateway", "oauth", "security", "governance", "enterprise", "credential-brokering", "observability" ], "use_cases": [ "Federate multiple MCP servers behind a single governed endpoint with OAuth authorization, credential brokering, and tool curation using the Zuplo MCP Gateway", "Ship MCP servers to customer AI agents with enterprise-grade OAuth 2.0 authorization, per-user credential management, and full audit logging via Zuplo's hosted gateway", "Govern employee MCP server access with centralized security policies, PKCE enforcement, and real-time observability across all connected AI tools through the Zuplo MCP Gateway" ], "health": "active" }, { "id": "mintmcp-gateway", "name": "MintMCP Gateway", "description": "Enterprise-grade MCP gateway and governance platform that provides centralized security, observability, authentication, and compliance controls for AI agents connecting to internal systems. Features Virtual MCP Bundles for team-specific endpoints exposing minimum required tools, Agent Bundles with M2M auth and scoped tools, one-click deployment transforming local STDIO servers into production services with automatic OAuth wrapping, native Snowflake and Elasticsearch integrations, and SCIM-driven membership with rule-based policy. SOC 2 Type II audited.", "category": "infrastructure", "endpoint": "MintMCP Gateway", "homepage_url": "https://www.mintmcp.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "gateway", "enterprise", "governance", "security", "compliance", "soc2", "snowflake", "elasticsearch" ], "use_cases": [ "Deploy and govern enterprise MCP infrastructure at scale with team-specific Virtual MCP Bundles that expose only minimum required tools per team via MintMCP's SOC 2 Type II audited gateway", "Transform local STDIO-based MCP servers into production remote services with one-click deployment and automatic OAuth wrapping through the MintMCP platform", "Give internal AI agents first-class identities with M2M authentication and scoped tool access using Agent Bundles while maintaining full audit logging and SCIM-driven membership governance" ], "health": "active" }, { "id": "kong-mcp-gateway", "name": "Kong MCP Gateway", "description": "Enterprise MCP gateway from Kong Inc. that standardizes, secures, and observes AI agent workflows at scale. Part of the Kong AI Gateway 3.14+ release which supports LLM traffic management, MCP server connectivity, API management, and agent-to-agent (A2A) communication in a single gateway. Includes Kong MCP Registry for discovering and governing MCP servers within Kong Konnect, federated SSO, OAuth 2.0, multi-region failover, and comprehensive audit logging. Announced February 2026 with Agent Gateway capabilities added April 2026.", "category": "infrastructure", "endpoint": "Kong MCP Gateway", "homepage_url": "https://konghq.com/blog/product-releases/enterprise-mcp-gateway", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "gateway", "enterprise", "api-management", "a2a", "security", "registry", "kong", "multi-region" ], "use_cases": [ "Manage MCP server connectivity alongside LLM traffic and agent-to-agent communication through a single enterprise Kong AI Gateway with centralized governance and audit logging", "Register, discover, and govern MCP servers and AI-native tools across the organization using the Kong MCP Registry within Kong Konnect for centralized agent discovery", "Secure enterprise AI agent workflows with federated SSO, OAuth 2.0, multi-region failover, and comprehensive observability through Kong's production-grade MCP Gateway" ], "health": "active" }, { "id": "manufact-mcp-use", "name": "Manufact (mcp-use)", "description": "Open-source SDK and cloud platform for building and deploying MCP servers, clients, and agents. The mcp-use SDK provides a CLI, dev server, Inspector, and managed deploys for spinning up and aggregating MCP servers through a single endpoint. Supports TypeScript and Python with integrations for LangChain, OpenAI, and Anthropic. The cloud platform adds hosted MCP server deployment, authentication, and scaling. YC S25 backed with over 6,000 GitHub stars and 120,000 downloads. Used by teams at NASA, NVIDIA, and SAP.", "category": "infrastructure", "endpoint": "Manufact MCP", "homepage_url": "https://manufact.com/", "github_url": "https://github.com/mcp-use", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "sdk", "infrastructure", "open-source", "cloud", "deployment", "developer-tools", "typescript", "python" ], "use_cases": [ "Build and deploy custom MCP servers in TypeScript or Python using the mcp-use SDK with CLI, dev server, and Inspector for rapid iteration and testing", "Aggregate multiple MCP servers through a single hosted endpoint with managed authentication and scaling using the Manufact cloud platform for production agent deployments", "Connect any LLM to MCP tools through the mcp-use open-source framework with native LangChain and OpenAI integration for building custom AI agents" ], "health": "active" }, { "id": "composio-mcp", "name": "Composio MCP Server", "description": "Agent-integration platform providing 1,000+ managed MCP integrations across 500+ apps with built-in OAuth handling, automatic token refresh, and RBAC controls. Features a Tool Router for dynamic tool discovery through a single endpoint, sandboxed execution, and a centralized MCP Gateway for auth, observability, rate limiting, and governance. Integrates natively with OpenAI, Anthropic, LangChain, AutoGen, and Claude Agent SDK. SOC2/ISO certified. Free tier includes 20,000 tool calls per month.", "category": "infrastructure", "endpoint": "Composio MCP", "homepage_url": "https://composio.dev/mcp-gateway", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "integration", "platform", "oauth", "gateway", "tools", "saas", "multi-app", "agent-framework" ], "use_cases": [ "Connect AI agents to 500+ apps through a single MCP endpoint with managed OAuth, automatic token refresh, and dynamic tool discovery using Composio's Tool Router", "Build production AI agents with integrated MCP tooling across CRM, project management, communication, and developer tools using Composio's framework-native SDKs for OpenAI, Anthropic, and LangChain", "Govern agent tool access with role-based controls, rate limiting, sandboxed execution, and full observability through Composio's centralized MCP Gateway" ], "health": "active" }, { "id": "truefoundry-mcp-gateway", "name": "TrueFoundry MCP Gateway", "description": "Enterprise AI gateway and MCP control plane that manages access, discovery, and orchestration of MCP servers across organizations. Features Virtual MCP Server abstraction for aggregating tools into logical managed endpoints, OAuth 2.0 Identity Injection for on-behalf-of user actions, federated SSO, dynamic discovery, multi-region failover, and end-to-end tracing with metadata tagging for compliance. Supports the 2026-07-28 spec including MCP Apps and Tasks extensions for interactive UIs and long-running workflows.", "category": "infrastructure", "endpoint": "TrueFoundry MCP Gateway", "homepage_url": "https://www.truefoundry.com/mcp-gateway", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-12", "updated": "2026-07-12", "tags": [ "gateway", "enterprise", "ai-gateway", "orchestration", "governance", "multi-region", "observability", "mcp-apps" ], "use_cases": [ "Centralize access to all organization MCP servers through TrueFoundry's Virtual MCP Server abstraction with OAuth 2.0 Identity Injection ensuring agent actions are attributed to individual users", "Govern enterprise AI agent tool access with federated SSO, dynamic server discovery, role-based policies, and end-to-end tracing with compliance-ready audit logging via TrueFoundry", "Deploy MCP infrastructure supporting the 2026-07-28 spec extensions including MCP Apps for interactive server-rendered UIs and Tasks for durable long-running agent workflows" ], "health": "active" }, { "id": "microsoft-dataverse-mcp", "name": "Microsoft Dataverse MCP Server", "description": "Official MCP server from Microsoft that connects AI coding agents to the Dataverse business data platform across Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, GitHub Copilot, and Cursor. Routes every request through 15 named, auditable MCP tools while inheriting the calling user's existing Dataverse security role. Part of a catalog of 60+ ready MCP servers across the Microsoft ecosystem. Supports OAuth authentication with per-user identity and full audit logging. Coding-agent plugin expanded to Claude, Cursor, and GitHub Copilot as of July 6, 2026.", "category": "data", "endpoint": "Microsoft Dataverse MCP", "homepage_url": "https://www.microsoft.com/en-us/power-platform/blog/2026/07/06/dataverse-july2026/", "github_url": "https://github.com/microsoft/mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "microsoft", "dataverse", "power-platform", "enterprise", "business-data", "copilot", "governance" ], "use_cases": [ "Query and manage business data in Microsoft Dataverse from AI coding agents in Claude, Cursor, or GitHub Copilot through 15 auditable MCP tools with per-user security role enforcement", "Connect enterprise AI agents to CRM, ERP, and business application data across the Microsoft 365 ecosystem using Dataverse MCP with OAuth identity and full audit logging", "Leverage Microsoft's catalog of 60+ certified MCP servers to give AI agents governed access to Power Platform, Dynamics 365, and custom Dataverse tables without custom API integration" ], "health": "active" }, { "id": "digi-remote-manager-mcp", "name": "Digi Remote Manager MCP Server", "description": "Official MCP server from Digi International that connects AI assistants to Digi Remote Manager (DRM) and Genesis for IoT and WWAN device fleet management. Enables natural language queries against device fleets, automated configuration workflows, troubleshooting, and operational analytics across cellular router and IoT gateway deployments. Built with enterprise-grade security and SOC 2 Type 2 compliance. Supports integration with Claude and other MCP-compatible AI clients. Announced February 25, 2026.", "category": "data", "endpoint": "Digi Remote Manager MCP", "homepage_url": "https://www.digi.com/company/press-releases/2026/digi-launches-mcp-server-to-power-ai-workflows", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "iot", "device-management", "networking", "cellular", "wwan", "enterprise", "soc2", "fleet-management" ], "use_cases": [ "Query and manage IoT device fleets through natural language in AI assistants connected to Digi Remote Manager via MCP for real-time monitoring, configuration, and troubleshooting", "Automate cellular router and IoT gateway configuration workflows across distributed enterprise deployments using AI agents connected to Digi's SOC 2 compliant MCP server", "Generate operational analytics and diagnostic insights across WWAN connectivity deployments by giving AI assistants direct access to Digi Remote Manager fleet data via MCP" ], "health": "active" }, { "id": "aperag-mcp", "name": "ApeRAG MCP Server", "description": "Production-ready GraphRAG platform from ApeCloud with built-in MCP server support. Combines five index types — vector, full-text, graph, summary, and vision — for hybrid retrieval across documents and knowledge bases. Features deeply modified LightRAG with entity normalization for cleaner knowledge graphs, multi-modal document parsing powered by MinerU, and built-in AI agents with MCP tool support. Deploys on Kubernetes with Helm charts and KubeBlocks integration for PostgreSQL, Redis, Qdrant, Elasticsearch, and Neo4j. Open source with 1.3K GitHub stars.", "category": "ai", "endpoint": "ApeRAG MCP", "homepage_url": "https://rag.apecloud.com/", "github_url": "https://github.com/apecloud/ApeRAG", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "rag", "graphrag", "knowledge-base", "vector-search", "open-source", "kubernetes", "document-parsing", "hybrid-search" ], "use_cases": [ "Build production knowledge bases with hybrid retrieval combining GraphRAG, vector search, full-text search, and vision-based search through the ApeRAG MCP server", "Give AI agents access to enterprise document collections with semantic search, graph-based knowledge reasoning, and natural-language querying via ApeRAG's built-in MCP integration", "Deploy a self-hosted RAG platform on Kubernetes with multi-modal document parsing and MCP-compatible AI agent tooling for privacy-sensitive enterprise knowledge management" ], "health": "active" }, { "id": "mcp-local-rag", "name": "MCP Local RAG", "description": "Privacy-first local RAG server for developers that runs entirely on-device with zero cloud dependencies. Combines semantic search via embeddings with keyword boost for exact technical terms like function names, error codes, and class names. Uses smart semantic chunking that splits documents by meaning rather than character count. Supports PDF, DOCX, and TXT files with optional vision-language model for PDF visual parsing. Zero-friction setup via npx with no Docker or Python required. Works fully offline after initial model download. 340 GitHub stars.", "category": "ai", "endpoint": "MCP Local RAG", "homepage_url": "https://github.com/shinpr/mcp-local-rag", "github_url": "https://github.com/shinpr/mcp-local-rag", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y mcp-local-rag", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "rag", "local", "privacy", "semantic-search", "offline", "document-search", "open-source", "developer-tools" ], "use_cases": [ "Search local documents with semantic understanding and keyword boosting for technical terms using a fully private on-device RAG server with zero cloud dependencies", "Index code documentation, technical specs, and reference materials locally for AI-assisted development in Claude Code or Cursor without sending data to external services", "Run privacy-first document retrieval with smart semantic chunking and optional vision-language PDF parsing in air-gapped or compliance-sensitive development environments" ], "health": "active" }, { "id": "desktop-commander-mcp", "name": "Desktop Commander MCP", "description": "MCP server that gives AI assistants direct terminal control, file system operations, and diff-based file editing on the local machine. Exposes approximately 25 tools including shell command execution, long-running process management, file read/write with diff editing, process listing and termination, and content search. Includes file preview UI with rendered markdown, inline images, and support for Excel, PDF, and Word documents. Security features include symlink traversal prevention, command blocklist, and optional Docker isolation. Actively maintained with v0.2.45 released July 11, 2026.", "category": "code", "endpoint": "Desktop Commander MCP", "homepage_url": "https://github.com/wonderwhy-er/DesktopCommanderMCP", "github_url": "https://github.com/wonderwhy-er/DesktopCommanderMCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @wonderwhy-er/desktop-commander setup", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "terminal", "shell", "file-system", "diff-editing", "process-management", "developer-tools", "open-source", "desktop" ], "use_cases": [ "Give Claude Desktop or other MCP clients direct shell access with command execution, long-running process management, and diff-based file editing through Desktop Commander MCP", "Enable AI assistants to search file contents, manage system processes, and preview documents including Excel, PDF, and Word files with rendered inline previews", "Run terminal commands and manage development workflows from AI assistants with built-in security controls including command blocklists and symlink traversal prevention" ], "health": "active" }, { "id": "flato-mcp", "name": "Flato MCP Server", "description": "MCP server from Flato that connects AI agents to an editable canvas runtime for creating and managing interactive presentations, slide decks, infographics, and visual content. Gives AI full control over text, styles, layout, images, charts, vector elements, animation, and interaction on a persistent canvas that both AI agents and human editors can collaborate on. Includes built-in multi-source image search, vector element generation, and programmable charts. Compatible with Claude Code, Cursor, Codex, and other MCP clients.", "category": "media", "endpoint": "Flato MCP", "homepage_url": "https://www.flato.ai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "presentations", "canvas", "design", "visual-content", "slides", "infographics", "animation", "collaboration" ], "use_cases": [ "Create interactive presentations and slide decks from natural language descriptions using AI agents connected to Flato's editable canvas runtime via MCP", "Build infographics, social media visuals, and marketing assets with AI-controlled layout, typography, charts, and vector elements on a persistent collaborative canvas", "Enable human-AI collaboration on visual content where AI agents generate and edit canvas projects that designers can refine and export through the same Flato workspace" ], "health": "active" }, { "id": "scalekit-mcp-auth", "name": "ScaleKit MCP Auth", "description": "Authentication and authorization middleware for MCP servers from ScaleKit that adds OAuth 2.1 with Dynamic Client Registration, enterprise SSO via Okta, Azure AD, and Google Workspace, and delegated agent identity to any MCP server. Provides a token vault with AES-256 encryption and per-tenant isolation, scope-checked request authorization per connector and tenant, and full delegation chain audit logging exportable to SIEMs. Integrates with FastMCP and standard MCP server implementations. Designed for enterprise MCP deployments requiring production-grade identity controls.", "category": "identity", "endpoint": "ScaleKit MCP Auth", "homepage_url": "https://www.scalekit.com/mcp-auth", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-13", "updated": "2026-07-13", "tags": [ "authentication", "authorization", "oauth", "sso", "enterprise", "identity", "security", "middleware" ], "use_cases": [ "Add production-grade OAuth 2.1 authentication and enterprise SSO to any MCP server with ScaleKit's drop-in identity middleware supporting Okta, Azure AD, and Google Workspace", "Secure MCP server deployments with delegated agent identity, per-tenant token isolation, scope-checked authorization, and full audit logging for enterprise compliance requirements", "Enable multi-tenant MCP server architectures with encrypted token vaults, auto-refresh credentials, and SIEM-exportable delegation chain logging via ScaleKit MCP Auth" ], "health": "active" }, { "id": "rainfocus-mcp", "name": "RainFocus MCP Server", "description": "Enterprise MCP server from RainFocus that delivers live event intelligence to AI assistants through MCP Profiles. Part of RainFocus Nexus, an intelligent collaboration system of specialized AI agents for event marketing operations. Provides real-time access to event data including attendee analytics, session performance, and engagement metrics during high-stakes event execution windows. Features an enterprise-grade OAuth security layer. Cloud-agnostic architecture supports bring-your-own-infrastructure. Announced July 8, 2026.", "category": "data", "endpoint": "RainFocus MCP", "homepage_url": "https://www.rainfocus.com/nexus/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "events", "event-marketing", "conferences", "analytics", "enterprise", "attendee-data", "real-time" ], "use_cases": [ "Query live event data including attendee analytics, session performance, and engagement metrics from AI assistants during event execution using RainFocus MCP Profiles with enterprise OAuth security", "Connect event marketing operations to the agentic web by giving AI agents real-time access to registration, check-in, and session attendance data through the RainFocus Nexus MCP integration", "Enable event strategists to surface actionable insights from live event data directly in Claude or other MCP-compatible clients without leaving their workflow during high-stakes conference execution" ], "health": "active" }, { "id": "st8-gaming-mcp", "name": "St8 Gaming MCP Server", "description": "Enterprise MCP server from St8, a casino games aggregator, that enables operators to access backoffice data using AI assistants and LLMs. Allows teams to retrieve reports, summarize data, access game and provider information, analyze promotional performance, review release calendars, and perform operational tasks through natural language queries. Follows St8's permission hierarchy across companies, operators, and sites to ensure authorized-only data access. Compatible with ChatGPT, Gemini, and other LLMs. Launched July 10, 2026.", "category": "data", "endpoint": "St8 Gaming MCP", "homepage_url": "https://eegaming.org/latest-news/2026/07/10/142381/st8-launches-ai-ready-model-context-protocol/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "gaming", "casino", "igaming", "analytics", "backoffice", "enterprise", "reporting" ], "use_cases": [ "Retrieve operational reports and game performance data from St8's casino games aggregation platform through natural language queries in ChatGPT or Gemini with role-based access control", "Analyze promotional performance, review game release calendars, and summarize provider data across multiple casino operator sites using AI assistants connected to St8's backoffice MCP server", "Enable casino operations teams to query and monitor real-time gaming data across companies, operators, and sites without manually navigating multiple backoffice systems" ], "health": "active" }, { "id": "klient-mcp", "name": "Klient MCP Servers", "description": "Set of three MCP servers from Klient for Salesforce PSA (Professional Services Automation). MCP1 Data handles project and task management, resource assignment, and time logging. MCP1 Admin manages consultant onboarding and permission diagnostics. MCP1 Knowledge enables search, drafting, versioning, and publishing of Salesforce Knowledge articles. Runs locally against the customer's own Salesforce org under the user's login with full audit trail in Salesforce. Supports Claude, Cursor, and Copilot. Launched June 17, 2026.", "category": "productivity", "endpoint": "Klient MCP", "homepage_url": "https://klient.com/products/mcp/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "salesforce", "psa", "project-management", "professional-services", "time-tracking", "knowledge-base", "enterprise" ], "use_cases": [ "Create and manage Salesforce PSA projects, assign resources, and log time entries through natural language commands in Claude or Cursor with every action auditable in the Salesforce org", "Onboard new consultants and diagnose Salesforce permission issues in seconds by asking AI assistants to run admin operations through Klient's MCP1 Admin server", "Search, draft, version, and publish Salesforce Knowledge articles end-to-end from an AI assistant using Klient's MCP1 Knowledge server without switching to the Salesforce UI" ], "health": "active" }, { "id": "lockin-mcp", "name": "LockIn MCP Server", "description": "System-level distraction blocker built for the AI agent era. Lets AI assistants start focus sessions, block distracting domains, and manage timed unblocks through MCP. Edits the system hosts file to redirect distracting domains locally, making blocks apply across all browsers and apps rather than just a single extension. Exposes tools including block_site, unblock_temp, focus_session, and get_status. Works with Claude, ChatGPT, Perplexity, Gemini, and other MCP-compatible clients. One-time $9.99 license. Launched June 26, 2026.", "category": "productivity", "endpoint": "LockIn MCP", "homepage_url": "https://www.lockinmcp.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "productivity", "focus", "distraction-blocker", "system-level", "hosts-file", "focus-sessions" ], "use_cases": [ "Tell your AI assistant to block distracting sites like YouTube, Reddit, and X for a timed focus session using system-level hosts file redirection that works across all browsers and apps", "Manage temporary unblocks and focus session durations through natural language commands in Claude or ChatGPT without opening a separate app or browser extension", "Automate deep work routines by letting AI agents start and stop focus sessions with configurable block lists and timed unblock windows via MCP tools" ], "health": "active" }, { "id": "pictory-mcp", "name": "Pictory MCP Server", "description": "MCP server from Pictory for AI-powered video creation workflows. Exposes modular tools including create-storyboard and render-video that handle input validation, sequencing, and API orchestration. Enables AI assistants to generate personalized videos at scale by combining CRM data with video templates, voiceovers, and branding. Fully compliant with the Model Context Protocol for discovery and orchestration through natural language. Works with Claude Desktop, Cursor, and other MCP-compatible automation tools. Plans to expand with transcription, summarization, and PowerPoint input support.", "category": "media", "endpoint": "Pictory MCP", "homepage_url": "https://pictory.ai/pictory-mcp-server-api", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "video", "ai-video", "content-creation", "media", "marketing", "automation", "storyboard" ], "use_cases": [ "Generate personalized outreach videos at scale by connecting AI assistants to Pictory's MCP server to pull CRM data, select templates, apply branding, and render finished videos through natural language", "Build end-to-end video creation workflows in Claude Desktop or Cursor using Pictory's modular MCP tools for storyboard generation, voiceover selection, and multi-format video rendering", "Automate marketing video production by letting AI agents orchestrate the full pipeline from script to rendered video across multiple aspect ratios without switching to a video editing tool" ], "health": "active" }, { "id": "markifact-mcp", "name": "Markifact MCP Server", "description": "Hosted MCP server from Markifact for managing Google Ads, Meta Ads, GA4, TikTok Ads, and LinkedIn Ads from AI assistants. Supports 300+ ad operations including campaign creation, budget changes, keyword management, ad editing, and performance reporting. Features a human-in-the-loop approval system where every write operation requires marketer approval before changes are applied to ad accounts. Works with Claude, ChatGPT, Gemini, Cursor, and other MCP-compatible clients. No self-hosting required. Open source on GitHub. Launched July 13, 2026.", "category": "data", "endpoint": "Markifact MCP", "homepage_url": "https://www.markifact.com/mcp", "github_url": "https://github.com/markifact/markifact-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "google-ads", "meta-ads", "advertising", "marketing", "ppc", "campaign-management", "human-in-the-loop" ], "use_cases": [ "Manage Google Ads and Meta Ads campaigns from Claude or ChatGPT with human-in-the-loop approval on every write operation, ensuring marketers retain control over budget and bid changes", "Analyze cross-platform ad performance across Google, Meta, TikTok, and LinkedIn Ads through natural language queries in any MCP-compatible AI assistant without switching between ad dashboards", "Automate repetitive PPC operations like keyword additions, negative keyword list management, and ad copy updates through AI assistants while maintaining a human approval gate before changes go live" ], "health": "active" }, { "id": "whale-io-mcp", "name": "Whale.io MCP Server", "description": "MCP server for the Whale.io crypto casino and sportsbook platform that enables AI agents to interact directly with the platform, including placing bets, participating in games, and operating autonomously. Agents deposit real cryptocurrency, determine wager sizes, interpret game states, and execute subsequent actions based on predefined logic. Connected through OpenClaw, which functions as an MCP server facilitating interaction between external agents and Whale's gaming infrastructure. Compatible with Claude, OpenAI GPT-based systems, LangChain, CrewAI, AutoGen, and other MCP-compatible frameworks. Launched April 7, 2026.", "category": "payments", "endpoint": "Whale.io MCP", "homepage_url": "https://whale.io/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "crypto", "casino", "gaming", "sportsbook", "blockchain", "autonomous-agents", "betting" ], "use_cases": [ "Deploy autonomous AI agents to interact with Whale.io's crypto casino platform, placing bets and participating in games with real cryptocurrency through MCP-compatible frameworks like Claude or LangChain", "Build and test AI trading and gaming strategies on a provably fair crypto platform where agents autonomously manage funds, interpret game states, and execute decisions 24/7 without human intervention", "Connect AI agents to Whale.io's gaming infrastructure through the OpenClaw MCP server for agent-vs-agent competitions on live leaderboards across casino games and sportsbook events" ], "health": "active" }, { "id": "gitmcp", "name": "GitMCP", "description": "Free, open-source remote MCP server that transforms any GitHub project into a documentation hub for AI tools. Provides two modes: repository-specific endpoints (gitmcp.io/{owner}/{repo}) for targeted access, and a generic server (gitmcp.io/docs) for flexible multi-repo queries. Enables AI assistants to access up-to-date documentation and code to eliminate hallucinations. Respects robots.txt directives for GitHub Pages sites. Over 8,000 GitHub stars. Works with Claude, Cursor, Windsurf, VS Code, and other MCP-compatible clients.", "category": "code", "endpoint": "https://gitmcp.io/docs", "homepage_url": "https://gitmcp.io/", "github_url": "https://github.com/idosal/git-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-14", "updated": "2026-07-14", "tags": [ "github", "documentation", "open-source", "developer-tools", "code-context", "anti-hallucination", "remote" ], "use_cases": [ "Connect AI coding assistants to any GitHub project's documentation through a remote MCP endpoint to eliminate code hallucinations caused by outdated or missing training data", "Give Claude, Cursor, or VS Code agents real-time access to library documentation by pointing them at gitmcp.io/{owner}/{repo} without installing or configuring a local MCP server", "Use the generic gitmcp.io/docs endpoint to let AI assistants dynamically switch between multiple GitHub repositories for documentation lookups during multi-library development sessions" ], "health": "active" }, { "id": "reuters-mcp", "name": "Reuters MCP Server", "description": "Enterprise MCP server from Reuters that enables AI agents to programmatically search, retrieve, and download Reuters trusted news content within agentic workflows. Designed for Reuters News Agency customers, the server shifts from manual retrieval to intelligent, automated integration. AI agents can automate multimedia assembly by surfacing relevant visual assets during drafting, repackage stories into various formats, and curate content for newsrooms. Unlike traditional APIs, the server is built specifically for AI agent interaction with Reuters journalism. Launched July 8, 2026.", "category": "data", "endpoint": "Reuters MCP", "homepage_url": "https://reutersagency.com/content-delivery-platforms/content-delivery", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "news", "journalism", "media", "enterprise", "content-curation", "multimedia", "reuters" ], "use_cases": [ "Automate multimedia story assembly by having AI agents surface and insert relevant Reuters visual assets directly into drafts as journalists write, eliminating manual media searching", "Enable newsroom AI agents to curate and repackage Reuters content into multiple formats for different audiences without manual editorial intervention", "Deploy AI agents to search and retrieve Reuters-subscribed content programmatically for automated research, briefing generation, and real-time news monitoring workflows" ], "health": "active" }, { "id": "ians-mcp", "name": "IANS Cybersecurity MCP Server", "description": "Enterprise MCP server from IANS that delivers practitioner-validated cybersecurity intelligence directly into AI assistants. Provides 24/7 access to proprietary data including a database of thousands of client conversations with 170+ expert Faculty practitioners, unbiased vendor intelligence, and peer community discussions. Available through Claude with support for other major AI tools coming in H2 2026. Enables security teams to evaluate vendors, develop board presentations, advance AI governance programs, and benchmark decisions against peer organizations using practitioner-sourced intelligence rather than generic public data. Launched July 15, 2026.", "category": "data", "endpoint": "IANS MCP", "homepage_url": "https://www.iansresearch.com/mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "cybersecurity", "security", "enterprise", "intelligence", "vendor-evaluation", "compliance", "ciso" ], "use_cases": [ "Query practitioner-validated cybersecurity intelligence from IANS' 170+ expert Faculty network inside Claude to get vendor-agnostic guidance grounded in real peer decisions rather than generic public data", "Benchmark security decisions against peer organizations by asking AI assistants questions about what similar companies actually did, including trade-offs and outcomes, using IANS' proprietary conversation database", "Accelerate board presentation development and AI governance program planning by accessing IANS' curated cybersecurity research and practitioner recommendations directly through MCP-connected AI tools" ], "health": "active" }, { "id": "legatics-mcp", "name": "Legatics MCP Server", "description": "Enterprise MCP server from Legatics, the transaction management platform for law firms. Gives AI assistants real-time access to live deal data including matter status, signing progress, list management, binders, and data rooms. Enables AI tools to answer matter-specific questions from current information rather than static exports. Uses OAuth 2.0 with PKCE authentication, scoped permissions per AI application, full audit logging, and immediate revocability. Vendor-neutral design works with any MCP-compatible AI assistant. Included at no additional cost for all Legatics customers. Read access at launch with write access planned. Launched July 15, 2026.", "category": "productivity", "endpoint": "Legatics MCP", "homepage_url": "https://www.legatics.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "legal", "transactions", "deal-management", "law-firms", "enterprise", "signing", "matter-management" ], "use_cases": [ "Connect AI assistants to live Legatics deal data to answer matter-specific questions about outstanding items, signing status, and next steps in real time with OAuth 2.0 PKCE security and full audit logging", "Enable law firms to query structured deal data across multiple matters using AI assistants to analyze how transactions are being delivered and inform staffing and process decisions", "Give legal AI tools vendor-neutral access to transaction infrastructure including list management, signing management, binders, and data rooms without switching between platforms" ], "health": "active" }, { "id": "fundednext-mcp", "name": "FundedNext MCP Server", "description": "MCP server from FundedNext, a prop trading firm, that allows traders to connect their FundedNext accounts with AI assistants including Claude, ChatGPT, and Gemini. Provides read-only access to trading account data, preventing AI from executing trades. Appears to be the first prop trading firm to offer MCP integration. Traders can query account performance, analyze trading history, and review challenge progress through natural language. Compatible with any MCP-compatible client. Launched July 14, 2026.", "category": "data", "endpoint": "FundedNext MCP", "homepage_url": "https://fundednext.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "trading", "prop-trading", "finance", "fintech", "read-only", "account-analytics", "forex" ], "use_cases": [ "Connect prop trading accounts to AI assistants like Claude or ChatGPT to query FundedNext account performance, challenge progress, and trading history through natural language with read-only safety guarantees", "Analyze trading patterns and performance metrics across FundedNext evaluation phases using AI assistants without manually navigating the trading dashboard", "Enable prop traders to build AI-powered reporting workflows that pull account data from FundedNext into MCP-compatible tools for automated journaling and performance reviews" ], "health": "active" }, { "id": "heirwealth-mcp", "name": "HeirWealth MCP Server", "description": "MCP server from HeirWealth that enables wealth managers and family offices to query consolidated client data using AI assistants like Claude and ChatGPT. Features a deterministic calculation engine ensuring figures are accurate and auditable. Zero-training policy means client data is never used to train third-party models. Generates real-time portfolio summaries, automated anomaly flags, and risk detection across the balance sheet through plain-English prompts. Integrates with existing HeirWealth Atlas permissions for governed data access. Available immediately for Atlas firms on opt-in basis. Launched July 9, 2026.", "category": "data", "endpoint": "HeirWealth MCP", "homepage_url": "https://www.heirwealth.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "wealth-management", "finance", "family-office", "portfolio", "enterprise", "compliance", "fintech" ], "use_cases": [ "Generate real-time portfolio summaries and client communications by querying consolidated wealth data across multiple entities through Claude or ChatGPT with deterministic calculations and full audit trails", "Detect portfolio anomalies and balance sheet risks automatically by connecting AI assistants to HeirWealth's governed data layer with zero-training privacy guarantees on client information", "Prepare client meeting briefs and first-draft communications in seconds by asking AI assistants to pull and synthesize data across all structures within the HeirWealth Atlas permission framework" ], "health": "active" }, { "id": "voxpopme-mcp", "name": "Voxpopme MCP Server", "description": "MCP server from Voxpopme that connects an organization's proprietary customer research repositories to AI assistants including Claude, ChatGPT, and Microsoft Teams. Enables research, marketing, product, and innovation teams to query their own internal customer studies from AI tools with answers grounded in real customer interviews and linked to source video clips. If a question hasn't been asked of customers yet, users can launch new research studies directly from the conversation. Permissioned access ensures each user only reaches insights they are cleared to see. Early access launched July 9, 2026.", "category": "data", "endpoint": "Voxpopme MCP", "homepage_url": "https://www.voxpopme.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "customer-research", "market-research", "consumer-insights", "video-research", "enterprise", "surveys", "qualitative" ], "use_cases": [ "Query proprietary customer research repositories from Claude or ChatGPT to get answers grounded in real customer interviews with direct links to source video clips rather than relying on generic public data", "Launch new customer research studies directly from an AI assistant conversation when existing data doesn't cover the question, keeping the entire insights workflow inside one tool", "Enable cross-functional teams to access permissioned customer intelligence in their existing AI workflows without switching to a separate research platform or waiting for analyst reports" ], "health": "active" }, { "id": "wistia-mcp", "name": "Wistia MCP Server", "description": "MCP server from Wistia that connects a video library to Claude, Cursor, or ChatGPT for full video management through natural language. Enables creating, searching, editing, publishing, and pulling analytics for an entire video library without opening the Wistia dashboard. Key capabilities include finding content by description, reading captions and transcripts at scale, auditing accessibility gaps, splitting long videos into chapters, curating channels, and performance reporting. Over 300 accounts connected within days of launch generating thousands of queries. Available to account owners and managers. Launched July 6, 2026.", "category": "media", "endpoint": "Wistia MCP", "homepage_url": "https://wistia.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-15", "updated": "2026-07-15", "tags": [ "video", "video-management", "marketing", "analytics", "captions", "accessibility", "content-management" ], "use_cases": [ "Manage an entire Wistia video library through Claude or ChatGPT using natural language to search, edit metadata, reorder channels, and publish content without opening the Wistia dashboard", "Run library-wide caption and accessibility audits by asking an AI agent to flag every video missing captions and order them in bulk, replacing hours of manual title-by-title review", "Pull video performance analytics including plays, engagement, and audience data directly into AI workflows for instant reporting without logging into Wistia's analytics dashboard" ], "health": "active" }, { "id": "tiiny-host-mcp", "name": "Tiiny Host MCP Server", "description": "MCP server from Tiiny Host that enables AI assistants to publish, update, and delete hosted web projects directly from a chat conversation. Supports HTML files, ZIP archives, PDFs, PHP apps, and over 100 other file types. Users connect via Claude's custom connector at mcp.tiiny.host and get a live tiiny.site URL without leaving the chat window. Available on all Tiiny Host plans including the free tier. Paid plans range from $5/mo to $74/mo with custom domains and additional storage. Launched July 13, 2026.", "category": "web", "endpoint": "https://mcp.tiiny.host", "homepage_url": "https://tiiny.host/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "hosting", "web-publishing", "deployment", "static-sites", "html", "free-tier", "no-code" ], "use_cases": [ "Publish a finished HTML file, ZIP archive, or PDF to a live hosted URL directly from a Claude conversation without opening a separate hosting dashboard or configuring DNS", "Update or delete existing Tiiny Host projects through natural language commands in an AI assistant, turning the chat window into a complete web publishing workflow", "Deploy AI-generated websites, landing pages, and portfolios instantly by connecting Claude to Tiiny Host's MCP server for zero-friction publishing of over 100 supported file types" ], "health": "active" }, { "id": "salesforce-headless-360-mcp", "name": "Salesforce Headless 360 MCP Server", "description": "Hosted MCP server from Salesforce that brings the full breadth of the Salesforce platform to any MCP-compatible agent through a single connection. Instead of exposing thousands of features as individual tools, the server provides four meta-tools — Discover, Describe, Dispatch, and Dispatch Read Only — backed by a continuously growing library of Salesforce operations. Covers user management, Apex trigger deployment, event-driven integrations, named credentials, Commerce Cloud Orders, and more. Every transaction runs as the authenticated user with full CRUD, FLS, sharing rules, and audit trail enforcement. Beta launched July 2026 with approximately 100 skills at launch, expanding to thousands.", "category": "productivity", "endpoint": "https://api.salesforce.com/platform/mcp/v1/platform/headless-360", "homepage_url": "https://developer.salesforce.com/blogs/2026/07/announcing-the-headless-360-mcp-server-beta", "github_url": "https://github.com/forcedotcom/mcp-hosted", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "salesforce", "crm", "enterprise", "platform", "admin", "apex", "integrations", "beta" ], "use_cases": [ "Manage Salesforce users, permission sets, and org configuration from any MCP-compatible AI assistant using four meta-tools that semantically discover and invoke the right operations across the entire Salesforce platform", "Build event-driven integrations by asking an AI agent to configure Change Data Capture, named credentials, and event relays through the Headless 360 MCP server without navigating multiple Setup screens", "Deploy and manage Apex triggers, create Commerce Cloud orders, and execute complex multi-step Salesforce workflows from Claude, Cursor, or other MCP clients with full RBAC and audit trail enforcement" ], "health": "active" }, { "id": "6sense-mcp", "name": "6sense MCP Server", "description": "MCP server from 6sense that makes proprietary go-to-market intelligence — account insights, predictive buying stages, 6sense Qualified Account (6QA) status, keyword intent, and ad campaign performance — callable from any MCP-compatible AI agent including Claude, ChatGPT, Writer, and Agentforce. Every 6QA is trained on customer-specific purchase outcomes rather than engagement proxies, with explainable reasoning showing which signals moved the score. Powered by RevvyAI and the Signalverse proprietary B2B signal network spanning 200,000+ properties built over 13 years. Open beta for Revenue Marketing customers, GA planned August 2026. Launched July 14, 2026.", "category": "data", "endpoint": "6sense MCP", "homepage_url": "https://6sense.com/newsroom/6sense-launches-mcp-server-bringing-proprietary-gtm-intelligence-into-any-ai-agent/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "gtm", "sales-intelligence", "intent-data", "account-based-marketing", "b2b", "enterprise", "predictive-analytics" ], "use_cases": [ "Query predictive buying stages and 6QA status from Claude, ChatGPT, or Agentforce to identify which accounts are actively in-market and where they sit in the buying journey without leaving the AI assistant", "Analyze ad campaign impact by asking AI agents which accounts advanced a buying stage or became new 6QAs after display campaigns reached them, with reasoning grounded in 6sense's proprietary Signalverse signal network", "Surface engagement gaps by asking which accounts moved into active buying stages with no recent outreach, enabling GTM teams to act on revenue signals in the same conversation where decisions are made" ], "health": "active" }, { "id": "rafay-mcp", "name": "Rafay MCP Server", "description": "Managed MCP server from Rafay Systems that gives platform, DevOps, and SRE teams a governed interface for querying operational infrastructure context through AI assistants. Connects MCP-compatible clients to the Rafay Platform using existing RBAC and project boundaries. Initial workflows cover fleet intelligence and cost attribution for Kubernetes environments, plus incident diagnosis with structured root-cause analysis for common issues like image-pull errors, crash loops, and failed deployments. Read-only access enforced through Rafay API key authentication. Available via feature flag. Announced July 15, 2026.", "category": "infrastructure", "endpoint": "Rafay MCP", "homepage_url": "https://rafay.co/ai-and-cloud-native-blog/bring-rafay-into-your-ai-workflows-with-the-rafay-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "kubernetes", "infrastructure", "devops", "sre", "fleet-management", "cost-attribution", "incident-response", "enterprise" ], "use_cases": [ "Query Kubernetes fleet data across projects from AI assistants to inventory clusters, summarize health and configuration status, and identify underutilized environments with cost-per-workload analysis using Rafay's existing RBAC boundaries", "Diagnose Kubernetes incidents by asking AI assistants which clusters or namespaces are degraded, with structured root-cause analysis for common issues like image-pull errors, crash loops, and unschedulable pods", "Build agentic operations workflows on top of the Rafay Platform by connecting MCP-compatible AI tools to live infrastructure context without writing bespoke translation layers for every API and data source" ], "health": "active" }, { "id": "primo-mcp", "name": "Primo MCP Server", "description": "MCP server from Primo that connects AI assistants to IT operations for fleet-wide device querying and management. Enables IT teams to ask natural language questions about their entire device fleet, including device status, assignment, last activity, open tickets, and installed software. Provides real-time context from Primo's unified IT operations platform without switching between consoles or running manual queries. Works with Claude and other MCP-compatible clients. Launched July 10, 2026.", "category": "infrastructure", "endpoint": "Primo MCP", "homepage_url": "https://www.getprimo.com/blog/primo-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "it-operations", "device-management", "fleet-management", "endpoint-management", "helpdesk", "enterprise" ], "use_cases": [ "Query an entire IT device fleet through natural language prompts in Claude or other MCP clients to find device assignments, last activity timestamps, open tickets, and installed software without switching between IT consoles", "Automate IT support triage by connecting AI assistants to Primo's unified IT operations platform for instant cross-referencing of device health, user assignment, and ticket status in a single conversation", "Enable IT teams to run fleet-wide audits and compliance checks through AI assistants connected to Primo, replacing manual console navigation and CLI queries with natural language fleet intelligence" ], "health": "active" }, { "id": "injective-mcp", "name": "Injective MCP Server", "description": "Open-source MCP server from Injective that enables AI coding agents to build, deploy, and verify smart contracts on the Injective Layer-1 blockchain using natural language prompts. Ships with 22 tools covering market data, trading, transfers, and bridging. Converts AI agent intent into signed blockchain transactions without manual transaction construction. Uses AES-256 encryption for key security. Part of a broader AI-native developer ecosystem including documentation MCP and agent-skills packages for EVM smart contract development. Compatible with Claude, Cursor, and other MCP clients. Launched July 5, 2026.", "category": "code", "endpoint": "Injective MCP", "homepage_url": "https://cryptobriefing.com/injective-mcp-server-smart-contract-ai-prompts/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "blockchain", "smart-contracts", "defi", "trading", "web3", "open-source", "evm", "layer-1" ], "use_cases": [ "Deploy smart contracts on Injective's Layer-1 blockchain through natural language prompts in AI coding agents, eliminating the need for manual transaction construction and Cosmos SDK knowledge", "Execute perpetual futures trades, access real-time market data, and manage token transfers autonomously through AI agents connected to Injective's 22 onchain MCP tools with AES-256 key encryption", "Build end-to-end blockchain development workflows where AI coding agents reference Injective documentation, write contracts, deploy to the network, and verify them through the MCP server tool suite" ], "health": "active" }, { "id": "snaplogic-snapcode-mcp", "name": "SnapLogic SnapCode MCP Server", "description": "MCP server from SnapLogic that brings governed enterprise integration capabilities directly into AI coding environments like Cursor, GitHub Copilot, Claude Code, and Windsurf. Unlike SnapLogic's MCP Builder (which creates MCP servers from existing pipelines), SnapCode enables developers to create, deploy, and govern enterprise integrations from within their IDE through natural language. Includes guardrails that enforce compliance, governance, and security policies automatically. Part of SnapLogic's July 2026 product release alongside the generally available MCP Server. Launched July 14, 2026.", "category": "code", "endpoint": "SnapLogic SnapCode MCP", "homepage_url": "https://www.snaplogic.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "enterprise-integration", "ide", "coding-agents", "governance", "compliance", "data-pipelines", "low-code" ], "use_cases": [ "Create and deploy enterprise integrations from Cursor, Claude Code, or GitHub Copilot using natural language, with SnapLogic automatically enforcing compliance, governance, and security policies on every integration", "Connect AI coding agents to SnapLogic's enterprise integration platform so developers can build data pipelines and API integrations without leaving their IDE or learning the SnapLogic visual builder", "Govern AI-generated integrations at enterprise scale by routing all coding agent integration work through SnapLogic's policy engine, ensuring consistency and security across teams using different AI coding tools" ], "health": "active" }, { "id": "snaplogic-mcp-server", "name": "SnapLogic MCP Server", "description": "Generally available MCP server from SnapLogic that exposes existing SnapLogic integration pipelines, API Management services, and OpenAPI specifications as MCP tools consumable by any MCP-compatible AI agent. Distinct from the previously released MCP Builder (which creates MCP servers) and SnapCode (which targets coding agents), this is the runtime server that AI assistants connect to for executing enterprise integrations. Includes full governance controls and audit logging. Made generally available July 7, 2026 as part of SnapLogic's July product release.", "category": "infrastructure", "endpoint": "SnapLogic MCP Server", "homepage_url": "https://www.snaplogic.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-16", "updated": "2026-07-16", "tags": [ "enterprise-integration", "ipaas", "api-management", "automation", "data-pipelines", "governance" ], "use_cases": [ "Connect AI assistants like Claude or ChatGPT to existing SnapLogic enterprise integrations and execute data pipeline operations, API calls, and workflow automations through natural language without rebuilding integrations", "Expose any SnapLogic pipeline or API Management service as an MCP tool that AI agents can discover and invoke, with full governance controls and audit logging for enterprise compliance", "Enable business teams to trigger complex enterprise integration workflows from AI assistants by connecting to SnapLogic's generally available MCP server runtime with organizational access controls" ], "health": "active" }, { "id": "verbatik-mcp", "name": "Verbatik MCP Server", "description": "MCP server from Verbatik Technologies that connects text-to-speech voice generation tools directly to AI assistants. Provides access to over 2,700 neural voices in 50-plus languages, instant voice cloning from a 10-second audio sample, and SSML support for fine-grained speech control. Exposes nine tools covering voice library browsing, text-to-speech generation for up to 50,000 characters, cloned-voice generation with seven emotional settings, voice management, account balance checks, and cost estimation. Supports multi-step audio workflows where an assistant can translate a script into multiple languages and generate narration for each version in a single pass. Uses Streamable HTTP transport with OAuth 2.1 and PKCE or per-client API key authentication. Serves over 150,000 users. Free initial setup with complimentary starting credits. Announced July 16, 2026.", "category": "media", "endpoint": "https://verbatik.com/mcp", "homepage_url": "https://verbatik.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "text-to-speech", "voice-cloning", "audio", "multilingual", "neural-voices", "ssml", "tts" ], "use_cases": [ "Generate audio narration of blog posts, articles, or documentation directly from Claude or other MCP-compatible assistants by selecting a voice and language, receiving a shareable audio URL without leaving the conversation", "Clone a brand voice from a 10-second audio sample and produce multilingual narrated content with emotional control, speed, and pitch adjustments through AI assistant commands", "Batch-produce audio for content libraries by having an AI agent estimate costs, check account balance, translate scripts into multiple languages, and generate narration for each version in a single automated workflow" ], "health": "active" }, { "id": "symmetry-payroll-mcp", "name": "Symmetry Payroll Tax MCP Server", "description": "MCP server from Symmetry that exposes a payroll tax calculation engine to AI agents through the Model Context Protocol. Enables autonomous AI agents on payroll platforms to perform real-time payroll tax calculations, compliance checks, and error detection across over 10,000 tax jurisdictions. Designed for fintech engineering teams building AI-native payroll features, eliminating the need for custom middleware between LLMs and tax data. The engine updates automatically as regulations change, ensuring agents always work with current tax rules. Announced July 17, 2026.", "category": "data", "endpoint": "Symmetry MCP Server", "homepage_url": "https://www.symmetry.co.za/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "payroll", "tax-compliance", "fintech", "enterprise", "hr", "regulatory", "calculations" ], "use_cases": [ "Automate payroll tax calculations for AI-driven HR platforms by connecting agents to Symmetry's engine via MCP, enabling real-time gross-to-net calculations across 10,000-plus US tax jurisdictions without building custom tax logic", "Detect payroll data entry errors autonomously by having AI agents query the Symmetry tax engine to validate withholding amounts, flag compliance risks, and suggest corrections before payroll processing deadlines", "Build AI-native payroll features for fintech products by integrating the Symmetry MCP server as the tax computation layer, reducing development time and ensuring automatic compliance updates as tax regulations change" ], "health": "active" }, { "id": "sprinklr-mcp", "name": "Sprinklr MCP Server", "description": "First-party MCP connector from Sprinklr that makes customer intelligence data available to AI assistants including Microsoft Copilot, ChatGPT, and Claude. Part of Sprinklr's Summer 2026 release, the beta connector lets marketing and CX teams query social listening data, campaign metrics, and survey results through natural language in their preferred AI assistant without opening the Sprinklr UI. Sprinklr is the third major martech vendor to ship a first-party MCP server in 2026, following HubSpot and Salesloft. Serves over 1,600 enterprise customers including 59 percent of the Fortune 100. Beta launched July 15, 2026.", "category": "data", "endpoint": "Sprinklr MCP", "homepage_url": "https://www.sprinklr.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "martech", "social-listening", "customer-intelligence", "enterprise", "crm", "marketing-analytics", "beta" ], "use_cases": [ "Query Sprinklr social listening data and campaign performance metrics from Microsoft Copilot, ChatGPT, or Claude without switching to the Sprinklr dashboard, enabling marketers to get customer intelligence answers inside their primary AI assistant", "Analyze how brand sentiment shifted after a campaign flight by asking AI assistants to pull Sprinklr data on social mentions, engagement trends, and survey responses in a single natural-language conversation", "Connect AI-driven marketing workflows to Sprinklr's customer intelligence platform so enterprise CX teams can surface insights, monitor brand health, and inform decisions from the assistant they already work in daily" ], "health": "active" }, { "id": "bmc-helix-mcp", "name": "BMC Helix MCP Server", "description": "MCP capabilities from BMC that securely connect AI agents to enterprise workflows and operational data across BMC Helix and mainframe environments. Enables organizations to move from insight to action with visibility, control, and resilience by letting AI agents query and interact with ITSM workflows, operational data, and mainframe operations through governed interfaces. Part of BMC's broader AI agent governance strategy that includes runtime protection and policy enforcement for agent interactions with enterprise systems. Announced July 15, 2026.", "category": "infrastructure", "endpoint": "BMC Helix MCP", "homepage_url": "https://www.bmc.com/newsroom/releases/bmc-brings-governed-ai-agents-to-enterprise-workflows-and-mainframe-operations.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "itsm", "enterprise", "mainframe", "workflow-automation", "governance", "devops", "operations" ], "use_cases": [ "Connect AI agents to BMC Helix ITSM workflows to query incident status, change requests, and service health through natural language, with governed access controls ensuring agents operate within defined organizational policies", "Enable AI-driven mainframe operations by giving agents secure read access to mainframe performance data, job status, and capacity metrics through BMC's MCP interface without exposing raw system credentials", "Build governed agentic workflows that span IT service management and infrastructure operations by connecting AI assistants to BMC Helix data with runtime protection, audit trails, and policy enforcement on every agent action" ], "health": "active" }, { "id": "sensorhubb-mcp", "name": "SensorHubb MCP Server", "description": "Native MCP server from SensorHubb that makes the unified sensor intelligence platform accessible to AI agents. First platform in the sensor intelligence category with native AI-agent access. Teams connect Claude, ChatGPT, Microsoft Copilot, Gemini, or any MCP-compatible agent and query sensor data in plain language — asking which coolers are trending toward failure or which sites logged compliance excursions. Strict safety constraints govern every agent action with confirmation on changes and blocking of destructive operations. Part of SensorHubb 3.0 which also adds predictive equipment health scoring, custom reporting, and building automation connectivity across eight industry protocols including BACnet/IP and Modbus TCP. Serves healthcare, food service, hospitality, education, and life sciences. Launched July 14, 2026.", "category": "infrastructure", "endpoint": "SensorHubb MCP", "homepage_url": "https://www.sensorhubb.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "iot", "sensors", "compliance", "food-safety", "healthcare", "predictive-maintenance", "building-automation" ], "use_cases": [ "Ask AI agents in plain language which refrigeration equipment is trending toward failure across a multi-site healthcare or food service operation, using SensorHubb's predictive health scores to schedule preventive maintenance before alarms trigger", "Run compliance audits through AI assistants by querying which sites logged temperature excursions last month, with SensorHubb's tamper-proof audit logs providing 21 CFR Part 11 support for regulated environments", "Monitor thousands of IoT sensors across facilities from a single AI conversation by connecting Claude, Copilot, or Gemini to SensorHubb's MCP server with strict safety constraints that block destructive operations and confirm every change" ], "health": "active" }, { "id": "evipedia-mcp", "name": "Evipedia MCP Server", "description": "Open-source MCP server from Forever Healthy Foundation that connects AI assistants to Evipedia, a continuously updated health and longevity encyclopedia with over 600 evidence reviews. Agents can search reviews, pull conclusions, retrieve full Markdown content, access structured medical metadata, and suggest new interventions. Every review includes schema.org structured data and primary-source citations as structured entries. Content is licensed under CC BY 4.0 with an agent-friendly site policy that places no barriers to automated access. Includes llms.txt, OpenAPI spec, and keyless API for broad integration. Compatible with Claude Desktop, Claude Code, Cursor, and other MCP clients. Launched July 15, 2026.", "category": "data", "endpoint": "Evipedia MCP", "homepage_url": "https://evipedia.ai/", "github_url": "https://github.com/forever-healthy/evipedia-mcp", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "health", "longevity", "medical-research", "evidence-based", "open-source", "encyclopedia", "cc-by-4" ], "use_cases": [ "Query evidence-based health intervention reviews from AI assistants by searching Evipedia's 600-plus continuously updated entries covering supplements, peptides, lifestyle protocols, and rejuvenation therapies with full source citations", "Build longevity research pipelines that pull structured medical metadata, review conclusions, and primary-source references from Evipedia through the open-source MCP server without API keys or authentication barriers", "Integrate Evipedia into health-focused AI agents that need verified intervention data — quick reference sheets for protocols and dosing plus full evidence reviews — all under CC BY 4.0 with schema.org structured data for deterministic extraction" ], "health": "active" }, { "id": "revid-ai-mcp", "name": "Revid.ai MCP Server", "description": "MCP server from Revid.ai that gives AI agents direct access to a complete video production pipeline. Exposes tools with stable names including render_video, get_project_status, export_video, clone_voice, schedule_publish, and publish_now. Supports nine production workflows at launch covering script-to-video, prompt-to-video, and audio-to-video from source materials including prompts, scripts, links, and audio files. Produces complete short films with scripts, voices, captions, and correct aspect ratios in a single pass rather than isolated clips. Users receive editable projects with full commercial rights and no watermarks. Supports OAuth 2.1 for hosted agent clients and API-key authentication for local configurations. Based in Paris. Launched July 16, 2026.", "category": "media", "endpoint": "Revid.ai MCP", "homepage_url": "https://www.revid.ai/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-17", "updated": "2026-07-17", "tags": [ "video-generation", "ai-video", "content-creation", "short-form-video", "voice-cloning", "publishing", "automation" ], "use_cases": [ "Automate end-to-end short-form video production from AI agents by passing a script or prompt to Revid.ai's MCP server and receiving a complete video with generated voice, captions, and correct aspect ratio — ready to publish without manual editing", "Schedule and publish AI-generated videos directly to social platforms through MCP tool calls, closing the last-mile gap between content generation and distribution without switching to a separate publishing dashboard", "Clone a brand voice and produce batches of short-form video content from scripts or audio files through AI agent workflows, with editable projects returned for human review before final export at full commercial rights" ], "health": "active" }, { "id": "streamline-ai-mcp", "name": "Streamline AI MCP Connector", "description": "First-party MCP connector from Streamline AI that securely extends the in-house legal operating platform to AI assistants including Claude, ChatGPT, Gemini, Microsoft Copilot, and Glean. Employees can ask natural-language questions about legal matters, request status updates, approvals, and reporting directly from their preferred AI assistant. Authenticates users through OAuth 2.1, enforces the same permissions that exist within Streamline, routes requests in real time without storing or caching customer data, and records every interaction in the platform's audit trail. Used by more than 1,000 lawyers at organizations including Gusto, 8x8, and Bloom Energy. Announced July 15, 2026.", "category": "productivity", "endpoint": "Streamline AI MCP", "homepage_url": "https://www.streamline.ai/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "legal", "enterprise", "compliance", "workflow-automation", "governance", "slack", "intake" ], "use_cases": [ "Query legal request status, approvals, and reporting from Claude, Copilot, or ChatGPT without switching to the Streamline dashboard, reducing interruptions to the legal team for routine status updates", "Enable employees to submit structured legal requests through Slack using natural language, with the Streamline agent capturing context and routing work through existing governance workflows", "Build AI-assisted legal operations that enforce permission-aware access to legal data, audit every interaction, and ensure no customer data is cached or stored outside the Streamline platform" ], "health": "active" }, { "id": "opmanager-nexus-mcp", "name": "ManageEngine OpManager Nexus MCP Server", "description": "MCP server from ManageEngine that connects AI assistants to the OpManager Nexus hybrid observability platform for live infrastructure monitoring and AIOps. Once connected to an MCP client like Cursor, VS Code, Claude Desktop, or Windsurf, AI assistants can pull live metrics, find anomalies, and correlate observability data with other tools in the stack including CI/CD pipelines, helpdesk tools, and version control. Ships as a Docker image for on-premises deployments or hosted inside Zoho's private datacenters for cloud customers. Part of OpManager Nexus's broader AIOps capabilities including Zia autonomous agents, smart event correlation, and GenAI integrations with OpenAI, DeepSeek, and Ollama. Announced July 16, 2026.", "category": "infrastructure", "endpoint": "OpManager Nexus MCP", "homepage_url": "https://www.manageengine.com/it-operations-management/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "observability", "aiops", "infrastructure-monitoring", "enterprise", "network-monitoring", "hybrid-cloud", "devops" ], "use_cases": [ "Ask AI assistants to show servers with high CPU usage over the last two hours and get answers from live OpManager Nexus observability data without opening the monitoring dashboard", "Correlate helpdesk tickets with observability metrics and deployment milestones during an outage, tracing incidents back to root causes through AI-assisted cross-tool analysis", "Deploy the MCP server as an on-premises Docker image for air-gapped environments or use the Zoho-hosted cloud version, ensuring AI-driven monitoring stays within organizational data sovereignty requirements" ], "health": "active" }, { "id": "rewst-mcp", "name": "Rewst MCP Server", "description": "MCP server at the core of Rewst's reengineered automation platform for managed service providers. Integrates MCP and agentic AI so that MSPs and their customers can build automation workflows using natural-language prompts instead of requiring trained automation engineers. An AI Agent tool lets users describe a process they want to automate, then automatically builds, visualizes, and presents the workflow for human review and approval. Designed to address the global shortage of automation engineers across 80,000 MSPs. Currently in expanded beta testing with MSP partners since early July 2026, with general availability planned for later in 2026. Announced July 13, 2026.", "category": "productivity", "endpoint": "Rewst MCP", "homepage_url": "https://rewst.io/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "msp", "automation", "workflow", "it-operations", "agentic-ai", "no-code", "beta" ], "use_cases": [ "Enable MSPs without dedicated automation engineers to build IT automation workflows by describing processes in natural language, with the Rewst AI agent constructing and presenting the workflow for human approval", "Increase automation engineer productivity by letting them describe complex multi-step automations in plain language and review AI-generated workflows, potentially building ten automations per week instead of one", "Scale automation services for SMB and enterprise customers by connecting MCP-compatible AI agents to Rewst's platform, making workflow creation accessible to non-technical staff" ], "health": "active" }, { "id": "metatrader5-mcp", "name": "MetaTrader 5 MCP Server", "description": "Native MCP integration in MetaTrader 5 Build 6030 from MetaQuotes that connects the trading platform to external AI agents through the Model Context Protocol. Replaces previous provider-specific AI integrations with a common interface, letting traders connect AI assistants like Codex and Claude Code to charts, market data, trading accounts, and execution workflows. The bundled AI Assistant can analyse markets, explain trading activity, generate and debug Expert Advisors, flag programming errors, and support strategy testing. Part of a broader industry shift where trading platforms including cTrader and ThinkMarkets are exposing their accounts and order management to AI tools through standard protocols. Released July 16, 2026.", "category": "data", "endpoint": "MetaTrader 5 MCP", "homepage_url": "https://www.metatrader5.com/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "trading", "fintech", "forex", "market-data", "algorithmic-trading", "expert-advisors", "financial-analysis" ], "use_cases": [ "Connect Claude Code or Codex to MetaTrader 5 to analyse live market data, generate trading strategy code as Expert Advisors, and debug MQL5 programs through natural-language conversation", "Ask AI assistants to explain recent trading activity, flag anomalies in account performance, and suggest next diagnostic checks during volatile market conditions using live MetaTrader data", "Automate strategy backtesting workflows by having AI agents generate Expert Advisor code from plain-language descriptions, run tests against historical data, and report results within a single conversation" ], "health": "active" }, { "id": "localize-mcp", "name": "Localize MCP Server", "description": "Open-source MCP server for the Localize Elixir library that teaches AI agents the full Localize API through eleven typed tool calls backed by BEAM introspection. Replaces source-code grepping with structured discovery, documentation, schema, locale resolution, and live execution tools. Supports formatting numbers, currencies, dates, times, units, lists, messages, collation, and plural rules across locales. The server runs locally from the user's project using stdio transport and sees the exact Localize version pinned in mix.exs. Compatible with Claude Desktop, Claude Code, Codex CLI, ChatGPT, and Zed. Published on Hex as localize_mcp. Released July 15, 2026.", "category": "code", "endpoint": "localize_mcp", "homepage_url": "https://hexdocs.pm/localize_mcp/readme.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "mix deps.get && mix compile", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "elixir", "localization", "i18n", "beam", "formatting", "open-source", "developer-tools" ], "use_cases": [ "Teach AI coding agents the full Localize API surface so they can correctly format numbers, currencies, dates, and messages across locales without grepping source code or burning tokens on documentation searches", "Enable AI assistants to invoke read-only Localize functions live from within an Elixir project, validating locale resolution and formatting output in real time under timeout and heap safety constraints", "Integrate with Claude Code, Cursor, or Zed to provide version-accurate Localize documentation and examples including guided sigil, Gettext, Phoenix, and LiveView translation setup workflows" ], "health": "active" }, { "id": "nable-mcp", "name": "Nable FinOps MCP Server", "description": "MCP server that acts as the FinOps cost brain for AI agents in Claude and Cursor, providing comprehensive insights into AWS, Azure, GCP, Kubernetes, and over 15 SaaS and AI provider expenses. Delivers real cost numbers based on actual negotiated rates, identifies genuine savings opportunities, and proposes fixes as actionable pull requests. Runs locally so billing data never leaves the user's machine. Read-only by default with pre-action cost controls that let agents check financial impact before making cost-affecting infrastructure changes. Covers right-sizing cloud resources, analyzing unexpected cost spikes, and implementing cost gates for AI-driven operations.", "category": "infrastructure", "endpoint": "Nable MCP", "homepage_url": "https://nable.dev/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "finops", "cloud-cost", "aws", "azure", "gcp", "kubernetes", "cost-optimization" ], "use_cases": [ "Right-size cloud resources like EC2 instances, RDS databases, and Kubernetes clusters by having AI agents query Nable for actual cost data and savings recommendations based on real negotiated rates", "Analyze unexpected cloud cost spikes by asking AI agents to identify root causes across AWS, Azure, GCP, and SaaS providers, with all billing data processed locally and never leaving the user's machine", "Implement pre-action cost gates for AI-driven infrastructure changes by querying Nable to assess financial impact before provisioning or scaling resources, with proposed fixes delivered as actionable pull requests" ], "health": "active" }, { "id": "adobe-workfront-mcp", "name": "Adobe Workfront MCP Server", "description": "MCP server from Adobe that connects the Workfront project management platform to AI agentic platforms including Claude and ChatGPT. Enables users to find, create, update, and analyze Workfront projects, tasks, issues, and work items through natural-language conversations in their preferred AI assistant. Part of Adobe Workfront's Third Quarter 2026 release. Designed for enterprise teams using Workfront for marketing operations, creative production, and cross-functional work management who want to interact with their project data through AI assistants without opening the Workfront interface.", "category": "productivity", "endpoint": "Adobe Workfront MCP", "homepage_url": "https://business.adobe.com/products/workfront/main.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "project-management", "enterprise", "adobe", "marketing-operations", "creative-production", "task-management", "work-management" ], "use_cases": [ "Query Workfront project status, task assignments, and deadlines from Claude or ChatGPT without switching to the Workfront dashboard, enabling project managers to get quick updates during planning sessions", "Create and update Workfront tasks, issues, and work items through natural-language AI assistant conversations, reducing manual data entry for marketing operations and creative production teams", "Analyze project performance metrics and workload distribution across teams by asking AI assistants to pull and summarize Workfront data, supporting resource planning and capacity decisions" ], "health": "active" }, { "id": "parallel-search-mcp", "name": "Parallel Search MCP Server", "description": "MCP server from Parallel AI that gives LLMs and AI agents instant access to real-time web knowledge through a plug-and-play search API. Exposes the Parallel Search API as an MCP tool that AI assistants can call to retrieve current web information, eliminating the need for custom search integrations. Designed for developers building AI applications that need grounded, up-to-date answers from the web. Supports simple configuration and works with any MCP-compatible client.", "category": "web", "endpoint": "Parallel Search MCP", "homepage_url": "https://parallel.ai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-18", "updated": "2026-07-18", "tags": [ "search", "web-search", "real-time", "grounding", "rag", "knowledge-retrieval", "api" ], "use_cases": [ "Give AI agents real-time web search capabilities through a single MCP tool call, enabling grounded responses with current information instead of relying solely on training data", "Build AI applications with up-to-date web knowledge retrieval by connecting any MCP-compatible client to the Parallel Search API through simple plug-and-play configuration", "Augment LLM responses with live web results for fact-checking, research, and real-time information queries without building custom search infrastructure or managing API integrations" ], "health": "active" }, { "id": "wpvibe-mcp", "name": "WPVibe MCP Server", "description": "MCP server plugin for WordPress that connects Claude, ChatGPT, Gemini, Cursor, and any MCP-compatible AI agent directly to self-hosted WordPress sites. Enables AI assistants to manage content, edit themes, run WP-CLI commands, and automate site operations without opening the WordPress dashboard. Installs as a standard WordPress plugin and exposes site capabilities through secure MCP endpoints. Supports creating and editing posts and pages, managing users, checking site status, and executing arbitrary WP-CLI commands for advanced automation. Published on WordPress.org and maintained by Awesome Motive.", "category": "productivity", "endpoint": "WPVibe MCP", "homepage_url": "https://wordpress.org/plugins/vibe-ai/", "github_url": "https://github.com/awesomemotive/wpvibe-ai-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "wordpress", "cms", "content-management", "web-publishing", "automation", "open-source", "wp-cli" ], "use_cases": [ "Create, edit, and publish WordPress posts and pages through natural-language conversations in Claude or ChatGPT, turning AI assistants into a full content management interface without opening the WordPress dashboard", "Automate WordPress site maintenance by running WP-CLI commands through AI agents for plugin updates, database optimization, user management, and site health checks", "Connect Cursor or Claude Code to a WordPress site for AI-assisted theme editing, content migration, and bulk operations that would normally require direct server access" ], "health": "active" }, { "id": "zscaler-mcp", "name": "Zscaler Integration MCP Server", "description": "Open-source MCP server from Zscaler that connects AI agents with the Zscaler Zero Trust Exchange platform for unified security automation. Acts as a secure bridge between AI assistants and Zscaler's APIs, enabling policy queries, configuration management, and multi-step security workflows through natural language. Supports managing several Zscaler products including ZIA, ZPA, and ZDX from Claude, Cursor, or any MCP-compatible client. Designed for security teams who want to automate zero trust operations, investigate incidents, and manage policies using AI agents while maintaining full audit trails.", "category": "infrastructure", "endpoint": "zscaler-mcp-server", "homepage_url": "https://www.zscaler.com/blogs/product-insights/zscaler-integrations-mcp-server-unified-security-automation-your-ai-agents", "github_url": "https://github.com/zscaler/zscaler-mcp-server", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "security", "zero-trust", "enterprise", "network-security", "policy-management", "open-source", "compliance" ], "use_cases": [ "Query and manage Zscaler ZIA, ZPA, and ZDX security policies through natural-language AI assistant conversations, enabling security teams to automate routine policy changes without navigating multiple dashboards", "Investigate security incidents by having AI agents correlate Zscaler Zero Trust Exchange data, identify affected users and applications, and suggest remediation steps based on current policy configurations", "Automate complex multi-step security workflows like onboarding new applications to zero trust access, configuring URL filtering rules, and auditing access policies by connecting Claude Code to the Zscaler MCP server" ], "health": "active" }, { "id": "commercetools-mcp", "name": "commercetools Managed MCP Server", "description": "Managed MCP server from commercetools that exposes the composable commerce platform's tools to AI agents via the Model Context Protocol. Became generally available on July 16, 2026, enabling AI assistants to interact with commercetools projects for product catalog management, order operations, cart handling, and customer data queries. Configured through the commercetools project settings and hosted as a managed service, eliminating the need for self-hosted infrastructure. Part of commercetools' AI-native commerce strategy for enabling next-generation agentic customer experiences.", "category": "data", "endpoint": "commercetools MCP", "homepage_url": "https://docs.commercetools.com/docs/release-notes", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "ecommerce", "composable-commerce", "enterprise", "product-catalog", "order-management", "headless-commerce", "managed" ], "use_cases": [ "Query product catalogs, check inventory levels, and manage pricing through AI agents connected to the commercetools MCP server, enabling merchandising teams to make data-driven decisions through natural conversation", "Build AI-powered customer service workflows that can look up orders, process returns, and update customer records in commercetools directly from an AI assistant without custom API integration code", "Enable agentic commerce experiences where AI agents create and manage shopping carts, apply promotions, and complete checkout flows on behalf of customers through the commercetools composable commerce platform" ], "health": "active" }, { "id": "ngram-mcp", "name": "ngram MCP Server", "description": "MCP server from ngram that enables AI agents to generate professional product demo videos directly from code context. Connects to Claude, Codex, and other MCP-compatible clients to create product videos using specs, release notes, documentation, screenshots, and application state as inputs. Supports the full video production workflow from prompt to rendered output including approval, rendering, progress tracking, review, and QA steps. Designed for developer marketing and product teams who want to automate demo video creation as part of their release process. Updated July 16, 2026.", "category": "media", "endpoint": "ngram MCP", "homepage_url": "https://www.ngram.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "video-generation", "product-demos", "developer-marketing", "automation", "content-creation", "ai-video", "release-management" ], "use_cases": [ "Generate product demo videos automatically from release notes and documentation by connecting Claude Code or Codex to the ngram MCP server, producing professional videos without manual video editing", "Automate the product marketing video pipeline by having AI agents create demo videos from application screenshots and specs, with built-in approval, rendering, and quality assurance workflow steps", "Create per-feature demo videos as part of CI/CD release workflows by triggering ngram video generation from AI agents that have access to the latest code changes and documentation" ], "health": "active" }, { "id": "insider-one-mcp", "name": "Insider One MCP Server", "description": "MCP server from Insider One that connects AI systems directly to live marketing and customer engagement data. Enables marketing teams and AI agents to query customer segments, campaign performance, and behavioral analytics through natural-language conversations. Designed for teams using the Insider One customer data platform who want AI assistants to surface actionable insights, optimize campaigns, and make data-driven engagement decisions without manual dashboard navigation.", "category": "data", "endpoint": "Insider One MCP", "homepage_url": "https://www.insiderone.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "marketing", "customer-engagement", "analytics", "customer-data-platform", "personalization", "campaign-management", "martech" ], "use_cases": [ "Query live customer segments and behavioral data through AI assistants to make faster marketing decisions without navigating the Insider One dashboard or writing custom analytics queries", "Optimize campaign performance by having AI agents analyze engagement metrics, identify underperforming segments, and suggest targeting adjustments based on real-time Insider One data", "Build AI-powered marketing workflows that automatically surface anomalies in customer behavior, churn signals, and engagement opportunities by connecting agents to the Insider One MCP server" ], "health": "active" }, { "id": "grasshopper-bank-mcp", "name": "Grasshopper Bank MCP Server", "description": "MCP server from Grasshopper Bank that brings AI-driven financial insights to banking clients while preserving data control and compliance. Enables authorized AI agents to query account data, analyze transaction patterns, and surface financial intelligence through the Model Context Protocol. Designed for fintech-forward banking clients who want AI assistants to help with cash flow analysis, transaction categorization, and financial planning without compromising regulatory compliance or data sovereignty.", "category": "data", "endpoint": "Grasshopper Bank MCP", "homepage_url": "https://www.grasshopper.bank/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-19", "updated": "2026-07-19", "tags": [ "banking", "fintech", "financial-data", "compliance", "enterprise", "cash-flow", "transaction-analytics" ], "use_cases": [ "Analyze cash flow patterns and transaction history through AI agents connected to Grasshopper Bank's MCP server, enabling CFOs and finance teams to get instant insights without exporting data to spreadsheets", "Automate financial reporting and anomaly detection by having AI assistants query banking data in real time, flagging unusual transactions and generating summary reports for compliance reviews", "Enable AI-powered financial planning conversations where agents can access live account balances, pending transactions, and historical trends to provide informed recommendations while maintaining bank-grade data controls" ], "health": "active" }, { "id": "customerio-mcp", "name": "Customer.io MCP Server", "description": "Official MCP server from Customer.io that connects the marketing automation platform to AI assistants through the Model Context Protocol. Gives AI agents full access to the Customer.io Journeys UI API and CDP Data Pipelines API, enabling natural-language management of automations, segments, profiles, one-time sends, templates, and delivery metrics. Supports both US and EU regions with OAuth 2.1 authentication. Features granular permission scopes separating read, write, delete, and sensitive data access. Includes built-in agent skills that teach AI tools Customer.io-specific workflows. Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Updated July 15, 2026.", "category": "productivity", "endpoint": "https://mcp.customer.io/mcp", "homepage_url": "https://docs.customer.io/ai/mcp/get-started/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "marketing-automation", "email", "messaging", "customer-engagement", "cdp", "segmentation", "oauth", "enterprise" ], "use_cases": [ "Manage marketing automations, segments, and one-time sends through natural-language prompts in Claude or ChatGPT, eliminating the need to navigate the Customer.io dashboard for routine campaign operations", "Query delivery metrics, profile data, and campaign performance from AI coding assistants like Cursor, enabling developers to debug messaging workflows and validate integration behavior without switching tools", "Set up and troubleshoot Customer.io SDK integrations for iOS, Android, and React Native directly through AI assistants using the MCP server's built-in skills that guide step-by-step installation and debugging" ], "health": "active" }, { "id": "pixazo-mcp", "name": "Pixazo MCP Server", "description": "MCP server platform from Pixazo that provides plug-and-play access to leading AI image and video generation models natively inside any MCP-compatible AI assistant. Offers per-model MCP servers for Nano Banana (Google image generation), Seedance (ByteDance video), Runway (cinematic video), and Flux (Black Forest Labs image generation), plus additional servers for audio, music, 3D, upscaling, and virtual try-on. Developers authenticate once with OAuth through a Pixazo account and use unified credits across all models. Each model runs as a dedicated server for tighter control over outputs and predictable latency. Launched July 16, 2026.", "category": "media", "endpoint": "https://gateway.pixazo.ai/pixazo/mcp", "homepage_url": "https://www.pixazo.ai/models/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add pixazo https://gateway.pixazo.ai/pixazo/mcp", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "image-generation", "video-generation", "ai-models", "creative-tools", "text-to-image", "text-to-video", "multi-model", "oauth" ], "use_cases": [ "Generate production-quality images and videos directly from Claude Code or ChatGPT by calling specific AI models like Flux for images or Runway for cinematic video through Pixazo's per-model MCP servers with unified billing", "Build multi-model creative workflows where AI agents use Flux for product images and Seedance for promotional videos in a single session, mixing models across different steps without managing separate API keys", "Prototype AI-powered creative tools and marketing automation pipelines by connecting Pixazo MCP to Cursor or Claude Code for rapid iteration on image and video generation with OAuth authentication and pay-per-call pricing" ], "health": "active" }, { "id": "betterworks-mcp", "name": "Betterworks MCP Server", "description": "MCP server from Betterworks that connects enterprise performance management data to AI assistants including ChatGPT, Claude, Microsoft Copilot, and Gemini. Enables managers, leaders, and HR teams to query goals, recognition, team performance, and organizational insights through natural language. Respects existing authentication and native permission models so users only access information they already have permission to see. Currently in beta with access to goals, teams, users, recognition, and hashtags. Announced July 14, 2026.", "category": "productivity", "endpoint": "Betterworks MCP", "homepage_url": "https://www.betterworks.com/magazine/betterworks-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "hr", "performance-management", "enterprise", "goals", "team-management", "recognition", "people-analytics" ], "use_cases": [ "Prepare for one-on-one meetings by asking an AI assistant to summarize a direct report's goal progress, recent recognition, and performance trends from Betterworks data without manually pulling reports", "Identify at-risk quarterly goals across a team by querying Betterworks through Claude or Copilot, enabling managers to surface emerging problems and coach employees before deadlines pass", "Generate leadership-ready performance updates by having AI agents pull team goals, recognition trends, and organizational insights from Betterworks and format them into structured reports" ], "health": "active" }, { "id": "sharegate-mcp", "name": "ShareGate MCP Server", "description": "MCP server from ShareGate that connects the ShareGate Protect Microsoft 365 governance platform to Claude, ChatGPT, and Microsoft Copilot. Enables IT administrators to query governance data including sharing patterns, guest access, workspace activity, sensitivity labels, ownership history, and license usage through natural-language prompts. Tracks trends over time so administrators can see how governance posture is changing. Designed to work alongside other MCP servers like Microsoft Work IQ for richer cross-platform answers. Write actions for remediation planned for July 2026. Included at no extra cost with ShareGate Protect. Launched June 22, 2026.", "category": "infrastructure", "endpoint": "ShareGate MCP", "homepage_url": "https://sharegate.com/mcp/install", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "microsoft-365", "governance", "security", "sharepoint", "compliance", "it-admin", "enterprise", "license-management" ], "use_cases": [ "Generate weekly Microsoft 365 governance summaries by asking Claude or Copilot to report on new oversharing findings, remediated sites, external guest exposure trends, and idle license counts from ShareGate Protect data", "Find high-risk access patterns by querying ShareGate MCP alongside Microsoft's Work IQ to identify the most active users in ownerless workspaces and suggest ownership assignments based on actual usage data", "Audit guest access and license waste by asking AI assistants to list inactive users still holding paid licenses or guests with access to sensitive sites who have not signed in for 90 days" ], "health": "active" }, { "id": "meta-devtools-mcp", "name": "Meta Developer Tools MCP Server", "description": "Beta MCP server from Meta that lets AI coding assistants read and manage Meta app configuration without opening the Meta for Developers dashboard. Exposes 10 tools covering API documentation search, app settings inspection, App Review status, compliance monitoring, API usage and rate limits, and webhook subscription management. Write access is limited to webhook subscriptions only. Uses OAuth authentication tied to a developer's existing Meta account with per-app Read and Manage scopes. Compatible with Claude Code, Claude Desktop, ChatGPT, Codex, and Cursor. Announced June 30, 2026.", "category": "code", "endpoint": "https://mcp.facebook.com/devtools", "homepage_url": "https://developers.facebook.com/docs/mcp/developer-tools/", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http meta_developer_tools https://mcp.facebook.com/devtools", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "meta", "facebook", "developer-tools", "api-management", "webhooks", "compliance", "app-review", "oauth" ], "use_cases": [ "Inspect Meta app settings, security configuration, and platform restrictions from inside Claude Code or Cursor without navigating the Meta for Developers dashboard, keeping developers in their coding environment", "Proactively monitor Data Access Renewal compliance status through AI agents that flag required actions before deadlines pass, preventing silent loss of app access from missed email notifications", "Debug Meta API integration issues by having AI assistants check rate limits, API deprecations, and call volume alongside App Review status and webhook subscription health in a single conversation" ], "health": "active" }, { "id": "acst-mp-mcp", "name": "ACST MP-MCP Server", "description": "MCP server from ACST that provides a secure AI gateway connecting MinistryPlatform church management data to AI assistants including Claude, ChatGPT, and Microsoft Copilot. Enables church administrators and staff to query member information, attendance, giving, groups, and event data through natural-language prompts while maintaining data privacy and security controls. Designed for organizations using the MinistryPlatform CRM to bring AI-powered insights to church operations without exposing sensitive congregational data to third-party AI training. Announced July 14, 2026 with general availability upcoming.", "category": "data", "endpoint": "ACST MP-MCP", "homepage_url": "https://www.acst.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "church-management", "crm", "nonprofit", "membership", "attendance", "giving", "ministry" ], "use_cases": [ "Query member attendance patterns, small group participation, and giving trends through AI assistants connected to MinistryPlatform, enabling church leaders to identify pastoral care needs without running manual reports", "Prepare for board meetings and leadership updates by asking AI agents to summarize congregational metrics, event attendance, and financial giving data from MinistryPlatform in a structured format", "Enable church administrative staff to answer operational questions about facility bookings, volunteer schedules, and member contact information through natural-language AI queries instead of navigating complex CRM interfaces" ], "health": "active" }, { "id": "oracle-analytics-cloud-mcp", "name": "Oracle Analytics Cloud MCP Server", "description": "MCP server from Oracle that exposes Oracle Analytics Cloud tools to AI agents through the Model Context Protocol. Introduced in the July 2026 Oracle Analytics Cloud release as a preview feature. Enables AI assistants to discover datasets, run analyses, create visualizations, and query business intelligence data through natural-language prompts. Designed for enterprise analytics teams who want to integrate Oracle Analytics capabilities into AI-powered workflows without building custom API integrations. Based on the MCP Protocol 2025 specification.", "category": "data", "endpoint": "Oracle Analytics Cloud MCP", "homepage_url": "https://docs.oracle.com/en/cloud/paas/analytics-cloud/acsdv/access-oracle-analytics-cloud-mcp-server-preview.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "analytics", "business-intelligence", "oracle", "enterprise", "data-visualization", "cloud", "reporting" ], "use_cases": [ "Query Oracle Analytics Cloud datasets and run ad-hoc analyses through AI assistants, enabling business users to get answers to data questions without learning the OAC interface or writing SQL", "Automate business intelligence reporting by having AI agents pull analytics data from Oracle Analytics Cloud and generate executive summaries, trend analyses, and anomaly alerts through natural-language prompts", "Integrate Oracle Analytics capabilities into multi-tool AI workflows where agents combine OAC data with information from other MCP-connected systems for comprehensive cross-platform business analysis" ], "health": "active" }, { "id": "bumpsh-mcp", "name": "Bump.sh MCP Server", "description": "MCP server generator from Bump.sh that automatically creates white-label MCP servers from existing API documentation. Generates MCP servers from OpenAPI specifications and hosts them as managed services. Supports custom domains via CNAME so servers appear at mcp.yourcompany.com, and custom OAuth integration with any identity provider including Okta, Auth0, and Keycloak. Available on every Bump.sh plan. Enables API providers to offer AI-native access to their APIs without building custom MCP implementations. Exited beta and became generally available July 2026.", "category": "code", "endpoint": "Bump.sh MCP", "homepage_url": "https://docs.bump.sh/product-updates/2026/07/06/mcp-servers-custom-oauth-custom-domain/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-20", "updated": "2026-07-20", "tags": [ "api-documentation", "openapi", "developer-tools", "white-label", "custom-domain", "api-management", "mcp-generator" ], "use_cases": [ "Generate production-ready MCP servers automatically from existing OpenAPI documentation, enabling API providers to offer AI-native access to their APIs without writing custom MCP server code", "White-label AI agent access to your API by hosting the generated MCP server on your own domain with your own OAuth provider, so AI assistants authenticate through your identity system without seeing the Bump.sh brand", "Enable AI coding assistants like Claude Code and Cursor to discover and use your API operations through natural language by pointing them at a Bump.sh-generated MCP server that stays in sync with your API documentation" ], "health": "active" }, { "id": "d1g1t-mcp", "name": "d1g1t MCP Server", "description": "MCP server from d1g1t, a leading wealthtech provider, that connects its enterprise wealth management platform to Claude, ChatGPT, and Microsoft Copilot. Enables financial advisors to pull household holdings, summarize year-to-date performance, flag mandate breaches, generate client reports, and prepare for meetings using natural language. Exposes the platform's core capabilities as tools that AI agents can call on an advisor's behalf to search, read, and reason over live portfolio data. Announced July 20, 2026.", "category": "productivity", "endpoint": "d1g1t MCP", "homepage_url": "https://www.d1g1t.com/mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "wealth-management", "financial-advisor", "portfolio", "compliance", "reporting", "enterprise", "wealthtech" ], "use_cases": [ "Prepare for client meetings by asking Claude or ChatGPT to summarize a household's holdings, year-to-date performance, outstanding tasks, and pending trades from live d1g1t data without navigating the platform manually", "Generate on-demand client reports and forward-looking growth projections by describing what you need in plain language, with the AI securely retrieving live portfolio data from the d1g1t platform", "Monitor compliance proactively by having AI agents flag mandate breaches, surface risk exposures, and check drift across portfolios using d1g1t's institutional-grade analytics engine" ], "health": "active" }, { "id": "amplemarket-mcp", "name": "Amplemarket MCP Server", "description": "Official MCP server from Amplemarket, the AI sales platform, that gives Claude, ChatGPT, Cursor, and Claude Code live access to its B2B prospecting database and outbound execution engine. Supports the complete outbound workflow: find net-new prospects by title, seniority, industry, and company filters; enrich and research contacts with firmographic and intent data; build personalized multichannel sequences with configured messaging settings; and enroll leads into live outreach with per-lead personalization. Authentication via browser-based OAuth scoped to each user's Amplemarket permissions. Includes 36+ pre-built GTM skills for one-click prospecting, account research, call prep, and pipeline analysis. Launched March 2026.", "category": "productivity", "endpoint": "https://mcp.amplemarket.com", "homepage_url": "https://www.amplemarket.com/blog/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "sales", "outbound", "prospecting", "b2b", "lead-generation", "sequences", "enrichment", "intent-data", "oauth" ], "use_cases": [ "Run the entire outbound sales workflow from inside Claude or ChatGPT: find net-new prospects by ICP criteria, enrich contacts, build personalized multichannel sequences, and enroll leads into live outreach without leaving the conversation", "Prepare for sales calls in seconds by asking an AI assistant to pull a prospect's company details, recent activity, tech stack, and buying signals from Amplemarket's 200M+ B2B contact database", "Build and launch personalized outbound sequences from AI coding tools like Cursor or Claude Code by connecting to Amplemarket's MCP server with OAuth, using configured value propositions and tone-of-voice settings" ], "health": "active" }, { "id": "borisfx-silhouette-mcp", "name": "Boris FX Silhouette MCP Server", "description": "MCP server built into Boris FX Silhouette, the professional VFX and post-production compositing application. Lets AI assistants work directly inside Silhouette projects using the FX Scripting API as first-class MCP tools. Assistants can inspect projects, build node trees, edit shapes and keyframes, and render frames. Supports interactive online mode connected to an active session and offline headless mode for automation, batch processing, and large-scale workflows. A new preferences panel simplifies setup by installing the MCP package, generating client configuration, and testing the connection. Announced at SIGGRAPH July 20, 2026 alongside NVIDIA agentic AI creative ecosystem updates.", "category": "media", "endpoint": "Boris FX Silhouette MCP", "homepage_url": "https://borisfx.com/products/silhouette/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "vfx", "compositing", "post-production", "creative-tools", "video-editing", "node-based", "batch-processing", "siggraph" ], "use_cases": [ "Automate repetitive VFX compositing tasks by having AI assistants build node trees, edit roto shapes, and adjust keyframes inside Boris FX Silhouette projects through natural language commands via MCP", "Run headless batch processing and large-scale VFX automation pipelines by connecting AI agents to Silhouette's offline MCP mode, enabling automated rendering and project manipulation without a GUI", "Accelerate creative workflows by letting AI assistants inspect Silhouette project structures, suggest node configurations, and render preview frames during interactive compositing sessions" ], "health": "active" }, { "id": "mployer-mcp", "name": "Mployer MCP Server", "description": "MCP server from Mployer, the employee benefits and insurance intelligence platform, that gives partners and advisors access to Mployer's proprietary benefits data and analytics within their own AI tools. Part of Mployer's Expanded AI Release powered by Anthropic, which includes MCP Server integration and Claude Connectors. Enables benefits advisors and brokers to query employer benefits data, compare plan options, and surface insurance intelligence through AI assistants. July 2026.", "category": "productivity", "endpoint": "Mployer MCP", "homepage_url": "https://mployeradvisor.com/blog/mployer-launches-expanded-ai-release-powered-by-anthropic", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "employee-benefits", "insurance", "hr", "benefits-intelligence", "advisors", "brokers", "anthropic" ], "use_cases": [ "Query Mployer's proprietary employee benefits data and employer intelligence from Claude or other AI assistants to compare plan options and surface benefits insights without navigating the Mployer dashboard", "Enable benefits advisors and insurance brokers to access Mployer's analytics and benchmarking data through natural language conversations in AI tools powered by Anthropic", "Integrate Mployer benefits intelligence into partner platforms and advisory workflows by connecting through the MCP server for automated plan analysis and employer data retrieval" ], "health": "active" }, { "id": "workato-mcp-registry", "name": "Workato Enterprise MCP Registry", "description": "Enterprise MCP Registry from Workato that gives organizations a governed system of record for discovering, securing, and governing AI tool capabilities at scale. Unlike Workato's existing MCP server for automation execution, the Enterprise MCP Registry is a management layer that catalogs all MCP servers and tools across the organization, enforces access policies, tracks usage, and provides a single control plane for IT and security teams to manage which AI agents can call which enterprise tools. Announced July 16, 2026.", "category": "infrastructure", "endpoint": "Workato Enterprise MCP Registry", "homepage_url": "https://www.businesswire.com/news/home/20260716488768/en/Workato-Launches-Enterprise-MCP-Registry-Advancing-the-Enterprise-AI-Control-and-Execution-Platform", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "enterprise", "governance", "registry", "access-control", "security", "mcp-management", "it-operations", "compliance" ], "use_cases": [ "Catalog and govern all MCP servers and AI tool capabilities across the enterprise from a single control plane, enabling IT teams to enforce access policies and track which agents call which tools", "Provide a discoverable registry of approved enterprise MCP tools that AI agents and assistants can query to find authorized capabilities without IT teams manually configuring each integration", "Enforce security and compliance policies on AI agent tool access at scale by routing all MCP discovery and invocation through Workato's governed registry with audit logging and role-based controls" ], "health": "active" }, { "id": "rogo-snowflake-mcp", "name": "Rogo Snowflake MCP Server", "description": "MCP server integration between Rogo, the AI-native finance platform, and Snowflake that lets customers bring proprietary data securely into Rogo's platform while retaining all governance controls. Enables financial analysts and research teams to query Snowflake data warehouses through Rogo's AI assistants, combining proprietary structured data with Rogo's financial analysis capabilities. Maintains Snowflake's existing access controls and data governance policies. Announced July 15, 2026.", "category": "data", "endpoint": "Rogo Snowflake MCP", "homepage_url": "https://www.prnewswire.com/news-releases/rogo-and-snowflake-extend-integration-to-power-ai-native-finance-workflows-302825654.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "finance", "snowflake", "data-warehouse", "financial-analysis", "research", "governance", "enterprise" ], "use_cases": [ "Query proprietary financial data stored in Snowflake through Rogo's AI-native finance platform, combining structured warehouse data with AI analysis capabilities while retaining all existing governance controls", "Enable financial research teams to access and analyze Snowflake data warehouses through natural language conversations in Rogo, eliminating the need to write SQL queries for routine financial analysis", "Build AI-native finance workflows that securely bridge Snowflake data governance with Rogo's financial AI capabilities for automated reporting, analysis, and research across proprietary datasets" ], "health": "active" }, { "id": "sap-business-ai-mcp", "name": "SAP Business AI MCP Server", "description": "MCP server capabilities within SAP's Business AI platform, part of the Q2 2026 product release announced at SAP Sapphire. Enables AI agents and assistants to connect to SAP enterprise systems through the Model Context Protocol, providing governed access to business data across ERP, supply chain, HR, and finance modules. Designed for enterprise-scale SAP customers who want to connect external AI tools like Claude, ChatGPT, and Microsoft Copilot to their SAP data without building custom integrations. July 2026.", "category": "infrastructure", "endpoint": "SAP Business AI MCP", "homepage_url": "https://news.sap.com/2026/07/sap-business-ai-release-highlights-q2-2026/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-21", "updated": "2026-07-21", "tags": [ "erp", "enterprise", "sap", "supply-chain", "finance", "hr", "business-intelligence", "governance" ], "use_cases": [ "Connect AI assistants like Claude or Copilot to SAP enterprise data across ERP, supply chain, HR, and finance modules for natural language querying of business operations without building custom integrations", "Enable enterprise teams to access SAP business intelligence and transactional data through AI agents with full governance controls, maintaining SAP's existing role-based access and audit requirements", "Build agentic AI workflows that span SAP enterprise systems by connecting to SAP's MCP server for automated reporting, process monitoring, and cross-module data analysis at enterprise scale" ], "health": "active" }, { "id": "crunchbase-mcp", "name": "Crunchbase MCP Server", "description": "MCP server from Crunchbase that brings private market intelligence directly into AI assistants including Claude, ChatGPT, Gemini and Cursor. Draws on more than 39 billion live private market signals, 790 data fields per company and 15 million predictions. Prediction models have accurately anticipated 84 percent of real-world funding events before they occurred. Enables investors, analysts and revenue teams to query company data, funding history, competitive landscape and predictive signals through natural language. Announced and available July 21, 2026.", "category": "data", "endpoint": "Crunchbase MCP", "homepage_url": "https://www.crunchbase.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "private-markets", "venture-capital", "funding", "company-intelligence", "predictions", "investors", "deal-flow", "competitive-intelligence" ], "use_cases": [ "Query Crunchbase from Claude or ChatGPT to research a company's funding history, leadership team, competitive landscape and growth signals using natural language instead of navigating the Crunchbase dashboard", "Enable investment AI agents to surface predictive funding signals and identify companies likely to raise their next round by connecting to Crunchbase's 15 million prediction models through MCP", "Build competitive intelligence workflows that pull live private market data from Crunchbase into AI coding tools like Cursor for automated deal sourcing, market mapping and portfolio monitoring" ], "health": "active" }, { "id": "bolddesk-mcp", "name": "BoldDesk MCP Server", "description": "Hosted MCP server from Syncfusion's BoldDesk AI 2.0, the customer support helpdesk platform. Gives external AI tools like Claude, ChatGPT, Gemini and GitHub Copilot secure, direct access to BoldDesk support workflows. Enables AI agents to query tickets, manage customer interactions, search knowledge bases and automate support operations through the Model Context Protocol. Part of the BoldDesk AI 2.0 release, which was named finalist in four SaaS Awards categories. Announced July 21, 2026.", "category": "productivity", "endpoint": "BoldDesk MCP Server", "homepage_url": "https://www.bolddesk.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "customer-support", "helpdesk", "ticketing", "knowledge-base", "saas", "syncfusion", "ai-support" ], "use_cases": [ "Connect Claude, ChatGPT or Gemini to your BoldDesk instance to query ticket status, search knowledge base articles and manage customer support workflows through natural language", "Enable AI coding agents like GitHub Copilot to access BoldDesk support data for building integrations, generating reports and automating ticket triage without switching to the helpdesk dashboard", "Automate customer support operations by letting AI agents create tickets, update statuses, assign agents and pull resolution metrics from BoldDesk through the hosted MCP server" ], "health": "active" }, { "id": "onesignal-mcp", "name": "OneSignal MCP Server", "description": "MCP server from OneSignal, the customer engagement platform trusted by more than one million businesses. Built on the open Model Context Protocol with OAuth support, it lets AI assistants including Claude, ChatGPT, Cursor and Copilot securely operate OneSignal on a user's behalf. Covers messaging, users and subscriptions, segments, templates, exports and analytics. Part of OneSignal's vision for autonomous lifecycle marketing, where AI agents can pull behavioral data, identify drop-off points, build segments, draft copy and schedule sends in a single conversation. Open beta available to every OneSignal account. Announced July 14, 2026.", "category": "productivity", "endpoint": "OneSignal MCP", "homepage_url": "https://onesignal.com/ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "customer-engagement", "push-notifications", "lifecycle-marketing", "messaging", "segments", "analytics", "marketing-automation", "oauth" ], "use_cases": [ "Run the entire lifecycle marketing workflow from inside Claude or ChatGPT: pull behavioral data from a warehouse, find where new users drop off, build a segment in OneSignal, draft the copy and schedule the sends without leaving the conversation", "Connect AI coding agents to OneSignal's MCP server with OAuth to automate notification campaigns, manage user segments and pull engagement analytics directly from development environments", "Enable autonomous marketing AI agents to monitor user engagement patterns, create targeted segments and launch personalized push notification campaigns through OneSignal's governed MCP connection" ], "health": "active" }, { "id": "bagel-ai-mcp", "name": "Bagel AI MCP Server", "description": "MCP server from Bagel AI, the autonomous product decision layer for AI-native teams. Part of the Everything AI platform, the Bagel MCP exposes product decisions to any MCP client including Claude Code, Cursor, Codex and Glean. When a developer opens a ticket, the AI agent queries Bagel AI and retrieves who requested the feature, the deal value at stake and the requirements. Connects customer feedback, revenue data and roadmap context so coding agents build the right thing from the start. Announced July 14, 2026.", "category": "productivity", "endpoint": "Bagel AI MCP", "homepage_url": "https://bagel.ai/platform-overview/bagel-mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "product-management", "decision-intelligence", "customer-feedback", "roadmap", "developer-tools", "ai-native", "product-decisions" ], "use_cases": [ "Give Claude Code or Cursor real product context by connecting to the Bagel MCP server so coding agents automatically retrieve who requested a feature, the deal value at stake and the requirements before writing any code", "Enable product and engineering teams to make data-driven build decisions by having AI agents surface customer evidence, revenue impact and competitive context from Bagel AI through natural language", "Connect AI-driven development workflows to Bagel's decision layer so every Linear ticket, PR or design review is grounded in validated customer signals and business impact rather than assumptions" ], "health": "active" }, { "id": "affinity-canva-mcp", "name": "Affinity by Canva AI Connector MCP", "description": "MCP-based AI Connector from Affinity by Canva that brings natural-language automation directly into the Affinity design suite (Designer, Photo, Publisher). Lets Claude handle repetitive production tasks such as renaming layers and artboards, resizing and reformatting assets for multiple channels, applying bulk edits, optimizing vector paths and preparing files for delivery. Also enables users to build reusable scripts and custom features tailored to their workflows. Announced at SIGGRAPH July 20, 2026 as part of NVIDIA's agentic AI creative ecosystem updates.", "category": "media", "endpoint": "Affinity by Canva AI Connector", "homepage_url": "https://affinity.serif.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "design", "creative-tools", "graphic-design", "vector", "photo-editing", "publishing", "canva", "siggraph", "automation" ], "use_cases": [ "Automate repetitive design production tasks by asking Claude to rename layers, resize assets for multiple channels, apply bulk edits and optimize vector paths inside Affinity Designer, Photo or Publisher", "Build reusable scripts and custom design features through natural language by connecting Claude to Affinity's MCP connector, reducing production overhead for creative professionals", "Prepare files for delivery across multiple formats and channels by having AI assistants handle batch reformatting, artboard management and export variant generation inside the Affinity design suite" ], "health": "active" }, { "id": "sidefx-houdini-mcp", "name": "SideFX Houdini 22 MCP Server", "description": "MCP support built into SideFX Houdini 22 through the new APEX Script workflow. AI assistants can access a curated collection of APEX Script syntax, functions, documentation and examples, helping artists generate and refine code for procedural character rigs. Initial implementation focuses on APEX Script and character rigging, while community-developed MCP servers offer broader ways for agents to interact with Houdini. Announced at SIGGRAPH July 20, 2026 as part of NVIDIA's agentic AI creative ecosystem updates.", "category": "media", "endpoint": "SideFX Houdini 22 MCP", "homepage_url": "https://www.sidefx.com/products/houdini/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "vfx", "procedural", "character-rigging", "3d", "creative-tools", "houdini", "siggraph", "apex-script" ], "use_cases": [ "Generate and refine procedural character rigs by asking AI assistants to write APEX Script code using Houdini 22's built-in MCP server with curated syntax documentation and examples", "Accelerate VFX artist workflows by connecting Claude or ChatGPT to Houdini 22 for natural language access to APEX Script functions, procedural setups and character rigging documentation", "Build complex procedural setups faster by having AI assistants reference Houdini's APEX Script syntax and function library through MCP while artists focus on creative direction and iteration" ], "health": "active" }, { "id": "open-targets-platform-mcp", "name": "Open Targets Platform MCP Server", "description": "Official MCP server from Open Targets, the public-private partnership for systematic drug target identification and prioritization. Provides AI assistants with access to the Open Targets Platform GraphQL API for querying disease-target associations, drug mechanisms, genetic evidence, clinical trial data and pharmacogenomics information. Enables drug discovery researchers and bioinformaticians to search diseases, find prioritized therapeutic targets, explore drug pipelines and analyze genetic associations through natural language. Open source on GitHub.", "category": "data", "endpoint": "Open Targets Platform MCP", "homepage_url": "https://platform.opentargets.org/", "github_url": "https://github.com/opentargets/open-targets-platform-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "drug-discovery", "genomics", "bioinformatics", "therapeutics", "clinical-trials", "open-science", "graphql", "life-sciences" ], "use_cases": [ "Search for disease-target associations and prioritized therapeutic targets by asking AI assistants to query the Open Targets Platform through MCP, accelerating early-stage drug discovery research", "Explore drug pipelines, clinical trial data and mechanism of action information for specific targets by connecting AI coding tools to the Open Targets MCP server for automated evidence aggregation", "Analyze genetic evidence linking genes to diseases by having AI assistants retrieve GWAS associations, functional genomics data and pharmacogenomics information from the Open Targets Platform" ], "health": "active" }, { "id": "axonius-mcp", "name": "Axonius MCP Server", "description": "MCP server from Axonius, the asset intelligence platform for unified security operations and exposure management. Connects AI assistants and agents to the Axonius Asset Cloud, translating natural language questions into Axonius Query Language (AQL) and returning live asset data. Gives security and IT teams a governed source of asset truth inside the AI tools they already use, including Claude, ChatGPT and Copilot. Covers devices, users, software, cloud resources, vulnerabilities and exposures across the entire environment. Announced July 21, 2026 alongside the Axonius AI Agent and Docs for AI.", "category": "infrastructure", "endpoint": "Axonius MCP Server", "homepage_url": "https://www.axonius.com/newsroom/press-release/axonius-launches-ai-agent-and-mcp-server-to-seamlessly-connect-asset-intelligence-to-enterprise-ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-22", "updated": "2026-07-22", "tags": [ "cybersecurity", "asset-intelligence", "exposure-management", "security-operations", "vulnerability", "enterprise", "it-operations" ], "use_cases": [ "Query the Axonius Asset Cloud from Claude or ChatGPT to get a real-time inventory of devices, users, software and cloud resources across your environment without navigating the Axonius dashboard", "Enable security AI agents to correlate asset data with vulnerability findings and exposure context by connecting to the Axonius MCP server for governed, decision-grade asset intelligence", "Accelerate incident response by asking AI assistants to identify affected assets, check patch status and surface coverage gaps using live data from the continuously reconciled Axonius asset model" ], "health": "active" }, { "id": "guideline-ad-intel-mcp", "name": "Guideline Ad Intelligence MCP Server", "description": "MCP server from Guideline giving AI agents secure access to proprietary ad spend, pricing and market intelligence data across 65 countries representing approximately 200 billion dollars in annual media investment. Enables agencies, brands, media owners and institutional investors to query competitive ad intelligence from any MCP-compatible AI application including Claude, ChatGPT, Gemini and Copilot. Users can compare category investment, benchmark pricing, analyze share-of-voice and test revenue assumptions using natural language. Complements Guideline's existing Media Plan Management MCP Server released in March 2026. Announced July 22, 2026.", "category": "data", "endpoint": "Guideline Ad Intelligence MCP", "homepage_url": "https://www.guideline.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "advertising", "ad-intelligence", "media", "ad-spend", "market-intelligence", "competitive-intelligence", "pricing", "enterprise" ], "use_cases": [ "Compare category ad investment, pricing benchmarks and share-of-voice data from Guideline's proprietary database while preparing a media pitch or client recommendation inside Claude or ChatGPT", "Enable marketing procurement and finance teams to benchmark their brand's media investment against category and subcategory peers by querying Guideline's ad intelligence through any MCP-compatible AI assistant", "Test revenue assumptions against observed advertising-spend signals across 65 countries by connecting institutional investor research workflows to Guideline's verified market intelligence via MCP" ], "health": "active" }, { "id": "glg-mcp", "name": "GLG MCP Connector", "description": "MCP connector from GLG, the world's leading platform for trusted human expertise, giving clients continuous access to expert research within AI tools. Enables users to query their complete project call history and named expert perspectives from GLG's Expert Content Library directly within AI platforms. Includes an agent that builds nuanced research angles with conversational input, helping users initiate primary research, surface new experts and synthesize insights without leaving their AI tools. Every query output traces back to specific expert conversations or content. Compliance officers retain full control over what enters AI tools. Announced July 22, 2026.", "category": "data", "endpoint": "GLG MCP Connector", "homepage_url": "https://www.glg.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "expert-network", "research", "consulting", "expert-intelligence", "due-diligence", "investment-research", "compliance" ], "use_cases": [ "Query your complete GLG project call history and named expert perspectives from inside Claude or ChatGPT to build on prior research without switching tools or re-reading transcripts", "Initiate primary expert research through natural language by having the GLG MCP agent build nuanced research angles, surface relevant experts and synthesize qualitative findings directly within AI workflows", "Trace every AI-generated insight back to a specific expert conversation or piece of GLG content for full attribution and compliance auditability in regulated research environments" ], "health": "active" }, { "id": "rocketreach-mcp", "name": "RocketReach MCP Server", "description": "MCP server from RocketReach, the sales and lead intelligence platform trusted by more than 30 million users and 95 percent of the S&P 500. Gives AI assistants direct real-time access to 700 million verified contacts and 60 million companies. Supports person search by title, location and company, company filtering by industry, size and funding stage, verified contact retrieval, detailed company profiles, simultaneous lookups and credit monitoring. Every lookup runs through real-time email verification. Uses OAuth 2.1 authentication. Compatible with ChatGPT, Claude and other MCP-enabled clients. Announced July 22, 2026.", "category": "data", "endpoint": "RocketReach MCP", "homepage_url": "https://rocketreach.co", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "sales-intelligence", "lead-generation", "contacts", "prospecting", "recruiting", "email-verification", "company-data", "oauth" ], "use_cases": [ "Ask an AI assistant to find 20 VPs of Sales at Series B fintech companies in New York and get verified contact results with email and phone directly inside ChatGPT or Claude without leaving the conversation", "Enable recruiting teams to search RocketReach's 700 million contact database by role, company, location and skills through natural language queries in any MCP-compatible AI assistant", "Build automated prospecting workflows where AI agents filter companies by industry, size and funding stage, retrieve verified decision-maker contacts and save results to your RocketReach account" ], "health": "active" }, { "id": "redgate-flyway-mcp", "name": "Redgate Flyway Enterprise MCP Server", "description": "MCP server from Redgate Software for governed, agentic database change management using Flyway Enterprise. Gives AI agents the ability to manage database schema changes with full capture, validation and audit trails. Every AI-driven change is recorded and auditable, addressing governance requirements for teams scaling agentic workflows. Includes advanced Databricks capabilities with Snowflake, operational dashboards and security dashboard views on the roadmap. Part of the broader Redgate AI capabilities platform. Built on Redgate's 25 years of database tooling expertise. Announced July 22, 2026.", "category": "infrastructure", "endpoint": "Redgate Flyway Enterprise MCP", "homepage_url": "https://www.red-gate.com/products/flyway/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "database", "schema-migration", "change-management", "devops", "governance", "audit", "databricks", "enterprise" ], "use_cases": [ "Enable AI coding agents to manage database schema migrations through Flyway Enterprise with full governance, ensuring every AI-driven change is captured, validated and auditable before reaching production", "Give development teams a governed path for agentic database change by connecting Claude Code or Cursor to the Flyway MCP server so schema updates follow the same controlled workflow as manual changes", "Automate database change control across Databricks and SQL Server environments by letting AI agents plan, validate and apply migrations through the Redgate Flyway MCP with enterprise-grade audit trails" ], "health": "active" }, { "id": "dnb-risk-analytics-mcp", "name": "Dun & Bradstreet Risk Analytics MCP Server", "description": "MCP server from Dun & Bradstreet connecting AI agents to the D&B Commercial Graph for verified business information and risk intelligence. Transforms commercial insurance underwriting workflows that typically take weeks into minutes by enabling AI assistants to verify insured identity and ownership structures, confirm broker credentials and licensure, screen against regulatory requirements, conduct financial risk checks, flag duplicate submissions and assemble decision-ready risk profiles. Supports KYB, entity resolution, screening, ownership insights and onboarding. Available on the Claude Connector Marketplace. Announced July 8, 2026.", "category": "data", "endpoint": "D&B Risk Analytics MCP", "homepage_url": "https://www.dnb.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "risk-analytics", "insurance", "underwriting", "kyb", "compliance", "commercial-data", "entity-resolution", "financial-risk" ], "use_cases": [ "Clear commercial insurance submissions in seconds by having Claude verify the insured's identity, ownership structure, broker licensure, OFAC screening and financial risk profile using D&B's Commercial Graph through MCP", "Enable insurance underwriting teams to compress weeks of manual data retrieval into minutes by connecting AI agents to D&B's verified business information, predictive scores and risk intelligence via the MCP server", "Build automated KYB and compliance workflows where AI agents resolve entities, screen against regulatory watchlists and generate audit-ready documentation using D&B's trusted commercial data directly in Claude" ], "health": "active" }, { "id": "foreflight-mcp", "name": "ForeFlight AI Connector MCP Server", "description": "MCP server from Jeppesen ForeFlight, the Boeing subsidiary and leading electronic flight bag platform for pilots and flight departments. Connects AI assistants to ForeFlight's aviation data and flight planning capabilities through the Model Context Protocol. Part of ForeFlight's agentic AI strategy for the aviation industry, previewing first in the General Aviation market. Enables pilots, dispatchers and flight operations teams to access aviation data, flight planning tools and operational intelligence through natural language. Announced July 1, 2026.", "category": "data", "endpoint": "ForeFlight AI Connector", "homepage_url": "https://www.foreflight.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "aviation", "flight-planning", "pilots", "boeing", "electronic-flight-bag", "general-aviation", "flight-operations" ], "use_cases": [ "Access ForeFlight's aviation data and flight planning tools through natural language queries in Claude or ChatGPT to streamline pre-flight preparation and route planning for general aviation pilots", "Enable flight operations teams to query weather, NOTAMs, airport information and route data from ForeFlight's platform through AI assistants for faster operational decision-making", "Connect AI agents to ForeFlight's electronic flight bag capabilities so dispatchers and flight departments can automate routine aviation data lookups and planning tasks through the MCP server" ], "health": "active" }, { "id": "lilt-mcp", "name": "LILT MCP Server", "description": "MCP server from LILT, the enterprise AI translation platform, providing human-verified translation capabilities to AI assistants through the Model Context Protocol. Includes agent-to-agent integration enabling autonomous translation workflows. AI assistants can submit content for translation, check translation status, retrieve completed translations and manage translation memory. All translations go through LILT's human-in-the-loop verification process ensuring enterprise-grade quality. Supports over 50 language pairs with domain-specific translation models.", "category": "productivity", "endpoint": "LILT MCP Server", "homepage_url": "https://lilt.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "translation", "localization", "i18n", "language", "enterprise", "human-verified", "agent-to-agent" ], "use_cases": [ "Submit content for human-verified translation directly from Claude or ChatGPT by connecting to the LILT MCP server, getting enterprise-grade translations without leaving the AI assistant workflow", "Enable AI agents to autonomously manage multilingual content pipelines by using LILT's agent-to-agent integration to submit, track and retrieve translations across 50-plus language pairs", "Build localization workflows where AI coding assistants translate UI strings, documentation and marketing copy through LILT's MCP server with human-in-the-loop quality verification" ], "health": "active" }, { "id": "nvidia-agent-toolkit-mcp", "name": "NVIDIA Agent Toolkit MCP Server", "description": "MCP server and client from the NVIDIA Agent Toolkit enabling AI agents to interact with NVIDIA's creative and simulation ecosystem through the Model Context Protocol. Includes an MCP client for connecting to remote MCP servers and an MCP server for publishing tools to any MCP-compatible client. Part of NVIDIA's broader push to make creative tools agent-ready, announced at SIGGRAPH July 20, 2026 alongside MCP integrations from Adobe, Blender, SideFX and Boris FX. Designed for developers building agentic workflows that require GPU-accelerated compute, rendering or simulation capabilities.", "category": "ai", "endpoint": "NVIDIA Agent Toolkit MCP", "homepage_url": "https://developer.nvidia.com/agent-toolkit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-23", "updated": "2026-07-23", "tags": [ "nvidia", "gpu", "creative-tools", "simulation", "rendering", "siggraph", "agent-toolkit", "developer-tools" ], "use_cases": [ "Publish NVIDIA GPU-accelerated tools to any MCP-compatible AI client so agents can access rendering, simulation and compute capabilities through natural language", "Connect AI agents to remote MCP servers through the NVIDIA Agent Toolkit's built-in MCP client for multi-tool agentic workflows spanning creative and engineering domains", "Build agentic creative workflows by combining the NVIDIA Agent Toolkit MCP server with MCP integrations from Adobe, Blender and other creative tools announced at SIGGRAPH 2026" ], "health": "active" }, { "id": "lumonic-mcp", "name": "Lumonic MCP Server", "description": "MCP server from Lumonic, a Morningstar company, providing audit-ready portfolio data to AI assistants for private credit, private equity and venture capital workflows. Connects Claude, ChatGPT and any MCP-enabled assistant to a firm's Lumonic workspace with read-only access to periodic financials, covenant status, reporting status and tracked KPIs. Every AI-returned figure links back to its exact source cell for full auditability. Includes an MCP Library with tested prompts and downloadable artifacts for PE, VC and private credit workflows. Announced July 23, 2026.", "category": "data", "endpoint": "Lumonic MCP Server", "homepage_url": "https://www.lumonic.com/mcp/library", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-24", "updated": "2026-07-24", "tags": [ "private-credit", "private-equity", "venture-capital", "portfolio-data", "financial-analytics", "morningstar", "audit-trail", "enterprise" ], "use_cases": [ "Query covenant status, periodic financials and reporting gaps across a private credit portfolio through Claude or ChatGPT connected to Lumonic via MCP with every figure traced back to its source cell", "Enable private equity and venture capital teams to ask natural language questions about portfolio company KPIs, financial submissions and compliance status through AI assistants connected to their Lumonic workspace", "Build audit-ready portfolio review workflows where AI agents pull live fund data from Lumonic and generate standardized reports with full data provenance for LP reporting and compliance" ], "health": "active" }, { "id": "turnstile-qtc-mcp", "name": "Turnstile Quote-to-Cash MCP Server", "description": "Read-and-write MCP server from Turnstile extending its flexible Quote-to-Cash platform to AI agents. One of the only QTC MCPs that allows AI agents to control the entire quote-to-cash process rather than just access data. Agents can reason over and take action on pricing, contracts, billing and customer data using the same trusted commercial information that people rely on. Enables hybrid human-agent teams to manage the full QTC lifecycle from quoting through billing. Announced July 23, 2026.", "category": "productivity", "endpoint": "Turnstile QTC MCP", "homepage_url": "https://turnstile.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-24", "updated": "2026-07-24", "tags": [ "quote-to-cash", "billing", "pricing", "contracts", "revenue-operations", "cpq", "enterprise", "read-write" ], "use_cases": [ "Enable AI agents to generate quotes, manage contracts and process billing changes through the Turnstile MCP server with read-and-write access to the full quote-to-cash lifecycle", "Build hybrid human-agent revenue operations workflows where AI agents handle routine pricing lookups, contract renewals and billing adjustments while escalating exceptions to human team members", "Automate quote-to-cash analysis by having AI assistants query pricing models, contract terms and billing data from Turnstile through MCP to identify revenue leakage and optimization opportunities" ], "health": "active" }, { "id": "skyfi-mcp", "name": "SkyFi MCP Server", "description": "MCP server from SkyFi, the AI-first Earth Intelligence Platform, making satellite imagery and geospatial analytics directly accessible through AI assistants. Connects Claude, ChatGPT and other MCP-compatible platforms to SkyFi's satellite imagery marketplace and analytical capabilities. Enables users to search, preview and order satellite imagery, run geospatial queries and access Earth observation data through natural language. Announced July 22, 2026.", "category": "data", "endpoint": "SkyFi MCP", "homepage_url": "https://skyfi.com/en/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-24", "updated": "2026-07-24", "tags": [ "satellite-imagery", "geospatial", "earth-observation", "remote-sensing", "gis", "mapping", "intelligence" ], "use_cases": [ "Search and preview satellite imagery for any location on Earth through Claude or ChatGPT connected to SkyFi via MCP for rapid site assessment, change detection and environmental monitoring", "Enable intelligence analysts and researchers to query geospatial data and order high-resolution satellite imagery through natural language in AI assistants connected to SkyFi's marketplace via MCP", "Build automated geospatial monitoring workflows where AI agents track changes at specific coordinates using SkyFi satellite imagery and surface alerts when significant changes are detected" ], "health": "active" }, { "id": "jams-mcp", "name": "JAMS MCP Server", "description": "MCP server from JAMS, the enterprise job scheduling platform, connecting AI coding assistants to JAMS workload automation capabilities. Built on the open Model Context Protocol standard, it brings JAMS into the AI tools engineering teams already use including Cursor, VS Code with Copilot, Claude Code, Claude Desktop and Codex. Enables developers to manage, monitor and troubleshoot scheduled jobs and automation workflows through natural language. Complements the JAX AI assistant for enterprise job scheduling. Announced July 24, 2026.", "category": "infrastructure", "endpoint": "JAMS MCP Server", "homepage_url": "https://www.jams.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-24", "updated": "2026-07-24", "tags": [ "job-scheduling", "workload-automation", "devops", "enterprise", "batch-processing", "cron", "orchestration" ], "use_cases": [ "Monitor and troubleshoot enterprise job schedules through Claude Code or Cursor by querying JAMS job status, execution history and failure logs via the MCP server without switching to the JAMS console", "Enable DevOps teams to manage scheduled batch jobs, modify job dependencies and review automation workflows through natural language commands in AI coding assistants connected to JAMS via MCP", "Build proactive job monitoring workflows where AI agents connected to JAMS detect failed or delayed jobs and suggest remediation steps based on execution history and dependency analysis" ], "health": "active" }, { "id": "ians-cybersecurity-mcp", "name": "IANS Cybersecurity MCP Server", "description": "MCP server from IANS Research delivering practitioner-validated cybersecurity intelligence directly into AI tools used by security teams. Described as the first cybersecurity MCP server, it provides access to IANS research content including security frameworks, best practices, vendor evaluations and practitioner insights. Enables CISOs and security professionals to query expert cybersecurity guidance through Claude, ChatGPT and other MCP-compatible clients without leaving their AI workflow. Announced July 15, 2026.", "category": "data", "endpoint": "IANS MCP Server", "homepage_url": "https://www.iansresearch.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-24", "updated": "2026-07-24", "tags": [ "cybersecurity", "security-research", "ciso", "threat-intelligence", "compliance", "risk-management", "enterprise" ], "use_cases": [ "Query IANS practitioner-validated cybersecurity research from Claude or ChatGPT to get expert guidance on security frameworks, vendor evaluations and best practices without leaving the AI assistant workflow", "Enable CISOs and security leaders to ground AI-generated security recommendations in validated IANS research data by connecting their AI tools to the IANS MCP server", "Build security program planning workflows where AI agents pull relevant IANS benchmarks, peer comparisons and framework guidance to support budget justification and board reporting" ], "health": "active" }, { "id": "nowsecure-mcp", "name": "NowSecure MCP Server", "description": "MCP server from NowSecure, the mobile application risk management platform, exposing deep mobile app security telemetry to AI assistants and agentic DevSecOps workflows. Gives security teams programmatic access to binary analysis findings, runtime artifacts, vulnerability data, remediation guidance, regulatory compliance mappings and the underlying evidence supporting each risk decision. Enables AI agents to query the NowSecure mobile risk knowledge graph through Claude, ChatGPT or any MCP-compatible client. Part of a broader AI-native update that also includes AI Chat and AI-specific vulnerability detection for mobile apps embedding LLMs. Announced July 23, 2026.", "category": "infrastructure", "endpoint": "NowSecure MCP Server", "homepage_url": "https://www.nowsecure.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "mobile-security", "appsec", "vulnerability-management", "devsecops", "compliance", "binary-analysis", "enterprise" ], "use_cases": [ "Integrate mobile app security findings, binary analysis artifacts and runtime vulnerability data into AI-driven DevSecOps workflows by connecting Claude or ChatGPT to the NowSecure MCP server for automated triage and remediation guidance", "Enable security teams to query the NowSecure mobile risk knowledge graph through natural language in AI assistants to assess portfolio-wide mobile app security posture, compliance status and AI-specific vulnerability exposure", "Build autonomous mobile app testing pipelines where AI agents trigger NowSecure scans, retrieve findings with full evidence provenance and generate remediation pull requests without manual intervention" ], "health": "active" }, { "id": "dogpile-fetch-mcp", "name": "Dogpile Fetch MCP Server", "description": "MCP server and web search API from Dogpile, the metasearch engine operated by System1 (NYSE: SST) that has been aggregating results across multiple search indexes since 1996. Designed specifically for AI agents that need broader web coverage than any single search index provides. Every query is classified and routed to the best backend automatically, returning ranked results, knowledge graph data and People Also Ask questions. Includes a Deep mode that breaks complex queries into multiple searches and deduplicates results. Installs in Claude Code, Cursor or any MCP-compatible client in under two minutes. Pricing starts at $2 per 1,000 calls with a free monthly credit and no credit card required. Announced July 23, 2026.", "category": "web", "endpoint": "https://developer.dogpile.com", "homepage_url": "https://developer.dogpile.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "search", "metasearch", "web-search", "research", "knowledge-graph", "ai-agents", "system1" ], "use_cases": [ "Give AI agents broader web coverage by routing search queries through Dogpile Fetch which aggregates results across multiple search indexes to surface pages that any single index would miss", "Use Dogpile Fetch Deep mode from Claude Code or Cursor to automatically decompose complex research queries into multiple sub-searches and return deduplicated ranked results with knowledge graph data", "Build research and fact-checking workflows where AI agents query Dogpile Fetch via MCP to cross-reference information across multiple search backends before generating answers grounded in diverse sources" ], "health": "active" }, { "id": "wisesheets-mcp", "name": "Wisesheets MCP Server", "description": "MCP server from Wisesheets, the financial data platform with over 70,000 users, providing SEC-sourced company fundamentals directly to AI assistants. Serves income statements, balance sheets, cash flow statements, financial ratios, historical stock prices and company profiles parsed from XBRL filings on SEC EDGAR. Every returned figure includes full provenance with the originating XBRL tag, SEC accession number and filing date so any number can be traced to its source disclosure. Available at mcp.wisesheets.io. Free tier includes 5,000 requests per month with paid plans from $19 per month. Announced July 24, 2026.", "category": "data", "endpoint": "https://mcp.wisesheets.io", "homepage_url": "https://wisesheets.io/api", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "financial-data", "sec-edgar", "fundamentals", "stock-data", "xbrl", "valuation", "fintech" ], "use_cases": [ "Pull income statements, balance sheets and financial ratios from SEC EDGAR filings through Claude or ChatGPT connected to the Wisesheets MCP server with every figure linked to its exact source filing for audit-ready financial research", "Build AI-powered stock screeners and DCF valuation models where agents query Wisesheets via MCP for comparable company fundamentals with full XBRL provenance instead of relying on scraped or third-party aggregated data", "Enable investment analysts to ask natural language questions about company financials in AI assistants that return structured data with SEC accession numbers so every cited figure can be verified against the original disclosure" ], "health": "active" }, { "id": "lumar-mcp", "name": "Lumar MCP Server", "description": "MCP server from Lumar, the enterprise website intelligence platform used by SEO and technical marketing teams for large-scale crawl analysis. Connects AI assistants directly to Lumar crawl data including site architecture issues, indexability problems, page speed metrics, internal linking analysis and technical SEO findings. Available as a connector in Claude and ChatGPT. Enables teams to query crawl results, surface technical issues and generate fix recommendations through natural language without switching to the Lumar dashboard. Launched June 2026.", "category": "data", "endpoint": "Lumar MCP Server", "homepage_url": "https://www.lumar.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "seo", "website-intelligence", "crawl-data", "technical-seo", "site-architecture", "enterprise", "marketing" ], "use_cases": [ "Query Lumar crawl data from Claude or ChatGPT to identify technical SEO issues including broken links, indexability problems and site architecture gaps across large websites without navigating the Lumar dashboard", "Enable SEO teams to ask natural language questions about crawl results and get AI-generated fix recommendations prioritized by impact through AI assistants connected to the Lumar MCP server", "Build automated site audit workflows where AI agents pull Lumar crawl metrics, compare them against previous crawls and surface regressions that need attention before the next release" ], "health": "active" }, { "id": "arraylake-mcp", "name": "Arraylake MCP Server", "description": "MCP server from Earthmover, the geospatial data infrastructure company, providing access to Arraylake cloud-native array storage for weather, climate and scientific datasets. Enables AI assistants to query multidimensional geospatial data including weather forecasts, climate model outputs and Earth observation datasets through natural language. Built on Icechunk tensor storage. Available at app.earthmover.io/mcp and works with any MCP-compatible client. First public release with active development.", "category": "data", "endpoint": "https://app.earthmover.io/mcp", "homepage_url": "https://www.earthmover.io", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "geospatial", "weather", "climate", "scientific-data", "earth-observation", "tensor-storage", "zarr" ], "use_cases": [ "Query weather forecasts and climate model outputs through Claude or ChatGPT connected to the Arraylake MCP server to get point forecasts with temperature, precipitation and wind data for any location without writing analysis code", "Enable researchers and data scientists to explore multidimensional Earth observation datasets stored in Arraylake through natural language queries in AI assistants for rapid scientific analysis and hypothesis testing", "Build environmental monitoring workflows where AI agents pull geospatial data from Arraylake via MCP, compare current conditions against historical baselines and surface anomalies for climate and agricultural applications" ], "health": "active" }, { "id": "seedlegals-mcp", "name": "SeedLegals MCP Server", "description": "MCP server from SeedLegals, the legal platform for startups covering funding rounds, share schemes, employment contracts and corporate governance. Connects AI assistants to SeedLegals platform data and capabilities through the Claude Connector directory and ChatGPT app directory. Enables founders, lawyers and advisors to query legal documents, funding round status and cap table information through natural language in their AI tools.", "category": "productivity", "endpoint": "SeedLegals MCP Server", "homepage_url": "https://seedlegals.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "legal", "startups", "funding-rounds", "cap-table", "employment-contracts", "corporate-governance", "legaltech" ], "use_cases": [ "Query funding round status, cap table details and shareholder information through Claude or ChatGPT connected to SeedLegals via MCP for quick due diligence and investor reporting without switching to the SeedLegals dashboard", "Enable startup founders to ask natural language questions about their employment contracts, share schemes and corporate governance documents through AI assistants connected to the SeedLegals MCP server", "Build legal workflow automations where AI agents pull SeedLegals data to draft board minutes, prepare funding round summaries and flag outstanding corporate governance tasks" ], "health": "active" }, { "id": "stellar-raven-mcp", "name": "Stellar Raven MCP Server", "description": "MCP server built by the Stellar developer community that aggregates Stellar blockchain documentation, developer tools and community intelligence into a single context source for AI assistants. Gives AI coding agents accurate Stellar-specific context for building on the Stellar network. Introduced at the July 16, 2026 Stellar Developers Meeting. Covers Stellar documentation, SDK references, smart contract patterns and ecosystem tooling.", "category": "data", "endpoint": "Stellar Raven MCP", "homepage_url": "https://stellar.org", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "stellar", "blockchain", "cryptocurrency", "developer-tools", "documentation", "smart-contracts", "web3" ], "use_cases": [ "Give AI coding assistants accurate Stellar blockchain context by connecting to the Stellar Raven MCP server for SDK references, smart contract patterns and network-specific documentation while building Stellar applications", "Enable developers to query Stellar ecosystem documentation and community resources through Claude Code or Cursor via MCP instead of manually searching fragmented docs across multiple Stellar developer sites", "Build Stellar dApp prototyping workflows where AI agents pull current Stellar SDK methods, Soroban smart contract templates and network parameters from Raven to generate correct code on the first pass" ], "health": "active" }, { "id": "joinable-propagator-mcp", "name": "Joinable Propagator MCP Server", "description": "MCP server from Joinable Labs exposing the Joinable Propagator knowledge foundry platform to AI agents in the enterprise. Propagator indexes and structures organizational knowledge from internal sources and makes it available through a native MCP server so AI assistants can retrieve verified internal context for decision-making, research and workflow automation. Designed for agentic enterprise use cases where AI agents need governed access to proprietary knowledge bases. Announced July 2026.", "category": "productivity", "endpoint": "Joinable Propagator MCP", "homepage_url": "https://joinable.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-25", "updated": "2026-07-25", "tags": [ "knowledge-management", "enterprise", "internal-knowledge", "agentic", "organizational-intelligence", "rag" ], "use_cases": [ "Connect AI assistants to verified internal organizational knowledge through the Joinable Propagator MCP server so agents can ground responses in proprietary data rather than relying solely on public training data", "Enable enterprise teams to query structured internal knowledge bases through Claude or ChatGPT via MCP for research, onboarding and cross-functional decision-making with governed access controls", "Build agentic workflows where AI agents retrieve relevant internal context from Joinable Propagator before drafting documents, preparing presentations or making recommendations grounded in organizational knowledge" ], "health": "active" }, { "id": "billtrust-mcp", "name": "Billtrust MCP Server", "description": "MCP server from Billtrust, the B2B cash generation platform, connecting live invoice-to-cash intelligence to AI assistants. First accounts receivable platform to offer direct MCP integration. Enables finance teams to query open invoices, payment status, cash application data, customer payment behavior and collections insights through Claude, ChatGPT or Microsoft Copilot. Designed for AR teams managing high-volume B2B billing and collections workflows. Announced July 21, 2026.", "category": "data", "endpoint": "https://www.billtrust.com/ai/mcp-server", "homepage_url": "https://www.billtrust.com/ai/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "accounts-receivable", "b2b", "fintech", "invoicing", "cash-application", "collections", "enterprise" ], "use_cases": [ "Query open invoice balances, aging reports and payment status across your B2B customer base through Claude or ChatGPT connected to the Billtrust MCP server without logging into the AR dashboard", "Enable finance teams to ask natural language questions about cash application rates, payment trends and collection priorities through AI assistants with live Billtrust data", "Build automated AR workflows where AI agents monitor invoice aging, flag overdue accounts and generate collection prioritization reports from Billtrust data via MCP" ], "health": "active" }, { "id": "gatekeeper-mcp", "name": "Gatekeeper MCP Server", "description": "MCP server from Gatekeeper, the natively unified contract and vendor management platform, providing live contract data access to AI assistants. Part of Gatekeeper's July 2026 platform refresh alongside Gatekeeper Chat. Enables procurement, legal and operations teams to query contract terms, vendor details, renewal dates and compliance status through conversational AI interfaces. Announced July 20, 2026.", "category": "productivity", "endpoint": "Gatekeeper MCP Server", "homepage_url": "https://www.gatekeeperhq.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "contract-management", "vendor-management", "procurement", "legal", "compliance", "enterprise", "clm" ], "use_cases": [ "Query contract terms, renewal dates and obligation status across your vendor portfolio through Claude or ChatGPT connected to Gatekeeper via MCP without navigating the contract management dashboard", "Enable procurement and legal teams to ask natural language questions about vendor agreements, spending commitments and compliance requirements through AI assistants with live Gatekeeper data", "Build automated contract review workflows where AI agents surface upcoming renewals, flag non-compliant terms and generate vendor risk summaries from Gatekeeper data via MCP" ], "health": "active" }, { "id": "onshape-featurescript-mcp", "name": "Onshape FeatureScript MCP Server", "description": "MCP server from PTC as part of Onshape Labs, offering a Text-to-Code-to-CAD framework that enables prompt-based CAD geometry creation and customization through FeatureScript. Part of PTC's broader push to accelerate AI inside the product development process. Enables engineers and designers to generate and modify CAD features through natural language prompts in AI assistants. Available through the Onshape Labs early access program with broader availability expected later in 2026. Announced July 17, 2026.", "category": "code", "endpoint": "Onshape FeatureScript MCP", "homepage_url": "https://www.onshape.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "cad", "product-design", "featurescript", "3d-modeling", "engineering", "ptc", "manufacturing" ], "use_cases": [ "Generate CAD geometry and custom features from natural language prompts through AI assistants connected to the Onshape FeatureScript MCP server for rapid prototyping without manual modeling", "Enable mechanical engineers to describe part modifications in plain English and have AI agents translate them into FeatureScript code that executes directly in Onshape CAD models", "Build AI-assisted product design workflows where agents create parametric CAD features, iterate on geometry and customize Onshape models through text-to-code-to-CAD via MCP" ], "health": "active" }, { "id": "socure-riskos-mcp", "name": "Socure RiskOS MCP Server", "description": "MCP server from Socure, the identity verification and fraud prevention platform, exposing the RiskOS identity risk engine to AI assistants and agentic workflows. Provides programmatic access to identity verification scores, fraud signals, KYC compliance data and risk assessments. Supports token-based authentication with MCP Server Keys replacing username-password auth as of July 21, 2026. Designed for compliance, fraud and operations teams at banks, fintechs and marketplaces.", "category": "infrastructure", "endpoint": "Socure RiskOS MCP", "homepage_url": "https://www.socure.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "identity-verification", "fraud-prevention", "kyc", "compliance", "risk-assessment", "fintech", "enterprise" ], "use_cases": [ "Run identity verification checks and retrieve fraud risk scores through Claude or ChatGPT connected to the Socure RiskOS MCP server for real-time compliance assessments without switching to the Socure dashboard", "Enable compliance teams to query KYC verification status, identity match confidence and risk signals across customer portfolios through AI assistants via MCP with governed access", "Build automated onboarding workflows where AI agents trigger Socure identity verification, evaluate risk scores and route applications based on fraud signals through the RiskOS MCP server" ], "health": "active" }, { "id": "warden-mcp", "name": "Warden MCP Server", "description": "Open-source MCP server for Vaultwarden and Bitwarden password vaults, built by icoretech. Enables AI assistants and coding agents to securely retrieve credentials, passwords and secure notes from self-hosted Vaultwarden instances or Bitwarden-compatible vaults. Supports both stdio transport for local MCP clients and HTTP SSE for shared service deployments. Installs via npx with environment variables for vault connection. Available on npm as @icoretech/warden-mcp.", "category": "infrastructure", "endpoint": "npx @icoretech/warden-mcp@latest", "homepage_url": "https://github.com/icoretech/warden-mcp", "github_url": "https://github.com/icoretech/warden-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @icoretech/warden-mcp@latest --stdio", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "password-manager", "vaultwarden", "bitwarden", "credentials", "security", "secrets", "self-hosted" ], "use_cases": [ "Retrieve credentials and secure notes from a self-hosted Vaultwarden or Bitwarden vault through Claude Code, Cursor or Codex agents via MCP for secure authentication during development workflows", "Run the Warden MCP server as a shared HTTP service so multiple AI assistants and coding agents can access vault credentials through SSE transport with header-based authentication", "Enable AI coding agents to look up API keys, database passwords and service credentials stored in Bitwarden-compatible vaults through MCP without hardcoding secrets in configuration files" ], "health": "active" }, { "id": "qgis-mcp", "name": "QGIS MCP Server", "description": "Open-source MCP server that bridges AI coding agents with QGIS, the leading open-source geographic information system. Built by nkarasiak, it enables AI assistants to control QGIS remotely for geospatial analysis, map rendering, layer management and spatial data processing. Supports Claude Code, Cursor, Codex and other MCP-compatible clients. Installs via uvx from the GitHub repository. Includes token-based authentication for secure access.", "category": "data", "endpoint": "uvx qgis-mcp-server", "homepage_url": "https://github.com/nkarasiak/qgis-mcp", "github_url": "https://github.com/nkarasiak/qgis-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx --from https://github.com/nkarasiak/qgis-mcp/archive/refs/heads/main.zip qgis-mcp-server", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "gis", "geospatial", "mapping", "qgis", "spatial-analysis", "cartography", "open-source" ], "use_cases": [ "Control QGIS remotely from Claude Code or Cursor to perform geospatial analysis, manage map layers and process spatial datasets through natural language commands via MCP", "Enable GIS analysts to automate repetitive QGIS operations like layer styling, attribute queries and spatial joins by describing tasks in plain English through AI coding agents", "Build automated mapping workflows where AI agents load geospatial data into QGIS, run spatial analyses and export styled maps without manual interaction with the QGIS interface" ], "health": "active" }, { "id": "nymbus-mcp", "name": "Nymbus MCP Server", "description": "MCP server from Nymbus, the next-generation core banking platform, purpose-built for financial institutions. One of the first MCP servers designed specifically for core banking operations. Exposes 19 tools covering customer lookup, account management, money movement and debit card controls through a single conversational interface. Includes token-based authentication, role-based access controls, PII masking in logs and full audit logging for regulated financial environments. Launched April 2026.", "category": "data", "endpoint": "Nymbus MCP Server", "homepage_url": "https://www.nymbus.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "banking", "core-banking", "fintech", "account-management", "money-movement", "compliance", "enterprise" ], "use_cases": [ "Perform customer lookups, account inquiries and balance checks through Claude or ChatGPT connected to the Nymbus MCP server with role-based access controls and PII masking for bank branch operations", "Enable bank operations teams to manage debit card controls, process money movements and update account details through AI assistants with full audit logging via the Nymbus MCP server", "Build AI-assisted banking workflows where agents handle routine account servicing tasks through natural language with governed access to core banking functions and compliance-ready audit trails" ], "health": "active" }, { "id": "zavora-computer-use-mcp", "name": "Zavora Computer Use MCP Server", "description": "High-performance MCP server from Zavora AI for computer use automation, enabling AI agents to interact with desktop applications, browsers and operating system interfaces. Provides tools for screen capture, mouse control, keyboard input and application interaction through the Model Context Protocol. Designed for AI agents that need to perform tasks across desktop software that lacks API access. Open source on GitHub.", "category": "infrastructure", "endpoint": "Zavora Computer Use MCP", "homepage_url": "https://github.com/zavora-ai/computer-use-mcp", "github_url": "https://github.com/zavora-ai/computer-use-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-26", "updated": "2026-07-26", "tags": [ "computer-use", "desktop-automation", "screen-control", "rpa", "browser-automation", "ai-agents", "open-source" ], "use_cases": [ "Enable AI agents to interact with desktop applications that lack APIs by using the Zavora Computer Use MCP server for screen capture, mouse clicks and keyboard input through any MCP-compatible client", "Automate repetitive desktop workflows across legacy software by connecting Claude Code or other AI agents to the Computer Use MCP server for visual interaction with application interfaces", "Build end-to-end automation pipelines where AI agents navigate desktop applications, fill forms, extract on-screen data and complete multi-step workflows through computer use via MCP" ], "health": "active" }, { "id": "hackerone-mcp", "name": "HackerOne MCP Server", "description": "Official MCP server from HackerOne, the bug bounty and vulnerability coordination platform, now generally available as of July 2026. Platform-hosted server that enables security teams and engineers to access HackerOne reports, programs, assets, bounties and remediation plans through Claude and other AI assistants. Supports direct authentication with HackerOne accounts. Available on Enterprise, Professional, Legacy and CTEM packaging tiers. Announced July 2026.", "category": "infrastructure", "endpoint": "https://docs.hackerone.com/en/articles/16069077-hackerone-mcp-server-setup-tool-reference", "homepage_url": "https://www.hackerone.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "security", "bug-bounty", "vulnerability", "penetration-testing", "remediation", "compliance", "enterprise" ], "use_cases": [ "Query and summarize HackerOne vulnerability reports, bounty status and remediation plans through Claude or other AI assistants without navigating the HackerOne dashboard", "Enable security teams to ask natural language questions about open reports, asset coverage and program metrics through AI assistants connected to the HackerOne MCP server", "Build automated security workflows where AI agents monitor incoming vulnerability reports, prioritize remediation and generate status summaries from live HackerOne data via MCP" ], "health": "active" }, { "id": "paper-search-mcp", "name": "Paper Search MCP Server", "description": "Open-source MCP server for searching and downloading academic papers from over 20 sources including arXiv, PubMed, bioRxiv, Semantic Scholar, Google Scholar, Crossref, OpenAlex, CORE, Zenodo and more. Follows a free-first strategy prioritizing open and public data sources. Features unified multi-source concurrent search with deduplication, intelligent DOI extraction, open-access-first download fallback chains and standardized paper output format. Available as MCP server, Claude Code skill and CLI. 2.3K GitHub stars. MIT license.", "category": "data", "endpoint": "npx -y @smithery/cli run @openags/paper-search-mcp", "homepage_url": "https://github.com/openags/paper-search-mcp", "github_url": "https://github.com/openags/paper-search-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx paper-search-mcp", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "academic", "research", "papers", "arxiv", "pubmed", "semantic-scholar", "science", "open-access" ], "use_cases": [ "Search for academic papers across arXiv, PubMed, Semantic Scholar, Crossref and 20 other sources simultaneously through Claude or other AI assistants with automatic deduplication and DOI extraction", "Download and read full-text academic PDFs through AI assistants using open-access-first fallback chains that prioritize free public sources before restricted ones", "Build AI-powered literature review workflows where agents search multiple academic databases, download relevant papers and extract key findings for systematic reviews via MCP" ], "health": "active" }, { "id": "zenml-mcp", "name": "ZenML MCP Server", "description": "Official MCP server from ZenML, the open-source MLOps framework for building portable and production-ready ML pipelines. Connects AI assistants to the ZenML API for managing ML pipelines, stack components, artifacts and model deployments. Enables MLOps teams to query pipeline runs, inspect artifacts, manage infrastructure stacks and monitor model performance through conversational AI interfaces. Open source under Apache 2.0 license.", "category": "ai", "endpoint": "https://github.com/zenml-io/mcp-zenml", "homepage_url": "https://www.zenml.io", "github_url": "https://github.com/zenml-io/mcp-zenml", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx mcp-zenml", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "mlops", "machine-learning", "pipelines", "model-management", "ml-infrastructure", "open-source" ], "use_cases": [ "Query ML pipeline run status, inspect artifacts and monitor model performance through Claude or other AI assistants connected to the ZenML MCP server without switching to the ZenML dashboard", "Enable ML engineers to manage infrastructure stacks, trigger pipeline runs and debug failed steps through natural language commands via AI assistants with live ZenML data", "Build automated MLOps workflows where AI agents monitor pipeline health, compare model versions and generate deployment recommendations from ZenML data via MCP" ], "health": "active" }, { "id": "pubmed-mcp", "name": "PubMed MCP Server", "description": "MCP server providing comprehensive access to PubMed and NCBI biomedical literature databases. Supports searching articles, retrieving full metadata, accessing abstracts and related citations. Available as a public hosted instance at pubmed.caseyjhand.com, self-hosted via npx or Docker. Features intelligent query construction, MeSH term support, batch operations and citation network traversal. Designed for medical researchers, clinicians and biomedical AI workflows. 126 GitHub stars.", "category": "data", "endpoint": "https://pubmed.caseyjhand.com/mcp", "homepage_url": "https://github.com/cyanheads/pubmed-mcp-server", "github_url": "https://github.com/cyanheads/pubmed-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "npx -y @cyanheads/pubmed-mcp-server@latest", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "pubmed", "biomedical", "medical-research", "ncbi", "literature", "healthcare", "clinical" ], "use_cases": [ "Search PubMed for biomedical literature using natural language queries through Claude or other AI assistants connected to the PubMed MCP server with MeSH term support and intelligent query construction", "Enable medical researchers and clinicians to retrieve article metadata, abstracts and citation networks through conversational AI interfaces with live PubMed data", "Build AI-powered biomedical research workflows where agents search PubMed, traverse citation graphs and synthesize findings from medical literature via MCP" ], "health": "active" }, { "id": "request-tracker-mcp", "name": "Request Tracker MCP Server", "description": "MCP server from Best Practical Solutions that connects AI assistants to a live RT (Request Tracker) instance. Enables searching tickets, viewing ticket history, creating and updating tickets through natural language conversations. Integrates with RT REST 2.0 API for full ticket lifecycle management. Designed for IT support teams, help desks and operations teams using Request Tracker for issue tracking. Open source.", "category": "productivity", "endpoint": "npx mcp-server-rt", "homepage_url": "https://bestpractical.com", "github_url": "https://github.com/bestpractical/mcp-server-rt", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g mcp-server-rt", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "ticketing", "it-support", "help-desk", "issue-tracking", "request-tracker", "operations" ], "use_cases": [ "Search and retrieve IT support tickets from Request Tracker through Claude or other AI assistants without logging into the RT web interface", "Enable help desk teams to create, update and resolve tickets through natural language commands via AI assistants connected to their RT instance via MCP", "Build automated IT operations workflows where AI agents monitor ticket queues, prioritize issues and generate status reports from Request Tracker data via MCP" ], "health": "active" }, { "id": "strata-klavis-mcp", "name": "Strata MCP Server", "description": "Unified MCP server from Klavis AI that enables AI agents to handle thousands of tools reliably at any scale. Acts as a single MCP gateway that aggregates and orchestrates multiple tool integrations, eliminating the need to configure separate MCP servers for each service. Features progressive tool loading, automatic retry and failover, and centralized authentication management. Backed by Y Combinator. Launched on Product Hunt. Designed for teams building agentic AI applications that need many integrations without managing individual MCP servers.", "category": "infrastructure", "endpoint": "https://www.klavis.ai", "homepage_url": "https://www.klavis.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "gateway", "orchestration", "tool-management", "aggregation", "infrastructure", "multi-tool", "yc" ], "use_cases": [ "Connect AI agents to hundreds of SaaS tools through a single Strata MCP endpoint instead of configuring and managing individual MCP servers for each service", "Enable development teams to progressively scale their agent tool integrations with automatic retry, failover and centralized authentication management through Strata via MCP", "Build production-grade agentic applications that reliably orchestrate thousands of tools at scale through one unified MCP gateway from Klavis AI" ], "health": "active" }, { "id": "spanly-mcp", "name": "Spanly MCP Observability", "description": "MCP server observability platform from Spanly that provides full visibility into how AI agents interact with your MCP servers. Tracks error rates, session traces, tool call patterns and usage analytics for MCP-enabled products. Designed for teams shipping MCP servers as part of their product, helping them understand agent behavior, debug failures and optimize tool performance. Launched on Product Hunt.", "category": "infrastructure", "endpoint": "https://spanly.dev", "homepage_url": "https://spanly.dev", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "observability", "monitoring", "analytics", "debugging", "traces", "mcp-infrastructure", "devtools" ], "use_cases": [ "Monitor error rates, latency and usage patterns across your MCP servers through Spanly to understand how AI agents interact with your tools in production", "Debug failed tool calls and trace full agent sessions through Spanly observability to identify and fix issues in your MCP server implementation", "Analyze agent tool call patterns and usage analytics through Spanly to optimize MCP server performance and understand which tools agents use most" ], "health": "active" }, { "id": "ansible-mcp", "name": "Ansible MCP Server", "description": "MCP server from the Red Hat Ansible project that connects AI assistants to Ansible automation capabilities. Published as a standalone npm package from the VS Code Ansible extension. Enables developers and DevOps engineers to generate, lint and run Ansible playbooks, manage inventory, query module documentation and troubleshoot automation tasks through conversational AI interfaces. Part of the broader Ansible developer tools ecosystem. Open source.", "category": "code", "endpoint": "https://github.com/ansible/vscode-ansible", "homepage_url": "https://www.ansible.com", "github_url": "https://github.com/ansible/vscode-ansible", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-27", "updated": "2026-07-27", "tags": [ "ansible", "automation", "devops", "infrastructure-as-code", "red-hat", "playbooks", "configuration-management" ], "use_cases": [ "Generate and lint Ansible playbooks through Claude or other AI assistants connected to the Ansible MCP server for faster infrastructure automation development", "Enable DevOps engineers to query Ansible module documentation, troubleshoot failed tasks and manage inventory through natural language commands via AI assistants", "Build AI-assisted infrastructure automation workflows where agents create playbooks, validate configurations and execute Ansible tasks via MCP" ], "health": "active" }, { "id": "snapchat-ads-mcp", "name": "Snapchat Ads MCP Server", "description": "Official MCP server from Snap Inc. that opens the Snapchat advertising platform to third-party AI agents. Connects to the Snapchat Marketing API, enabling advertisers and partners to plan, create, optimize and scale campaigns across Snapchat's 950 million monthly active users through external AI tools. Part of Snap's Human-First AI-Enabled ads suite announced June 2026, alongside Snap Smart Assistant and AI creative tools. Follows Google, Amazon, Pinterest and Meta in exposing ad platform controls via MCP.", "category": "data", "endpoint": "https://ads.snapchat.com", "homepage_url": "https://forbusiness.snapchat.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-28", "updated": "2026-07-28", "tags": [ "advertising", "social-media", "snapchat", "ad-management", "campaign-optimization", "marketing" ], "use_cases": [ "Connect third-party AI agents to Snapchat Ads Manager for automated campaign creation, audience targeting and optimization through the Snapchat Marketing API via MCP", "Enable advertising agencies to manage multi-platform ad campaigns across Snapchat, Meta, Google and Pinterest from a single AI agent using the shared MCP protocol", "Build automated advertising workflows where AI agents monitor campaign performance, adjust budgets and generate creative assets across Snapchat inventory via MCP" ], "health": "active" }, { "id": "revid-mcp", "name": "Revid.ai MCP Server", "description": "MCP server from Revid.ai, a leading AI video creation platform, that gives AI agents direct access to the full video production pipeline. Supports nine production workflows including script-to-video, prompt-to-video and audio-to-video. Exposes tools for rendering, voice cloning, captioning, scheduling and publishing. Agents can manage the entire lifecycle from script generation to social media publication through stable tool names like render_video, export_video, clone_voice and publish_now. Supports OAuth 2.1 for hosted agents and API-key auth for local setups. Announced July 16, 2026.", "category": "ai", "endpoint": "https://www.revid.ai", "homepage_url": "https://www.revid.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-28", "updated": "2026-07-28", "tags": [ "video", "content-creation", "social-media", "automation", "creative", "publishing" ], "use_cases": [ "Generate complete short-form videos from prompts, scripts or audio files through AI agents connected to the Revid.ai MCP server with automatic rendering, voice integration and captioning", "Enable content creators to automate video production pipelines where AI agents handle scripting, rendering, voice cloning and social media publishing via Revid.ai MCP tools", "Build automated content workflows where AI agents produce and schedule multiple video variants across platforms using Revid.ai render_video, export_video and publish_now tools via MCP" ], "health": "active" }, { "id": "cyware-mcp", "name": "Cyware MCP Server", "description": "Open-source MCP server from Cyware that brings natural language interfaces to cyber threat intelligence workflows. Integrates with Cyware Intel Exchange and Cyware Orchestrate, enabling SOC analysts to query, summarize and act on threat intelligence data using conversational AI. Supports indicator lookups, CQL search translations, bulk tagging, enrichment metadata, playbook triggering and policy-based automation. Features comprehensive logging, auditability and explainability. Available on GitHub under open-source license.", "category": "infrastructure", "endpoint": "https://github.com/cyware-labs/cyware-mcpserver", "homepage_url": "https://www.cyware.com", "github_url": "https://github.com/cyware-labs/cyware-mcpserver", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-28", "updated": "2026-07-28", "tags": [ "threat-intelligence", "cybersecurity", "soc", "security-operations", "open-source", "incident-response" ], "use_cases": [ "Query and filter threat indicators using natural language through AI assistants connected to the Cyware MCP server instead of memorizing complex CQL query syntax", "Enable SOC analysts to trigger Cyware Orchestrate playbooks and automate incident response actions through conversational AI commands via MCP", "Build AI-powered threat intelligence workflows where agents search indicators, enrich data, manage tags and generate investigation summaries from Cyware Intel Exchange via MCP" ], "health": "active" }, { "id": "oviond-mcp", "name": "Oviond MCP Server", "description": "MCP server from Oviond, the marketing reporting platform for agencies, that connects AI assistants to client reporting data. Enables agency teams to query campaign performance, pull cross-channel analytics and generate client reports through AI tools without leaving their workflow. Designed for digital marketing agencies managing multi-client reporting across platforms like Google Ads, Meta, LinkedIn and Google Analytics. Keeps the core Oviond interface unchanged for non-technical team members while opening data access for AI-powered workflows. Announced July 29, 2026.", "category": "data", "endpoint": "https://www.oviond.com", "homepage_url": "https://www.oviond.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "marketing", "reporting", "analytics", "agency", "advertising", "dashboards" ], "use_cases": [ "Query cross-channel marketing performance data through AI assistants connected to the Oviond MCP server for instant client reporting without navigating the Oviond dashboard", "Enable marketing agencies to generate multi-client performance summaries and campaign analytics through natural language commands via AI tools connected to Oviond via MCP", "Build AI-powered agency workflows where agents pull campaign metrics from Google Ads, Meta, LinkedIn and other platforms through Oviond reporting data via MCP" ], "health": "active" }, { "id": "braze-mcp", "name": "Braze MCP Server", "description": "Remote-hosted MCP server from Braze, the customer engagement platform, that connects AI agents to campaign, Canvas, segment analytics and content management tools. Supports both read and write operations including email template creation, Content Block management and media library updates. Authenticates via OAuth tied to Braze dashboard user permissions with no API key required. Does not expose user-level PII. Works with Claude, ChatGPT, Cursor, Codex and Claude Code. Available at mcp.braze.com/mcp (US) and mcp.braze.eu/mcp (EU). Released July 23, 2026 in early access.", "category": "data", "endpoint": "https://mcp.braze.com/mcp", "homepage_url": "https://www.braze.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "customer-engagement", "marketing", "analytics", "email", "campaigns", "enterprise" ], "use_cases": [ "Query campaign and Canvas performance analytics, segment data and custom attributes through AI assistants connected to the Braze MCP server without navigating the Braze dashboard", "Enable marketing teams to create and update email templates, Content Blocks and media library assets through natural language commands via AI tools connected to Braze via MCP", "Build AI-powered customer engagement workflows where agents analyze campaign KPIs, explore segments and generate performance reports from Braze data via MCP" ], "health": "active" }, { "id": "syncro-mcp", "name": "Syncro MCP Server", "description": "MCP server from Syncro, the all-in-one PSA and RMM platform for managed service providers. Connects AI assistants to IT service management data including tickets, assets, endpoints and billing. Enables MSPs to query device status, manage tickets and automate IT operations through AI-powered workflows. Part of Syncro's July 2026 release alongside CIS M365 baselines and end user portal SSO. Designed for IT professionals managing multi-client environments who want conversational access to their service management data.", "category": "infrastructure", "endpoint": "https://www.syncromsp.com", "homepage_url": "https://www.syncromsp.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "msp", "rmm", "psa", "it-management", "ticketing", "endpoint-management" ], "use_cases": [ "Query device health, ticket status and endpoint information across managed clients through AI assistants connected to the Syncro MCP server without switching between client dashboards", "Enable MSP technicians to create and update tickets, check asset inventories and review billing data through natural language commands via AI tools connected to Syncro via MCP", "Build AI-powered IT operations workflows where agents monitor endpoint alerts, prioritize tickets and generate client status reports from Syncro service management data via MCP" ], "health": "active" }, { "id": "arcadedb-mcp", "name": "ArcadeDB MCP Server", "description": "Built-in MCP server in ArcadeDB, the open-source multi-model database supporting graph, document, key-value, time-series and search in a single engine. Introduced in ArcadeDB v26.3.1, the MCP server lets AI assistants connect directly for natural language queries, schema exploration and report generation. Supports connections from Claude Desktop, ChatGPT and any MCP-compatible client. Part of a major release with 190+ commits including geospatial indexing, materialized views and a redesigned Studio with AI Assistant.", "category": "data", "endpoint": "https://arcadedb.com", "homepage_url": "https://arcadedb.com", "github_url": "https://github.com/ArcadeData/arcadedb", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "database", "graph-database", "multi-model", "open-source", "sql", "time-series" ], "use_cases": [ "Query graph, document and time-series data using natural language through AI assistants connected to the ArcadeDB built-in MCP server without writing SQL or Gremlin queries manually", "Enable developers and data teams to explore database schemas, run ad-hoc queries and generate reports through conversational AI interfaces connected to ArcadeDB via MCP", "Build AI-powered data workflows where agents query multi-model data across graph, document and key-value stores in a single ArcadeDB instance via MCP" ], "health": "active" }, { "id": "bloomberg-enterprise-mcp", "name": "Bloomberg Enterprise MCP Server", "description": "Enterprise MCP implementation from Bloomberg LP that connects AI agents to Bloomberg's financial data and analytics infrastructure. Designed for institutional workflows in trading, research and portfolio management. Built with enterprise-grade security, access controls and audit capabilities. Part of Bloomberg's broader AI integration strategy for financial services. Lessons and architecture shared publicly July 21, 2026. Targets banks, asset managers and hedge funds that need governed AI access to market data and analytics.", "category": "data", "endpoint": "https://www.bloomberg.com", "homepage_url": "https://www.bloomberg.com/company/stories/what-we-learned-building-enterprise-mcp-at-bloomberg/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "finance", "market-data", "enterprise", "trading", "analytics", "institutional" ], "use_cases": [ "Query Bloomberg market data, analytics and research through AI agents connected to the Bloomberg Enterprise MCP server for real-time financial intelligence without switching to a Bloomberg Terminal", "Enable portfolio managers and research analysts to retrieve pricing, fundamental data and market analytics through natural language commands via AI tools connected to Bloomberg via MCP", "Build AI-powered financial workflows where agents monitor market conditions, analyze portfolio exposures and generate investment research summaries from Bloomberg data via MCP" ], "health": "active" }, { "id": "kintone-mcp", "name": "Kintone MCP Server", "description": "Official MCP server from Cybozu for Kintone, the no-code business application platform popular in Japan and expanding globally. Provides 25 tools covering app management, record CRUD operations, process management, form field configuration, file downloads and space management. Supports Docker, npm and MCPB (Claude Desktop package) installation. Features password, API token and client certificate authentication with proxy support. Open source under Apache 2.0. Actively maintained with 468 commits and regular releases. Latest release v1.9.1 on July 23, 2026.", "category": "productivity", "endpoint": "https://www.kintone.com", "homepage_url": "https://www.kintone.com", "github_url": "https://github.com/kintone/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g @kintone/mcp-server", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "no-code", "business-apps", "crm", "workflow", "japan", "open-source", "cybozu" ], "use_cases": [ "Manage Kintone business application records including creation, retrieval, updates and deletion through AI assistants connected to the official Kintone MCP server via natural language commands", "Enable teams to configure Kintone app forms, manage process workflows and query app data through AI tools connected to Kintone via MCP without navigating the Kintone interface", "Build AI-powered business process workflows where agents monitor Kintone records, update statuses, add comments and manage spaces across multiple Kintone apps via MCP" ], "health": "active" }, { "id": "luzmo-mcp", "name": "Luzmo MCP Server", "description": "Hosted MCP server from Luzmo, the embedded analytics platform, that gives AI agents access to Luzmo IQ natural language analytics and on-demand chart generation. Supports two scenarios: adding Luzmo as a capability inside your own agent (OpenAI Agents SDK, Claude Agent SDK, LangChain) and exposing a user-facing MCP from your product. Features dataset and column search, embed token access control, and supports the MCP App standard for rendering charts inside Claude and ChatGPT. Source code available for custom builds. Released June 2026.", "category": "data", "endpoint": "https://developer.luzmo.com", "homepage_url": "https://www.luzmo.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "analytics", "embedded-analytics", "charts", "data-visualization", "bi", "saas" ], "use_cases": [ "Query business data and generate Luzmo IQ natural language analytics answers through AI agents connected to the Luzmo MCP server for instant data insights without building custom API integrations", "Enable AI agents to create Luzmo charts on demand and search datasets and columns through the Luzmo MCP server for dynamic data visualization inside agent workflows", "Build AI-powered analytics products where agents serve embedded Luzmo charts and IQ answers to end users through the MCP App standard for rendering in Claude and ChatGPT" ], "health": "active" }, { "id": "snowflake-cortex-ai-gateway-mcp", "name": "Snowflake Cortex AI Gateway MCP Server", "description": "MCP governance and security layer from Snowflake, announced at Black Hat 2026 on July 29. Part of Snowflake Cortex AI Gateway, it provides enterprise-grade controls for AI agent interactions with MCP servers including agent identity management, tool-level access policies, request auditing and data governance. Enables security teams to define which agents can access which MCP tools, enforce data classification policies and maintain audit trails across agentic workflows. Designed for enterprises running AI agents at scale that need centralized MCP governance without modifying individual server implementations.", "category": "infrastructure", "endpoint": "https://www.snowflake.com", "homepage_url": "https://www.snowflake.com/en/blog/enterprise-ai-security-agentic-mcp-governance/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-29", "updated": "2026-07-29", "tags": [ "security", "governance", "enterprise", "data-governance", "identity", "audit" ], "use_cases": [ "Enforce tool-level access policies and agent identity controls across MCP server connections through the Snowflake Cortex AI Gateway for centralized agentic governance without modifying individual servers", "Enable security teams to audit all AI agent interactions with MCP tools, track data access patterns and enforce data classification policies through Snowflake Cortex AI Gateway MCP governance", "Build enterprise-grade agentic architectures where Snowflake Cortex AI Gateway governs which agents access which MCP tools with role-based policies, request logging and real-time security controls" ], "health": "active" }, { "id": "browserstack-mcp", "name": "BrowserStack MCP Server", "description": "Open-source MCP server from BrowserStack, the AI-native software testing platform, that connects AI agents and coding assistants to BrowserStack's cloud testing infrastructure. Enables automated cross-browser testing, device management and test execution through AI tools like GitHub Copilot, Cursor and Claude Code. Supports manual and automated web testing, app testing and accessibility checks through natural language commands. Part of BrowserStack's AI portfolio alongside Test Companion for IDE-based agentic test automation. Open source on GitHub under browserstack/mcp-server. Announced alongside Test Companion on July 29, 2026.", "category": "code", "endpoint": "https://www.browserstack.com", "homepage_url": "https://www.browserstack.com/docs/browserstack-mcp-server/overview", "github_url": "https://github.com/browserstack/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "testing", "browser-testing", "qa", "automation", "open-source", "cross-browser", "accessibility" ], "use_cases": [ "Run cross-browser and cross-device tests through AI coding assistants connected to the BrowserStack MCP server without leaving the IDE or switching to the BrowserStack dashboard", "Enable QA teams and developers to execute automated test suites, check accessibility compliance and manage test sessions through natural language commands via AI tools connected to BrowserStack via MCP", "Build AI-powered testing workflows where agents open websites on specific browsers, run Selenium or Playwright tests and report results from BrowserStack's cloud infrastructure via MCP" ], "health": "active" }, { "id": "xero-mcp", "name": "Xero MCP Server", "description": "Official MCP server from Xero, the cloud accounting platform, that bridges AI frameworks to the Xero API for accounting automation. Part of the Xero Agent Toolkit alongside OpenAI Agents SDK and LangChain integrations. Enables AI assistants to manage invoices, contacts, bank transactions, reports and chart of accounts through natural language. Supports Claude Desktop, Claude Code and any MCP-compatible client. Authenticates via OAuth connected to Xero developer apps. Designed for accountants, bookkeepers and developers building AI-powered financial workflows.", "category": "productivity", "endpoint": "https://developer.xero.com", "homepage_url": "https://developer.xero.com/ai", "github_url": "https://github.com/XeroAPI/xero-agent-toolkit", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "accounting", "finance", "invoicing", "bookkeeping", "cloud-accounting", "open-source" ], "use_cases": [ "Manage invoices, contacts and bank transactions through AI assistants connected to the Xero MCP server without navigating the Xero dashboard manually", "Enable accountants and bookkeepers to query financial reports, reconcile transactions and generate statements through natural language commands via AI tools connected to Xero via MCP", "Build AI-powered accounting workflows where agents create invoices, update contact records and pull profit-and-loss data from Xero using the MCP-based Agent Toolkit" ], "health": "active" }, { "id": "glean-mcp", "name": "Glean MCP Server", "description": "Remote MCP server from Glean, the enterprise AI search platform, that gives AI agents access to company-wide knowledge including search, chat, document reading, code search and people directories. Supports remote MCP server deployment for centralized enterprise management of which tools are exposed. Works with Claude Desktop, Claude Code, Cursor and other MCP-compatible clients. Enterprises can centrally control tool exposure and permissions. Brings full company context into developer IDEs and AI tools for context-aware reasoning across all connected enterprise data sources.", "category": "data", "endpoint": "https://docs.glean.com", "homepage_url": "https://www.glean.com/blog/mcp-servers-septdrop-2025", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "enterprise-search", "knowledge-management", "ai-search", "enterprise", "code-search", "remote-mcp" ], "use_cases": [ "Search across all company knowledge sources including documents, code, people and chat through AI assistants connected to the Glean MCP server for instant enterprise-wide context", "Enable developers to pull relevant business context, internal documentation and code references into their IDE through Glean's remote MCP server for context-aware AI coding assistance", "Build AI-powered enterprise workflows where agents query Glean's unified search index, read documents and surface relevant people and expertise from across the organization via MCP" ], "health": "active" }, { "id": "masset-mcp", "name": "Masset MCP Server", "description": "MCP server from Masset, the digital asset management platform for business content, that exposes 32 tools for AI agents to search, manage and organize content assets. Provides read and write access to DAM operations including asset search, metadata management, content organization and media operations. Designed for marketing teams, content operations and enterprise knowledge management. Enables AI assistants to find and work with brand assets, documents and media files through natural language. Native MCP integration distinguishes Masset from competitors in the DAM space.", "category": "media", "endpoint": "https://www.getmasset.com", "homepage_url": "https://www.getmasset.com/software/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "dam", "digital-asset-management", "content-management", "media", "marketing", "brand-assets" ], "use_cases": [ "Search and retrieve brand assets, documents and media files through AI assistants connected to the Masset MCP server for instant access to business content without navigating the DAM interface", "Enable marketing teams to organize, tag and manage digital assets through natural language commands via AI tools connected to Masset's 32-tool MCP server", "Build AI-powered content workflows where agents search brand asset libraries, update metadata and surface relevant content from Masset's DAM platform via MCP" ], "health": "active" }, { "id": "paragon-actionkit-mcp", "name": "Paragon ActionKit MCP Server", "description": "MCP server from Paragon (useparagon.com) that provides access to prebuilt actions for over 130 SaaS integrations through a single MCP endpoint. Uses SSE transport to support multi-tenant MCP clients. Listed on the Anthropic MCP registry. Supports managed OAuth per end user and per-tenant isolation. Enables AI agents to execute actions across CRM, project management, communication and other enterprise tools through one standardized interface. Backed by SOC 2 compliance. Open source on GitHub under useparagon/paragon-mcp.", "category": "infrastructure", "endpoint": "https://www.useparagon.com", "homepage_url": "https://www.useparagon.com/use-case/article/agentic-actions", "github_url": "https://github.com/useparagon/paragon-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "sse", "auth": "oauth", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "integrations", "saas", "multi-tenant", "oauth", "enterprise", "open-source", "crm", "automation" ], "use_cases": [ "Execute actions across 130+ SaaS tools through a single AI agent connection to the Paragon ActionKit MCP server without building separate integrations for each service", "Enable AI agents to perform CRM updates, project management tasks and communication workflows across enterprise tools through Paragon's unified MCP endpoint with per-user OAuth isolation", "Build multi-tenant agentic applications where AI agents act on behalf of end users across Salesforce, HubSpot, Jira, Slack and other SaaS platforms through one Paragon ActionKit MCP connection" ], "health": "active" }, { "id": "dukascopy-mcp", "name": "Dukascopy MCP Server", "description": "MCP server from Dukascopy Bank, the Swiss-regulated forex and CFD broker, that enables AI assistants to interact with live trading accounts. First Swiss bank to launch AI-powered trading via MCP. Allows clients to place trades, analyze markets, manage risk and monitor positions through natural language commands in ChatGPT, Claude and other AI assistants. Powered by the Dukascopy trading API with institutional-grade execution. Designed for forex and CFD traders who want conversational access to their trading accounts with full regulatory compliance.", "category": "data", "endpoint": "https://ai.dukascopy.com", "homepage_url": "https://ai.dukascopy.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "trading", "forex", "finance", "banking", "swiss-bank", "cfds", "risk-management" ], "use_cases": [ "Place forex and CFD trades through AI assistants connected to the Dukascopy MCP server using natural language commands without navigating the trading platform manually", "Enable traders to analyze market conditions, monitor open positions and manage risk through conversational AI interfaces connected to their Dukascopy Bank account via MCP", "Build AI-powered trading workflows where agents execute trades, check account balances and retrieve market data from Dukascopy's Swiss-regulated platform via MCP" ], "health": "active" }, { "id": "sensor-tower-mcp", "name": "Sensor Tower MCP Server", "description": "MCP server from Sensor Tower, the digital intelligence and app data analytics platform, that gives AI agents access to app store analytics, digital advertising insights and market intelligence data. Enables agents to query app download estimates, revenue data, keyword rankings, advertising creative intelligence and market trends through natural language. Designed for mobile app marketers, product managers and competitive intelligence teams who need programmatic access to Sensor Tower's datasets through AI-powered workflows.", "category": "data", "endpoint": "https://sensortower.com", "homepage_url": "https://sensortower.com/blog/introducing-the-sensor-tower-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "app-analytics", "mobile", "market-intelligence", "advertising", "competitive-intelligence", "app-store" ], "use_cases": [ "Query app store download estimates, revenue data and keyword rankings through AI assistants connected to the Sensor Tower MCP server for instant mobile market intelligence", "Enable product managers and marketers to analyze competitive app landscapes, track advertising creative trends and monitor market shifts through AI tools connected to Sensor Tower via MCP", "Build AI-powered mobile intelligence workflows where agents pull app performance data, compare competitor metrics and generate market reports from Sensor Tower's analytics platform via MCP" ], "health": "active" }, { "id": "microsoft-etw-mcp", "name": "Microsoft ETW MCP Server", "description": "Local MCP server from Microsoft for AI-assisted analysis of Event Tracing for Windows (ETW) traces. Gives AI assistants structured read-only access to ETL trace data including CPU usage, process filtering, time range analysis, trace comparison and critical path walking. Powered by the TraceProcessor engine that drives Windows Performance Analyzer (WPA). Uses STDIO transport for local operation. Works with GitHub Copilot, Claude Code and any MCP-compatible AI assistant. Companion to the upcoming WPA MCP server. Early preview release from the Microsoft Performance Diagnostics team.", "category": "code", "endpoint": "https://devblogs.microsoft.com", "homepage_url": "https://devblogs.microsoft.com/performance-diagnostics/etw-mcp-intro/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "windows", "performance", "diagnostics", "tracing", "debugging", "microsoft", "developer-tools" ], "use_cases": [ "Analyze Windows ETW performance traces through AI assistants connected to the Microsoft ETW MCP server for AI-guided performance diagnostics without manually navigating WPA", "Enable developers and performance engineers to query CPU usage patterns, filter by process, compare traces and walk critical paths through natural language commands via AI tools connected to the ETW MCP server", "Build AI-powered Windows performance analysis workflows where agents process ETL traces, identify bottlenecks and generate diagnostic reports using the TraceProcessor engine via MCP" ], "health": "active" }, { "id": "draup-mcp", "name": "Draup MCP Server", "description": "MCP server from Draup, the AI-powered account and market intelligence platform, that brings context-rich sales intelligence into AI agent workflows. Surfaces hiring surges, funding events, IT spend shifts, executive moves and other buying signals. Converts intelligence into actionable next steps for sales teams. Certified MCP server listed in the Microsoft Copilot Studio directory for Dynamics 365 Sales integration. Designed for enterprise sales teams using AI agents for account research and sales qualification. Announced as part of the Microsoft Dynamics 365 MCP partner ecosystem in July 2026.", "category": "data", "endpoint": "https://draup.com", "homepage_url": "https://draup.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-30", "updated": "2026-07-30", "tags": [ "sales-intelligence", "market-intelligence", "enterprise", "sales", "account-intelligence", "dynamics-365" ], "use_cases": [ "Surface hiring surges, funding events and executive moves for target accounts through AI agents connected to the Draup MCP server for real-time sales intelligence without manual research", "Enable sales teams to qualify leads and identify buying signals through natural language queries to Draup's account intelligence platform via AI tools connected through MCP", "Build AI-powered sales workflows where agents research accounts, analyze IT spend shifts and generate actionable next steps from Draup's market intelligence data via MCP integrated with Dynamics 365" ], "health": "active" }, { "id": "casepoint-mcp", "name": "Casepoint MCP Server", "description": "Official MCP server from Casepoint, a leader in AI-powered legal, investigative and compliance solutions for government agencies and enterprises. Enables AI models, agents and ecosystems to connect with the Casepoint platform across eDiscovery, legal hold, investigations, FOIA and other legal and compliance workflows. Initial release includes capabilities across Casepoint eDiscovery, Legal Hold and FOIA applications. Allows organizations to use their preferred AI models while maintaining data security and governance. Works with Claude, ChatGPT and other MCP-compatible clients. Announced July 30, 2026.", "category": "productivity", "endpoint": "https://www.casepoint.com", "homepage_url": "https://www.casepoint.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "legal", "ediscovery", "compliance", "government", "legal-hold", "foia", "enterprise" ], "use_cases": [ "Connect AI assistants to Casepoint's eDiscovery platform via MCP to search, review and analyze case documents using natural language commands without switching to the Casepoint interface", "Enable legal teams and government agencies to manage legal holds, track custodian compliance and run FOIA workflows through AI tools connected to Casepoint via MCP", "Build AI-powered legal workflows where agents query case data, generate review summaries and manage document collections across Casepoint's investigation and compliance modules via MCP" ], "health": "active" }, { "id": "edge-negotiation-mcp", "name": "Edge Negotiation MCP Server", "description": "Enterprise MCP server from The Edge Negotiation Group that embeds negotiation methodology, planning tools and simulation technology directly into corporate AI environments. Allows organizations to plug negotiation training, case studies, deal planning and role-play simulations into existing AI platforms like Claude, ChatGPT and Copilot. Includes Deal Spar AI sparring tool for real-time negotiation practice and guidance. Designed for post-workshop adoption and enterprise skill development. Announced July 30, 2026.", "category": "productivity", "endpoint": "https://www.edgenegotiationgroup.com", "homepage_url": "https://www.edgenegotiationgroup.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "negotiation", "enterprise", "training", "sales", "simulation", "coaching" ], "use_cases": [ "Embed negotiation methodology and planning tools into corporate AI environments via MCP so employees can access real-time deal guidance and case studies without leaving their workflow", "Enable sales and procurement teams to run AI-powered negotiation simulations and role-play scenarios through the Deal Spar tool connected via MCP to their existing enterprise AI platform", "Build AI-assisted negotiation workflows where agents provide strategy recommendations, analyze counterparty positions and surface relevant case studies from the Edge methodology via MCP" ], "health": "active" }, { "id": "violet-audio-dmix-mcp", "name": "Violet Audio dMix 128 MCP Server", "description": "MCP server built into the Violet Audio dMix 128 digital mixing console that enables AI-powered mixing and workflow automation. Allows AI assistants to control mixing parameters, manage audio routing and automate repetitive mixing tasks through natural language. Bridges professional audio engineering with AI agent workflows. Part of Violet Audio's push to bring AI directly into professional audio hardware. Announced July 25, 2026.", "category": "media", "endpoint": "https://www.violetaudio.com", "homepage_url": "https://www.violetaudio.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "audio", "mixing", "music-production", "hardware", "professional-audio", "automation" ], "use_cases": [ "Control mixing console parameters, channel routing and effects through AI assistants connected to the dMix 128 MCP server using natural language commands during live or studio sessions", "Automate repetitive mixing tasks like gain staging, channel naming and routing presets through AI agents connected to the Violet Audio dMix 128 via MCP", "Build AI-powered audio workflows where agents manage mix snapshots, recall scenes and adjust monitor sends on the dMix 128 mixing console through MCP integration" ], "health": "active" }, { "id": "medplum-mcp", "name": "Medplum MCP Server", "description": "Open-source MCP server from Medplum, the healthcare infrastructure platform, that connects AI agents to FHIR-compliant healthcare data. Enables AI assistants to search patients, read clinical resources, manage encounters and interact with electronic health records through the Medplum API. Supports both Medplum hosted and self-hosted server deployments. Works with Claude Desktop, Claude Code, Cursor and other MCP-compatible clients. Open source on GitHub under medplum/medplum-mcp-server.", "category": "data", "endpoint": "https://www.medplum.com", "homepage_url": "https://www.medplum.com", "github_url": "https://github.com/medplum/medplum-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm run dev", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "healthcare", "fhir", "ehr", "medical", "open-source", "clinical-data", "health-records" ], "use_cases": [ "Search and retrieve patient records, clinical encounters and FHIR resources through AI assistants connected to the Medplum MCP server without navigating the EHR interface directly", "Enable healthcare developers to build AI-powered clinical workflows that read patient data, manage encounters and query health records from Medplum via MCP", "Connect AI coding assistants to a Medplum server via MCP to prototype healthcare integrations, test FHIR queries and build clinical decision support tools" ], "health": "active" }, { "id": "contractors-cloud-mcp", "name": "Contractors Cloud MCP Server", "description": "MCP server from Contractors Cloud, an AI-first CRM platform for the roofing industry, that enables AI agents to manage roofing project workflows. Connects AI assistants to project data, customer records, estimates, work orders and scheduling. Designed for roofing contractors to automate project management through AI tools. Part of Contractors Cloud's AI-first CRM strategy. Announced July 29, 2026.", "category": "productivity", "endpoint": "https://contractorscloud.com", "homepage_url": "https://contractorscloud.com/blog/ai-first-contractors-cloud-launches-mcp-server-revolutionizing-roofing-project-management/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "crm", "construction", "roofing", "project-management", "contractor", "field-service" ], "use_cases": [ "Manage roofing project workflows, customer records and estimates through AI assistants connected to Contractors Cloud via MCP without switching to the CRM dashboard", "Enable roofing contractors to query project status, schedule work orders and generate estimates through natural language commands via AI tools connected to Contractors Cloud via MCP", "Build AI-powered construction workflows where agents track job progress, manage customer communications and update project records in Contractors Cloud via MCP" ], "health": "active" }, { "id": "kinocut-mcp", "name": "Kinocut MCP Server", "description": "Open-source guardrailed video editing MCP server from Kyanite Labs that gives AI agents control over video editing operations. Built on FFmpeg with Hyperframes support for frame-accurate editing. Includes repurposing tools for content adaptation, a Python client library and CLI. Runs locally for fast processing. Designed with safety guardrails to prevent destructive operations on source media. Free and open source on GitHub.", "category": "media", "endpoint": "https://github.com/KyaniteLabs/kinocut", "homepage_url": "https://github.com/KyaniteLabs/kinocut", "github_url": "https://github.com/KyaniteLabs/kinocut", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "video-editing", "ffmpeg", "media", "content-repurposing", "open-source", "local" ], "use_cases": [ "Enable AI agents to perform frame-accurate video editing operations like trimming, splitting and concatenating clips through the Kinocut MCP server with built-in safety guardrails", "Automate content repurposing workflows where AI agents extract highlights, resize for different platforms and generate clips from longer videos using Kinocut via MCP", "Build AI-powered video production pipelines where agents process raw footage, apply edits and export final cuts locally through FFmpeg operations exposed via the Kinocut MCP server" ], "health": "active" }, { "id": "salesforce-slack-mcp", "name": "Salesforce Slack MCP Servers", "description": "MCP servers from Salesforce that turn Slack into an AI workspace by enabling multiple AI agents to operate within Slack with centralized authentication and governance. Part of Salesforce's push to deepen Slack's role in enterprise AI by allowing users to orchestrate AI agents from different providers while maintaining security controls. Supports centralized auth so agents inherit workspace-level permissions. Works with Claude, ChatGPT and other MCP-compatible AI platforms operating through Slack. Announced July 25, 2026.", "category": "productivity", "endpoint": "https://slack.com", "homepage_url": "https://cloudwars.com/cloud-wars-minute/salesforce-launches-mcp-servers-to-turn-slack-into-an-ai-workspace/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "slack", "salesforce", "enterprise", "collaboration", "messaging", "ai-workspace", "governance" ], "use_cases": [ "Orchestrate multiple AI agents within Slack through Salesforce MCP servers with centralized authentication so agents inherit workspace-level permissions and security policies", "Enable enterprise teams to interact with AI agents from different providers directly in Slack channels via MCP while maintaining centralized governance and audit controls", "Build AI-powered Slack workflows where agents from Claude, ChatGPT and other platforms access Slack data, manage channels and respond to messages through Salesforce's MCP integration" ], "health": "active" }, { "id": "vibe-trading-mcp", "name": "Vibe Trading MCP Server", "description": "Open-source MCP server from the Vibe Trading personal trading agent platform. Exposes trading tools, portfolio analysis, market data and strategy execution to AI assistants and coding agents. Supports stdio, Streamable HTTP and legacy SSE transports. Can also act as an MCP client to connect to external MCP tool servers via SWARM mode. Installable via PyPI. Works with Claude Code, Cursor, Codex and other MCP-compatible clients. Open source on GitHub.", "category": "data", "endpoint": "https://github.com/HKUDS/Vibe-Trading", "homepage_url": "https://github.com/HKUDS/Vibe-Trading", "github_url": "https://github.com/HKUDS/Vibe-Trading", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install vibe-trading", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "trading", "finance", "portfolio", "market-data", "open-source", "python" ], "use_cases": [ "Connect AI coding assistants to Vibe Trading via MCP to analyze portfolios, query market data and execute trading strategies through natural language commands", "Build AI-powered trading workflows where agents monitor positions, run backtests and manage risk using Vibe Trading tools exposed through the MCP server", "Use Vibe Trading as both an MCP server and client in SWARM mode to orchestrate multi-agent trading systems that combine external market data tools with portfolio management via MCP" ], "health": "active" }, { "id": "hashicorp-consul-mcp", "name": "HashiCorp Consul MCP Server", "description": "MCP server from HashiCorp for Consul, the service mesh and service discovery platform. Enables AI agents to query service catalogs, check health statuses, manage key-value stores and interact with Consul's service networking features through MCP. Note: versions 0.1.0 through 0.1.3 were subject to security advisory HCSEC-2026-24 addressing multiple vulnerabilities, with fixes available in 0.1.4+. Works with Claude Desktop, Claude Code and other MCP-compatible clients.", "category": "infrastructure", "endpoint": "https://www.hashicorp.com/consul", "homepage_url": "https://www.hashicorp.com/consul", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "service-mesh", "service-discovery", "consul", "hashicorp", "infrastructure", "devops", "networking" ], "use_cases": [ "Query Consul service catalogs, check service health statuses and browse key-value store data through AI assistants connected to the Consul MCP server without using the Consul CLI or UI", "Enable platform engineers to manage service mesh configurations, inspect service intentions and troubleshoot connectivity issues through natural language commands via AI tools connected to Consul via MCP", "Build AI-powered infrastructure workflows where agents monitor service health, update configuration values and manage service registrations in HashiCorp Consul through MCP" ], "health": "active" }, { "id": "mondoo-shadow-ai-mcp", "name": "Mondoo Shadow AI Discovery", "description": "Security platform from Mondoo that discovers, assesses risk and enforces policy controls for enterprise AI agents and MCP servers. Scans for shadow AI deployments including unauthorized agents, exposed MCP servers and leaked credentials across the organization. Provides vulnerability management, risk scoring and remediation guidance for AI infrastructure. Integrates with existing security workflows. Part of Mondoo's expansion into AI agent governance and security. Announced July 29, 2026.", "category": "infrastructure", "endpoint": "https://mondoo.com", "homepage_url": "https://mondoo.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-07-31", "updated": "2026-07-31", "tags": [ "security", "shadow-ai", "vulnerability-management", "compliance", "ai-governance", "enterprise" ], "use_cases": [ "Discover unauthorized AI agents, MCP servers and exposed credentials across enterprise infrastructure using Mondoo's shadow AI scanning through MCP-connected security tools", "Enable security teams to assess risk scores, enforce policy controls and generate remediation guidance for all AI agent deployments through Mondoo's MCP-integrated vulnerability management", "Build AI-powered security workflows where agents continuously monitor for new shadow AI deployments, flag policy violations and track remediation status across the organization via Mondoo's MCP integration" ], "health": "active" }, { "id": "gethookd-mcp", "name": "GetHookd MCP Server", "description": "MCP server from GetHookd, an ecommerce advertising research and creative generation platform. Enables AI agents to search competitor ad libraries, analyze ad creative performance, identify winning hooks and CTAs, and generate ad concepts directly through MCP-connected workflows. Designed for ecommerce brands and agencies building AI-powered advertising pipelines. Announced July 31, 2026.", "category": "data", "endpoint": "https://www.gethookd.ai", "homepage_url": "https://www.gethookd.ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "ecommerce", "advertising", "ad-research", "creative", "marketing", "competitive-intelligence" ], "use_cases": [ "Search and analyze competitor ad creatives across Facebook, Instagram and TikTok through AI assistants connected to GetHookd via MCP to identify winning hooks, CTAs and creative patterns without manual library browsing", "Enable ecommerce marketing teams to generate ad concepts and creative briefs informed by competitive research data from GetHookd directly within AI-powered advertising workflows via MCP", "Build automated competitive intelligence pipelines where AI agents monitor competitor ad activity, surface trending creative formats and recommend creative strategies using GetHookd data via MCP" ], "health": "active" }, { "id": "tenzir-mcp", "name": "Tenzir MCP Server", "description": "Open-source MCP server from Tenzir, the security data engineering platform, that uses AI to automatically generate valid Tenzir Query Language (TQL) pipelines for OCSF schema mappings. Takes raw security log samples and returns validated TQL pipelines that map them to the Open Cybersecurity Schema Framework. Built with OCSF at its core. Runs locally for fast processing. Open source on GitHub under tenzir/mcp.", "category": "infrastructure", "endpoint": "https://github.com/tenzir/mcp", "homepage_url": "https://tenzir.com/blog/announcing-the-tenzir-mcp-server-ai-generated-ocsf-mappings", "github_url": "https://github.com/tenzir/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "security", "ocsf", "siem", "log-mapping", "data-engineering", "open-source", "tql" ], "use_cases": [ "Generate validated OCSF schema mappings from raw security logs by providing log samples to the Tenzir MCP server and receiving production-ready TQL pipelines without manually writing transformation rules", "Accelerate OCSF adoption across security teams by letting AI assistants connected to the Tenzir MCP server automatically map vendor-specific log formats to standardized OCSF event classes", "Build AI-powered security data engineering workflows where agents normalize heterogeneous security telemetry into OCSF-compliant pipelines using Tenzir TQL through MCP" ], "health": "active" }, { "id": "regrid-mcp", "name": "Regrid MCP Server", "description": "MCP server from Regrid, the definitive U.S. and Canadian parcel data platform, connecting AI agents directly to 160 million-plus land parcels with standardized property records. Enables AI tools to search parcels by location, zoning, acreage, ownership and building criteria. Supports both schema exploration without an API key and live parcel data retrieval with an API token. Works with Claude, ChatGPT, Perplexity, Cursor and other MCP-compatible clients. Launched July 2026.", "category": "data", "endpoint": "https://regrid.com/mcp", "homepage_url": "https://regrid.com/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "real-estate", "parcel-data", "property", "land-intelligence", "geospatial", "zoning", "gis" ], "use_cases": [ "Search 160 million-plus U.S. and Canadian parcels by location, zoning, acreage, ownership or building criteria through AI assistants connected to Regrid via MCP without navigating the Regrid platform", "Enable real estate professionals and developers to retrieve live parcel records, ownership details, zoning information and building data through natural language queries via AI tools connected to Regrid via MCP", "Build AI-powered land intelligence workflows where agents analyze property records, identify parcels matching investment criteria and generate site selection reports using Regrid data via MCP" ], "health": "active" }, { "id": "zylo-mcp", "name": "Zylo MCP Server", "description": "MCP server from Zylo, the enterprise SaaS management platform, now in public preview. Enables AI assistants to query SaaS spend data, license utilization, renewal schedules, duplicate application detection, and savings opportunities. Transforms Zylo from a standalone dashboard into a knowledge source accessible from Claude, ChatGPT and other MCP-compatible clients. Designed for IT, procurement and finance teams managing enterprise software portfolios.", "category": "productivity", "endpoint": "https://zylo.com", "homepage_url": "https://zylo.com/blog/zylo-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "saas-management", "spend-management", "license-optimization", "procurement", "enterprise", "it-management" ], "use_cases": [ "Query enterprise SaaS spend, license utilization and renewal data through AI assistants connected to Zylo via MCP to surface savings opportunities and underutilized subscriptions without navigating the Zylo dashboard", "Enable IT procurement teams to generate executive-ready SaaS spend reports and renewal summaries by asking AI tools to extract and format data from Zylo via MCP", "Build AI-powered SaaS rationalization workflows where agents identify duplicate applications, forecast consumption-based costs and prioritize renewals using Zylo intelligence via MCP" ], "health": "active" }, { "id": "datarobot-global-mcp", "name": "DataRobot Global MCP Server", "description": "Global MCP server from DataRobot, the enterprise AI and machine learning platform. A persistently-deployed MCP server that provides AI agents with access to DataRobot models, deployments, predictions and monitoring capabilities. Supports both local development and production deployment modes. Enables external AI assistants to interact with DataRobot deployments, run predictions, and manage ML workflows through MCP. Introduced in DataRobot v11.8.", "category": "ai", "endpoint": "https://www.datarobot.com", "homepage_url": "https://www.datarobot.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "machine-learning", "mlops", "ai-platform", "predictions", "model-management", "enterprise", "automl" ], "use_cases": [ "Run predictions against deployed DataRobot models through AI assistants connected to the Global MCP server without navigating the DataRobot platform or writing API integration code", "Enable data science teams to monitor model performance, check deployment health and manage ML workflows through natural language commands via AI tools connected to DataRobot via MCP", "Build AI-powered ML operations pipelines where agents trigger retraining, compare model accuracy and surface prediction drift alerts using DataRobot capabilities via MCP" ], "health": "active" }, { "id": "scoro-mcp", "name": "Scoro MCP Server", "description": "MCP server from Scoro, the end-to-end work management platform for professional services and agencies. Securely connects Scoro workspaces to Claude, ChatGPT and other MCP-compatible AI tools. Enables AI assistants to manage projects, tasks, budgets, time entries, contacts and invoices. Supports project budget analysis with planned vs actual comparisons, role-based selling prices, and project phase management.", "category": "productivity", "endpoint": "https://www.scoro.com/mcp/", "homepage_url": "https://www.scoro.com/mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "project-management", "work-management", "professional-services", "agency", "budgeting", "time-tracking", "invoicing" ], "use_cases": [ "Manage Scoro projects, tasks and time entries through AI assistants via MCP without switching to the Scoro dashboard, enabling project managers to update status and assign work through natural language", "Enable professional services teams to analyze project budgets with planned vs actual comparisons, track labor costs and review revenue projections through AI tools connected to Scoro via MCP", "Build AI-powered agency workflows where agents create invoices, update contact records and generate project profitability reports using Scoro data via MCP" ], "health": "active" }, { "id": "gainsight-mcp", "name": "Gainsight CS MCP Server", "description": "MCP server from Gainsight, the leading customer success platform, that brings customer retention data and workflows into the agentic AI era. Enables AI assistants to access customer health scores, renewal timelines, churn risk signals, product usage analytics and customer journey data. Powers AI-driven retention workflows through Claude, ChatGPT and other MCP-compatible tools. Part of Gainsight's July 2026 platform release.", "category": "data", "endpoint": "https://www.gainsight.com", "homepage_url": "https://www.gainsight.com/press/gainsight-opens-its-platform-with-mcp-bringing-customer-retention-into-the-agentic-era/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-01", "updated": "2026-08-01", "tags": [ "customer-success", "retention", "churn-prediction", "health-scores", "saas", "enterprise", "analytics" ], "use_cases": [ "Query customer health scores, renewal timelines and churn risk signals through AI assistants connected to Gainsight via MCP to identify at-risk accounts without navigating the Gainsight dashboard", "Enable customer success teams to generate account review summaries, track product adoption metrics and surface expansion opportunities through natural language commands via AI tools connected to Gainsight via MCP", "Build AI-powered retention workflows where agents monitor customer health trends, trigger proactive outreach and generate churn risk reports using Gainsight data via MCP" ], "health": "active" }, { "id": "nethunt-crm-mcp", "name": "NetHunt CRM MCP Server", "description": "MCP server from NetHunt CRM that gives AI tools direct read-and-write access to CRM folders, records and timeline data. Enables sales teams to find deals and contacts, pull customer interaction history, update records, enrich data and generate pipeline reports through natural language in Claude, ChatGPT and other MCP-compatible tools. Setup requires no coding with a simple URL-based connection. Launched July 2026.", "category": "productivity", "endpoint": "https://nethunt.com", "homepage_url": "https://nethunt.com/blog/nethunt-crm-releases-mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "crm", "sales", "contacts", "pipeline", "lead-management", "customer-data" ], "use_cases": [ "Search deals, contacts and interaction history in NetHunt CRM through AI assistants connected via MCP using natural language without switching to the CRM interface", "Enable sales teams to create and update CRM records, enrich contact data and manage deal pipelines through conversational AI tools connected to NetHunt CRM via MCP", "Build AI-powered sales reporting workflows where agents analyze pipeline health, identify stalled negotiations and generate deal-level risk assessments using live NetHunt CRM data via MCP" ], "health": "active" }, { "id": "propellerads-mcp", "name": "PropellerAds MCP Connector", "description": "MCP connector from PropellerAds, the multi-format ad network, that lets advertisers manage campaigns directly through Claude, ChatGPT, Cursor and other AI agents. Supports all ad formats including Push, Popunder, Telegram Ads, Interactive Ads and Paid Social Traffic. Enables campaign creation, bid adjustments, performance monitoring, GEO and device targeting, and budget management through natural language. API token stored locally and never shared with AI providers. Launched July 24, 2026.", "category": "data", "endpoint": "https://propellerads.com", "homepage_url": "https://www.prnewswire.com/news-releases/propellerads-launches-mcp-connector-letting-advertisers-run-campaigns-through-ai-agents-302834104.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "advertising", "ad-network", "campaigns", "push-notifications", "popunder", "media-buying" ], "use_cases": [ "Manage PropellerAds campaigns across Push, Popunder, Telegram Ads and other formats through AI assistants connected via MCP without opening the dashboard", "Enable media buyers to pause underperforming campaigns, adjust bids and update GEO, device and browser targeting directly in chat through AI tools connected to PropellerAds via MCP", "Build AI-powered campaign optimization workflows where agents monitor ad performance, identify underperforming creatives and recommend budget reallocation using PropellerAds data via MCP" ], "health": "active" }, { "id": "propush-mcp", "name": "ProPush.me MCP Connector", "description": "MCP connector from ProPush.me, the push notification monetization platform, that lets publishers manage accounts, stats, zones and postbacks through Claude, ChatGPT and other AI agents. Runs as a remote server with no files to install. Supports OAuth authorization, account overview and balance checks, reporting with multi-dimensional filtering, zone and site management, and postback URL configuration. Announced July 30, 2026.", "category": "data", "endpoint": "https://propush.me", "homepage_url": "https://www.martechcube.com/propush-me-announced-the-launch-of-mcp-connector/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "push-notifications", "monetization", "publisher", "advertising", "analytics", "web-monetization" ], "use_cases": [ "Check ProPush.me account balances, earnings and API access levels through AI assistants connected via MCP without logging into the dashboard", "Enable publishers to filter and analyze monetization stats by date range, country, zone, site, OS and traffic direction through natural language queries in AI tools connected to ProPush.me via MCP", "Manage push notification zones, create new zones and configure postback URLs through conversational AI tools connected to ProPush.me via MCP" ], "health": "active" }, { "id": "dialmcp", "name": "DialMCP", "description": "Hosted MCP server from Datawizz Inc that lets AI agents place real phone calls on a user's behalf using the user's own verified phone number as caller ID. Includes mandatory AI disclosure, recorded transcripts and anti-spam limits. Designed for tasks like restaurant reservations, contractor quotes, medical appointments and small-business scheduling that remain phone-only. Works with Claude, Claude Code, ChatGPT and Cursor via remote MCP over OAuth. Launched July 29, 2026.", "category": "communication", "endpoint": "https://mcp.dialmcp.com/mcp", "homepage_url": "https://dialmcp.com/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "phone", "calling", "voice", "appointments", "reservations", "communication", "telephony" ], "use_cases": [ "Let AI agents place real phone calls for restaurant reservations, appointment scheduling and service inquiries using the user's own verified phone number through DialMCP via MCP", "Enable AI assistants to handle phone-only tasks like contractor quotes, hotel requests and medical scheduling by placing calls with mandatory AI disclosure and recorded transcripts via DialMCP", "Build AI-powered outreach workflows where agents make verified calls on behalf of users while enforcing anti-spam limits and permanent suppression lists through DialMCP via MCP" ], "health": "active" }, { "id": "firmable-mcp", "name": "Firmable MCP Server", "description": "MCP server from Firmable, the AI-native B2B sales platform, giving revenue teams direct access to Australian and global company and contact data from AI tools. Available through Firmable Connect. Enables AI assistants to search companies by size, revenue, technology stack and growth signals, access verified decision-maker contacts and enrich CRM records. Works with Claude, Claude Code, ChatGPT, Codex and Cursor. Launched July 29, 2026 alongside a 14 million dollar Series A.", "category": "data", "endpoint": "https://connect.firmable.ai", "homepage_url": "https://salestechstar.com/price-optimization-revenue-management/firmable-launches-mcp-giving-sales-teams-a-direct-line-from-any-ai-tool-to-verified-company-and-contact-data/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "b2b-data", "sales-intelligence", "contacts", "company-data", "australia", "lead-generation", "enrichment" ], "use_cases": [ "Search Firmable's B2B database for Australian and global companies by size, revenue, technology stack and growth signals through AI assistants connected via MCP without navigating the Firmable platform", "Enable sales teams to access verified decision-maker contacts and enrich CRM records with company intelligence through natural language queries in AI tools connected to Firmable via MCP", "Build AI-powered prospecting workflows where agents identify target companies matching ideal customer profiles, pull contact details and generate outreach lists using Firmable data via MCP" ], "health": "active" }, { "id": "thoughtspot-mcp", "name": "ThoughtSpot Agentic MCP Server", "description": "Agentic MCP server from ThoughtSpot, the analytics and business intelligence platform. First major analytics platform to launch an enterprise-ready agentic MCP server. Gives any AI agent trusted access to dynamically interpret user intent, invoke the ThoughtSpot Agentic Analytics Platform and deliver real-time insights from structured enterprise data. Supports Spotter 3 with advanced analytics, forecasting, multi-step reasoning and deep research. Works with Claude, Gemini and ChatGPT.", "category": "data", "endpoint": "https://developers.thoughtspot.com", "homepage_url": "https://www.thoughtspot.com/press-releases/thoughtspot-redefines-ai-interoperability-with-launch-of-thoughtspot-agentic-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "analytics", "business-intelligence", "data-visualization", "insights", "forecasting", "enterprise", "agentic" ], "use_cases": [ "Query structured enterprise data and discover insights through AI assistants connected to ThoughtSpot via MCP without writing SQL or navigating dashboards", "Enable business teams to perform advanced analytics, forecasting and multi-step reasoning on live data through natural language queries in AI tools connected to ThoughtSpot Spotter 3 via MCP", "Build AI-powered analytics workflows where agents dynamically interpret business questions, generate visualizations and deliver real-time insights from ThoughtSpot via MCP" ], "health": "active" }, { "id": "jasper-mcp", "name": "Jasper MCP Server", "description": "MCP server from Jasper, the enterprise AI marketing platform, that embeds Jasper IQ channel context, brand guardrails, institutional knowledge and performance best practices into every AI tool. Ensures AI-generated content remains consistent, high-quality and governed across departments regardless of the model in use. Works with ChatGPT, Claude, Microsoft Copilot and other MCP-compatible tools. External MCP Server support added March 2026.", "category": "productivity", "endpoint": "https://www.jasper.ai", "homepage_url": "https://www.jasper.ai/blog/march-2026-product-update", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "marketing", "content-generation", "brand-governance", "copywriting", "enterprise", "ai-content" ], "use_cases": [ "Generate on-brand marketing content through any AI assistant connected to Jasper via MCP with automatic enforcement of brand voice, style guidelines and compliance rules", "Enable marketing teams to scale AI content production across departments while maintaining consistent quality and governance through Jasper IQ brand intelligence embedded via MCP", "Build AI-powered content workflows where agents create campaigns, blog posts and ad copy with built-in brand guardrails and performance best practices using Jasper via MCP" ], "health": "active" }, { "id": "elastic-path-mcp", "name": "Elastic Path Developer MCP Server", "description": "Developer MCP server from Elastic Path, the composable commerce platform, enabling rapid scaffolding of storefront components and accelerating headless commerce development. Contains Elastic Path domain intelligence including catalog rules, price book logic, account hierarchy patterns and cart and checkout flows optimized for B2B buying. Generates product grids, authentication flows, cart management and checkout logic wired to Elastic Path APIs. Works with any MCP-aware IDE or coding agent.", "category": "code", "endpoint": "https://www.elasticpath.com", "homepage_url": "https://www.elasticpath.com/company/news", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-02", "updated": "2026-08-02", "tags": [ "ecommerce", "composable-commerce", "storefront", "b2b", "headless-commerce", "code-generation", "scaffolding" ], "use_cases": [ "Generate production-grade storefront components including product grids, cart management and checkout flows wired to Elastic Path APIs through AI coding agents connected via MCP", "Enable commerce developers to scaffold B2B buying experiences with embedded catalog rules, price book logic and account hierarchy patterns using Elastic Path domain intelligence via MCP", "Build AI-powered ecommerce development workflows where coding agents create, validate and deploy headless commerce components with Elastic Path best practices embedded via MCP" ], "health": "active" }, { "id": "rafay-systems-mcp", "name": "Rafay Systems MCP Server", "description": "Managed MCP server from Rafay Systems that gives platform, DevOps and SRE teams governed AI assistance for infrastructure operations without exporting data or building one-off integrations. Provides fleet intelligence, cost attribution, and incident diagnosis for Kubernetes environments managed through Rafay. Uses the same RBAC and project boundaries teams already have in place. Connects AI assistants to Rafay operational context through a standard protocol for cluster inventory, health status, workload placement and infrastructure cost analysis. Launched July 15, 2026.", "category": "code", "endpoint": "https://rafay.co", "homepage_url": "https://rafay.co/ai-and-cloud-native-blog/bring-rafay-into-your-ai-workflows-with-the-rafay-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-03", "updated": "2026-08-03", "tags": [ "kubernetes", "infrastructure", "devops", "sre", "fleet-management", "cost-attribution", "platform-engineering" ], "use_cases": [ "Inventory Kubernetes clusters across projects, summarize health and configuration status, and identify stale or underutilized environments through AI assistants connected to Rafay via MCP", "Enable platform engineers to correlate workload placement with node specifications and infrastructure cost using natural language queries in AI tools connected to Rafay via MCP", "Build AI-powered incident diagnosis workflows where agents access Rafay operational context with existing RBAC boundaries to troubleshoot Kubernetes environments via MCP" ], "health": "active" }, { "id": "symmetry-payroll-tax-mcp", "name": "Symmetry Tax Engine MCP Server", "description": "MCP server from Symmetry Software that puts the Symmetry Tax Engine directly into AI tools, giving payroll teams self-serve real-time access to deterministic payroll tax calculations. Read-only by design, runs on the same live STE tax tables used in production that calculate 64 million-plus employees paychecks annually. Reflects rate and rule changes the moment they land in STE. No developer required. Works with Claude, Cursor, ChatGPT and Google Anti-Gravity. Launched July 15, 2026.", "category": "data", "endpoint": "https://www.symmetry.com", "homepage_url": "https://www.symmetry.com/payroll-tax-insights/payroll-tax-insights-ste-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-03", "updated": "2026-08-03", "tags": [ "payroll", "tax", "compliance", "hr", "fintech", "calculations", "enterprise" ], "use_cases": [ "Query real-time payroll tax calculations using the same production tax tables that process 64 million-plus paychecks annually through AI assistants connected to the Symmetry Tax Engine via MCP", "Enable payroll teams to verify tax withholding rates, check state and local tax rules, and validate compliance scenarios through natural language queries in Claude and other AI tools connected to Symmetry via MCP", "Build AI-powered payroll compliance workflows where agents access deterministic tax calculations with automatic rate and rule updates from the Symmetry Tax Engine via MCP" ], "health": "active" }, { "id": "guideline-ad-intelligence-mcp", "name": "Guideline Ad Intelligence MCP Server", "description": "MCP server from Guideline, the advertising intelligence company, giving clients secure standards-based access to proprietary ad spend, pricing and market intelligence data from MCP-compatible AI applications. Authorized users ask questions in natural language, retrieve subscription-covered data and use it alongside approved internal information without exporting reports or building point-to-point integrations. Follows the earlier Media Plan Management MCP Server launched in March 2026. Works with Claude, ChatGPT, Gemini, Microsoft Copilot and proprietary agents. Launched July 27, 2026.", "category": "data", "endpoint": "https://www.guideline.com", "homepage_url": "https://www.prnewswire.com/news-releases/guideline-launches-its-ad-intelligence-mcp-server-to-power-ai-agents-with-its-leading-global-advertising-data-302832328.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-03", "updated": "2026-08-03", "tags": [ "advertising", "ad-intelligence", "media-planning", "market-data", "ad-spend", "analytics", "enterprise" ], "use_cases": [ "Query Guideline proprietary ad spend and market intelligence data through AI assistants connected via MCP without exporting reports or navigating the Guideline platform", "Enable media planners and buyers to access advertising pricing data, competitive spend analysis and market trends through natural language queries in Claude, ChatGPT and other AI tools connected to Guideline via MCP", "Build AI-powered media planning workflows where agents retrieve subscription-covered ad intelligence data and combine it with internal information for competitive analysis using Guideline via MCP" ], "health": "active" }, { "id": "inriver-pim-mcp", "name": "Inriver PIM MCP Server", "description": "MCP server from Inriver, the product information management platform, that gives AI tools standardized access to governed product data. Summer 2026 release adds enhanced MCP endpoints for AI ecosystem integration, an in-platform assistant for LLM-powered content enrichment at scale, orchestration features for content lifecycle management, and expanded automation for print and digital catalog production. Customers and partners use it as a rapid development foundation to build custom applications, workflow extensions and administrative tools on top of Inriver. Works with any MCP-compatible AI tool. Enhanced endpoints launched June 30, 2026.", "category": "data", "endpoint": "https://www.inriver.com", "homepage_url": "https://www.inriver.com/2026/03/inriver-advances-agentic-ai-product-information-management/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-03", "updated": "2026-08-03", "tags": [ "pim", "product-data", "ecommerce", "catalog", "content-enrichment", "product-management", "enterprise" ], "use_cases": [ "Access governed product information and catalog data through AI assistants connected to Inriver PIM via MCP for content enrichment, product descriptions and catalog management without manual data exports", "Enable commerce teams to enrich product content at scale using LLM-powered assistants connected to Inriver PIM via MCP with orchestration features for content lifecycle management", "Build custom applications and workflow extensions on top of Inriver PIM through the MCP server as a rapid development foundation for product data access and catalog automation" ], "health": "active" }, { "id": "seamless-ai-mcp", "name": "Seamless.AI MCP Server", "description": "MCP server from Seamless.AI, the real-time sales intelligence platform, connecting AI tools directly to Seamless prospecting and enrichment capabilities. Enables sales, revenue ops and marketing teams to find contacts, enrich CRM records, build targeted prospect lists and launch personalized outreach through natural language prompts in Claude, ChatGPT, Perplexity, Gemini and other MCP-compatible clients. Also integrates with workflow platforms including n8n, Gumloop and ActivePieces. Launched July 30, 2026.", "category": "data", "endpoint": "https://seamless.ai", "homepage_url": "https://seamless.ai/customers/blog/products/seamless-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "sales", "prospecting", "lead-generation", "crm-enrichment", "sales-intelligence", "b2b", "outreach" ], "use_cases": [ "Find verified contacts and decision-makers at target companies through AI assistants connected to Seamless.AI via MCP using natural language prompts without switching to the Seamless dashboard", "Enable revenue teams to enrich CRM records with real-time contact data, company firmographics and technographics by querying Seamless.AI through Claude, ChatGPT or other MCP-compatible tools", "Build AI-powered prospecting workflows where agents source leads, build targeted lists and generate personalized outreach sequences using Seamless.AI sales intelligence data via MCP" ], "health": "active" }, { "id": "kythera-clinical-semantic-mcp", "name": "Kythera Labs Clinical Semantic Bridge MCP", "description": "Healthcare MCP server from Kythera Labs available on the Databricks Marketplace that bridges clinical language and structured healthcare data. Enables AI agents to describe diseases, medications, procedures, lab tests, outcomes and eligibility criteria in plain language and automatically translates them into retrieval-ready code sets across ICD-10-CM, SNOMED CT, CPT, HCPCS, NDC, RxNorm and LOINC vocabularies. Supports cohort discovery, patient finding, clinical trial feasibility, commercial analytics, market access research and real-world evidence generation. Kythera received the 2026 Databricks ISV Innovation Built-On Partner of the Year Award. Launched July 7, 2026.", "category": "data", "endpoint": "https://www.kytheralabs.com", "homepage_url": "https://www.prnewswire.com/news-releases/kythera-labs-expands-partnership-with-databricks-launching-the-clinical-semantic-bridge-mcp-on-databricks-marketplace-302817357.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "healthcare", "clinical-data", "life-sciences", "medical-coding", "databricks", "clinical-trials", "real-world-evidence" ], "use_cases": [ "Describe diseases, medications and procedures in plain language and get retrieval-ready code sets across ICD-10-CM, SNOMED CT, CPT, RxNorm and LOINC through AI agents connected to Kythera Clinical Semantic Bridge via MCP on Databricks", "Enable life sciences teams to run clinical trial feasibility queries, cohort discovery and patient finding through natural language in AI tools connected to Kythera via MCP without writing SQL against medical code tables", "Build AI-powered real-world evidence generation workflows where agents translate clinical eligibility criteria into structured queries across multiple healthcare vocabularies using Kythera Clinical Semantic Bridge via MCP" ], "health": "active" }, { "id": "jetstream-verified-mcp", "name": "JetStream Verified MCP", "description": "MCP governance and verification platform from JetStream Security that helps enterprises safely adopt third-party MCP servers without unmanaged AI supply chain risk. Combines the JetStream Verified MCP catalog with the JetStream AI Hub to give security, risk and assurance teams one platform to verify server images, control agent permissions and govern runtime activity. Each verified image is produced through proprietary semantic scanning that analyzes data flows and code paths to identify risks such as credential leakage, unicode smuggling and obfuscated malware patterns. FedRAMP Class D High certified. Launched July 13, 2026.", "category": "infrastructure", "endpoint": "https://www.jetstreamsecurity.com", "homepage_url": "https://www.newswire.com/news/jetstream-launches-verified-mcp-governance-layer-for-enterprise-ai-22824752", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "security", "governance", "verification", "supply-chain", "enterprise", "fedramp", "compliance" ], "use_cases": [ "Verify third-party MCP server images before deployment using JetStream proprietary semantic scanning that identifies credential leakage, unicode smuggling and malware patterns in code paths and data flows", "Enable enterprise security teams to govern MCP and model traffic through a common control point with agent permission controls and runtime activity monitoring via JetStream AI Hub", "Build governed AI agent deployments where every MCP server is verified against supply chain risks before production use with FedRAMP High compliance via JetStream Verified MCP" ], "health": "active" }, { "id": "mescius-mcp", "name": "MESCIUS MCP Server", "description": "MCP server from MESCIUS USA (formerly GrapeCity) that gives AI coding agents direct access to trusted product knowledge for MESCIUS enterprise developer tools including SpreadJS, ActiveReports.NET and Document Solutions. Enables AI assistants to retrieve up-to-date documentation, APIs, best practices, sample code, CDN resources and implementation guidance through natural language queries. Instead of manually searching documentation, developers ask their AI coding assistant what they want to build and receive accurate, product-specific answers. Announced July 30, 2026.", "category": "code", "endpoint": "https://developer.mescius.com/mcp", "homepage_url": "https://developer.mescius.com/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "developer-tools", "documentation", "spreadsheet", "reporting", "enterprise", "javascript", "dotnet" ], "use_cases": [ "Query MESCIUS product documentation, APIs and best practices for SpreadJS, ActiveReports.NET and Document Solutions through AI coding assistants connected via MCP without searching docs manually", "Enable developers to get implementation guidance and sample code for MESCIUS enterprise components by describing what they want to build in natural language through Claude Code, Cursor or other MCP-compatible coding tools", "Build faster with MESCIUS developer tools by having AI agents retrieve CDN resources, API references and component configuration examples from the MESCIUS MCP server during active development" ], "health": "active" }, { "id": "jethost-mcp", "name": "JetHost AI Connector", "description": "MCP server from JetHost, the Bulgarian hosting provider, that lets customers manage hosting accounts through AI assistants. Connects hosting infrastructure directly to Claude, ChatGPT, Cursor, Lovable and other MCP-compatible tools through a unified MCP framework. Users can check domain renewals, deploy GitHub projects, spin up email accounts, monitor server resource usage and review support tickets through natural language. First Bulgarian hosting provider to offer MCP-based infrastructure management. Launched July 2026.", "category": "infrastructure", "endpoint": "https://jethost.com", "homepage_url": "https://hostingdiscussion.com/news/jethost-lets-customers-manage-hosting-through-ai-chat-assistants/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "hosting", "vps", "infrastructure", "devops", "domain-management", "server-management", "email" ], "use_cases": [ "Check domain renewal dates, server resource usage and support ticket status through AI assistants connected to JetHost via MCP without logging into the hosting dashboard", "Enable developers to deploy GitHub projects, spin up email accounts and configure hosting environments through natural language commands in Claude, ChatGPT or Cursor connected to JetHost via MCP", "Build automated hosting management workflows where AI agents monitor server health, manage domains and handle routine infrastructure tasks through the JetHost AI Connector via MCP" ], "health": "active" }, { "id": "hostafrica-mcp", "name": "HOSTAFRICA MCP Server", "description": "MCP server from HOSTAFRICA, the first hosting provider on the African continent to support MCP, giving developers direct control of VPS infrastructure from inside Claude, ChatGPT and other MCP-compatible AI tools. Covers the full VPS lifecycle including power management with start, stop, reboot and scheduled actions, backup creation and scheduling, firewall and port configuration, and threshold-based monitoring alerts. VPS instances run in tier three data centres in Johannesburg with nodes in Nairobi, Lagos and Accra. POPIA-compliant with local data residency for financial services, healthcare and government workloads. Launched July 2026.", "category": "infrastructure", "endpoint": "https://hostafrica.co.za/developers/connecting-via-mcp/", "homepage_url": "https://www.itweb.co.za/article/hostafrica-launches-africas-first-hosting-mcp-server-manage-your-vps-from-claude-and-chatgpt/JBwEr7n3zJYM6Db2", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "hosting", "vps", "africa", "infrastructure", "server-management", "devops", "cloud" ], "use_cases": [ "Manage VPS power state, create backups and configure firewall rules through AI assistants connected to HOSTAFRICA via MCP without using the hosting control panel", "Enable developers in Africa to control VPS infrastructure across Johannesburg, Nairobi, Lagos and Accra data centres through natural language in Claude or ChatGPT connected to HOSTAFRICA via MCP", "Build automated server monitoring and maintenance workflows where AI agents handle threshold-based alerts, scheduled reboots and backup creation for POPIA-compliant VPS environments through HOSTAFRICA via MCP" ], "health": "active" }, { "id": "microchip-mcp", "name": "Microchip Technology MCP Server", "description": "MCP server from Microchip Technology that provides AI-driven access to verified, up-to-date Microchip public product data including specifications, datasheets, inventory, pricing and lead times. Built on MCP streamable HTTP standards, delivers context-aware and JSON-encoded responses optimized for AI clients such as copilots, chatbots, LLM-based IDEs and enterprise AI agents. Publicly available at no cost with no authentication required. Supports a wide range of embedded systems applications across microcontrollers, FPGAs, analog, wireless and memory products. Announced November 2025.", "category": "data", "endpoint": "https://www.microchip.com/en-us/resources/model-context-protocol-server", "homepage_url": "https://www.microchip.com/en-us/about/news-releases/products/microchip-technology-unveils-model-context-protocol-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "semiconductor", "embedded-systems", "hardware", "microcontrollers", "datasheets", "product-data", "electronics" ], "use_cases": [ "Query Microchip product specifications, datasheets, inventory levels and pricing through AI assistants connected to the Microchip MCP server for hardware design decisions without navigating the product catalog manually", "Enable embedded engineers to find compatible microcontrollers, FPGAs and analog components by describing requirements in natural language through AI coding tools connected to Microchip via MCP", "Build hardware design workflows where AI agents retrieve verified component data, check availability and compare specifications across Microchip product families via MCP for bill-of-materials planning" ], "health": "active" }, { "id": "ssojet-mcp-auth", "name": "SSOJet MCP Auth Bridge", "description": "Enterprise SSO authentication bridge for MCP from SSOJet that enables B2B SaaS companies to make their products AI-agent ready while leveraging customers existing enterprise identity providers. Delivers a spec-compliant authorization server with MCP OAuth 2.1 compliance including mandatory PKCE and Resource Indicators, dynamic client registration, and pre-built integrations with Okta, Microsoft Entra ID, Google Workspace and OneLogin. Replaces 6-12 weeks of custom authentication engineering with a drop-in solution for MCP server authentication. Launched December 2025.", "category": "identity", "endpoint": "https://ssojet.com", "homepage_url": "https://www.einpresswire.com/article/874296056/ssojet-launches-enterprise-sso-bridge-for-mcp-enabling-b2b-saas-companies-to-deploy-ai-ready-authentication-in-days", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-04", "updated": "2026-08-04", "tags": [ "authentication", "sso", "oauth", "enterprise", "identity", "b2b-saas", "security" ], "use_cases": [ "Add MCP-compliant OAuth 2.1 authentication with PKCE and Resource Indicators to B2B SaaS products in days instead of months using SSOJet pre-built enterprise identity provider integrations", "Enable enterprise customers to connect AI agents to SaaS products using their existing Okta, Entra ID or Google Workspace SSO through SSOJet MCP Auth Bridge without custom authentication code", "Build governed MCP server deployments where AI agent authentication flows through enterprise identity infrastructure with dynamic client registration and full audit logging via SSOJet" ], "health": "active" }, { "id": "marginedge-mcp", "name": "MarginEdge MCP Connector", "description": "MCP connector from MarginEdge, the restaurant management and bill payment platform, that gives restaurant operators secure access to their operational data within AI platforms like ChatGPT, Claude and Gemini. Enables operators to ask questions in natural language, explore trends across locations and combine restaurant data with other connected business information. First MCP connector from a restaurant management and bill payment platform. Built on the open Model Context Protocol standard. Launched August 4, 2026.", "category": "data", "endpoint": "https://www.marginedge.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/04/3338368/0/en/MarginEdge-Launches-First-of-Its-Kind-MCP-Connector.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "restaurant", "food-service", "bill-payment", "operations", "hospitality", "analytics", "finance" ], "use_cases": [ "Query restaurant operational data including food costs, labor metrics and vendor spending through AI assistants connected to MarginEdge via MCP using natural language without logging into the MarginEdge dashboard", "Enable multi-location restaurant operators to explore trends, compare performance across sites and build custom reports by connecting MarginEdge data to Claude, ChatGPT or Gemini through the MCP connector", "Build AI-powered restaurant analytics workflows where agents combine MarginEdge bill payment, inventory and P&L data with other business information to surface patterns a single tool alone could not detect" ], "health": "active" }, { "id": "wrike-mcp", "name": "Wrike MCP Server", "description": "MCP server from Wrike, the enterprise work management platform, that enables third-party AI agents including Claude, Microsoft Copilot, Perplexity and custom assistants to securely access, analyze and act on live work management data. Users can search projects, create tasks, update records, manage workflows and generate insights through natural language. Supports OAuth authentication with no developer resources required. Since January 2026, MCP server connections have grown 16x. Enterprise adoption of Wrike AI has tripled year over year with users executing more than 5.5 million AI agent actions. Originally launched June 2025, major expansion July 2026.", "category": "productivity", "endpoint": "https://developers.wrike.com", "homepage_url": "https://www.wrike.com/newsroom/wrike-launches-mcp-server-empowering-third-party-ai-agents-with-real-time-work-management-intelligence/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "project-management", "work-management", "enterprise", "collaboration", "task-management", "workflow", "productivity" ], "use_cases": [ "Search projects, create tasks, update records and manage work items through AI assistants connected to Wrike via MCP using natural language without switching to the Wrike interface", "Enable enterprise teams to generate pipeline insights, receive smart task assignment suggestions and automate workflows by connecting Claude, Microsoft Copilot or Perplexity to live Wrike project data through MCP", "Build cross-platform work management workflows where AI agents create Teams messages, trigger automations and manage tasks across Wrike and connected tools through the Wrike MCP Server" ], "health": "active" }, { "id": "meltwater-mcp", "name": "Meltwater MCP Server", "description": "MCP server from Meltwater, the global media intelligence platform, that connects AI assistants like Claude and ChatGPT to real-time media, social and influencer intelligence. Processes 1.3 billion-plus documents daily. Teams can ask for breaking news overviews, brand health reports, trending social topics and media analysis in plain language with answers grounded in Meltwater's licensed data. Hosted MCP natively since June 2025. Major expansion with new action tools announced July 2026, allowing AI assistants to take action inside the Meltwater platform including creating reports and tracking alerts.", "category": "data", "endpoint": "https://www.meltwater.com", "homepage_url": "https://www.meltwater.com/en/press-releases/meltwater-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "media-intelligence", "social-media", "news-monitoring", "pr", "brand-monitoring", "influencer", "analytics" ], "use_cases": [ "Query breaking news coverage, brand mentions and media trends through AI assistants connected to Meltwater via MCP using natural language without logging into the Meltwater platform", "Enable PR and communications teams to generate brand health reports, track competitor coverage and monitor trending social topics by connecting Claude or ChatGPT to Meltwater's 1.3 billion daily document index through MCP", "Build media intelligence workflows where AI agents create alerts, compile coverage reports and analyze influencer activity inside Meltwater through the expanded MCP action tools" ], "health": "active" }, { "id": "rival-technologies-mcp", "name": "Rival Technologies MCP Server", "description": "MCP server from Rival Technologies, the conversational market research platform, that provides organizations a standardized two-way connection between proprietary research data with full context from the Rival platform and enterprise AI applications. Enables brands with agentic workflows to connect research intelligence, consumer insights and survey data directly to AI tools. Also launched the Emerging Consumer Index, a syndicated intelligence offering tracking emerging affluent Gen Z and Millennial consumers across the US and Canada with new data collected every two weeks. Announced July 27, 2026.", "category": "data", "endpoint": "https://www.rivaltech.com", "homepage_url": "https://www.prnewswire.com/news-releases/rival-technologies-announces-mcp-and-first-syndicated-intelligence-offering-302834569.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "market-research", "consumer-insights", "survey", "research", "analytics", "gen-z", "syndicated-data" ], "use_cases": [ "Connect proprietary consumer research data from the Rival platform to enterprise AI applications through MCP for real-time insight querying and analysis without manual data exports", "Enable insights teams to query survey results, consumer sentiment and research findings through AI assistants connected to Rival Technologies via MCP using natural language", "Build agentic market research workflows where AI agents access the Emerging Consumer Index and proprietary research intelligence from Rival to inform brand strategy, product development and marketing decisions" ], "health": "active" }, { "id": "cotality-mcp", "name": "Cotality MCP Server", "description": "MCP server from Cotality, the global property information and analytics provider formerly known as CoreLogic, that acts as a universal connector for AI to access trusted property intelligence. AI-ready data serves as a translator for AI models to understand the meaning behind property values while the MCP server connects AI systems to precise property and location insights in real time. Designed for production-grade workflows including underwriting, valuation and risk analysis. Addresses the challenge of property data being historically fragmented and non-standardized which leads AI models to hallucinate. Launched March 31, 2026.", "category": "data", "endpoint": "https://www.cotality.com", "homepage_url": "https://www.cotality.com/press-releases/cotality-launches-a-universal-ai-connector-mcp-server-and-ai-ready-property-intelligence", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "real-estate", "property-data", "valuation", "underwriting", "risk-analysis", "analytics", "location-intelligence" ], "use_cases": [ "Query real-time property valuations, location insights and market data through AI agents connected to Cotality via MCP for underwriting and risk analysis workflows without manual data lookups", "Enable mortgage lenders and real estate professionals to access structured property intelligence including comparable sales, ownership records and neighborhood analytics through AI tools connected to Cotality via MCP", "Build production-grade property valuation and risk assessment workflows where AI agents retrieve trusted Cotality data through MCP to reduce hallucination and improve accuracy in automated underwriting decisions" ], "health": "active" }, { "id": "nitro-mcp", "name": "Nitro MCP Connector", "description": "MCP connector from Nitro Software that integrates the Nitro document engine with Claude AI, enabling users to execute complex document workflows through single prompts. Handles tasks including data entry, information extraction and agreement processing. According to Nitro's 2026 Enterprise AI Report, 75 to 95 percent of enterprise employees now use AI for document tasks with 89 percent reporting time savings of nine-plus hours weekly. Precedes Nitro Automate, an intelligent document automation solution launching soon. Available at gonitro.com. Launched May 2026.", "category": "productivity", "endpoint": "https://www.gonitro.com/automate/mcp", "homepage_url": "https://www.gonitro.com/about/press/nitro-releases-mcp-connector-for-claude-ai-introduces-document-automation-solution", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "document-management", "pdf", "document-automation", "enterprise", "data-extraction", "productivity", "esignature" ], "use_cases": [ "Execute complex document workflows including data entry, information extraction and agreement processing through single prompts in Claude connected to the Nitro document engine via MCP", "Enable enterprise teams to automate PDF processing, contract review and document generation by connecting Claude to Nitro's document automation capabilities through the MCP connector", "Build AI-powered document pipelines where agents extract structured data from agreements, populate forms and process documents at scale through the Nitro MCP connector without manual document handling" ], "health": "active" }, { "id": "tenable-hexa-mcp", "name": "Tenable Hexa AI MCP Server", "description": "MCP server from Tenable that exposes 90 structured tools from Tenable's Exposure Data Fabric to any MCP-compatible AI client. Provides a single Tenable-hosted HTTPS endpoint compatible with Claude Desktop, Claude Code, Cursor and any client supporting MCP over HTTP. Enables security teams to build custom agents for unique security workflows while keeping data governed through Tenable's Exposure Data Fabric. Organizations bring their own LLM while Tenable provides ground truth data. Also launched the CyberAgents Exchange, the first open-source cybersecurity-native registry for AI agents, skills, MCP servers and multi-agent playbooks. Announced August 4, 2026 at Black Hat USA.", "category": "infrastructure", "endpoint": "https://cloud.tenable.com/mcp/", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/04/3338369/0/en/Tenable-Advances-Exposure-Management-with-Coverage-Across-Every-Major-AI-Platform-and-Developer-Tool.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "security", "vulnerability-management", "exposure-management", "cybersecurity", "compliance", "enterprise", "threat-intelligence" ], "use_cases": [ "Build custom cybersecurity agents that query Tenable's Exposure Data Fabric through 90 structured MCP tools to automate vulnerability management, asset discovery and exposure analysis workflows", "Enable security teams to bring their own LLM and reason over Tenable vulnerability and exposure data through Claude Desktop, Claude Code or Cursor connected to the Tenable Hexa AI MCP server without local install or proxy infrastructure", "Create multi-agent cybersecurity playbooks using the CyberAgents Exchange and Tenable MCP server to orchestrate threat detection, risk prioritization and remediation workflows across enterprise environments" ], "health": "active" }, { "id": "digits-mcp", "name": "Digits MCP Server", "description": "MCP server from Digits, the AI-native accounting platform, that gives accounting firms, business owners and finance teams direct access to financial data inside AI tools like Claude, ChatGPT and Cursor. Digits processes transactions in real time with 95-percent-plus auto-booking accuracy and structures every vendor, category, dimension and customer as a discrete object with stable identity. AI tools querying Digits work with clean, current, structured data from the start. All access is read-only by design to preserve ledger integrity. Free on all plans with no restrictions and no developer experience required for setup. Launched April 21, 2026.", "category": "data", "endpoint": "https://www.digits.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/04/21/3278035/0/en/digits-launches-mcp-server-connecting-ai-tools-directly-to-its-real-time-ai-native-ledger.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-05", "updated": "2026-08-05", "tags": [ "accounting", "finance", "bookkeeping", "ledger", "ai-native", "small-business", "fintech" ], "use_cases": [ "Query real-time financial data including transactions, vendor spending and P&L breakdowns through AI assistants connected to the Digits MCP server without switching to the accounting dashboard", "Enable accounting firms to analyze client books, identify anomalies and generate financial insights by connecting Claude, ChatGPT or Cursor to clean structured ledger data from Digits via MCP", "Build AI-powered financial analysis workflows where agents query the Digits AI-native ledger through MCP with 95-percent-plus auto-booked transactions and stable entity identities for reliable downstream reasoning" ], "health": "active" }, { "id": "tanium-atlas-mcp", "name": "Tanium Atlas MCP Server", "description": "MCP server from Tanium that exposes governed endpoint data and actions from the Tanium Autonomous IT Platform to MCP-compatible AI clients including Claude, ChatGPT and Microsoft Security Copilot. Security and IT teams can query real-time endpoint intelligence, investigate assets and take remediation actions without leaving their AI workflow. All interactions remain subject to access controls defined within Tanium Atlas. Part of Tanium's broader autonomous security initiative spanning agentic AI, exposure management and security operations. Announced at Black Hat USA August 3, 2026.", "category": "infrastructure", "endpoint": "https://www.tanium.com", "homepage_url": "https://www.tanium.com/blog/bringing-tanium-s-real-time-endpoint-intelligence-into-enterprise-ai-workflows-with-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-06", "updated": "2026-08-06", "tags": [ "security", "endpoint-management", "cybersecurity", "it-operations", "asset-management", "threat-detection", "enterprise" ], "use_cases": [ "Query real-time endpoint data including device inventory, patch status and security posture through AI assistants connected to the Tanium Atlas MCP server without navigating the Tanium dashboard", "Enable security analysts to investigate incidents and identify affected assets by asking natural language questions about endpoint state, software inventory and configuration compliance through Claude or ChatGPT connected to Tanium via MCP", "Build autonomous security operations workflows where AI agents query Tanium endpoint intelligence, correlate exposure data and execute remediation actions through the Atlas MCP server with governed access controls" ], "health": "active" }, { "id": "intel-471-mcp", "name": "Intel 471 MCP471", "description": "MCP server from Intel 471 that connects the Verity471 cyber intelligence platform to AI environments including Claude, ChatGPT and custom agent harnesses. MCP471 exposes underground intelligence across three modes: Intelligence for adversary HUMINT and finished intelligence, Exposure for compromised credentials and vulnerability data, and Hunt for real-time malware indicators. AI agents can resolve actor aliases, pivot across sources and retrieve decision-grade threat intelligence. Pairs with Agent471, a native AI agent inside Verity471 that reasons across intelligence like a human analyst. Announced July 28, 2026.", "category": "infrastructure", "endpoint": "https://www.intel471.com", "homepage_url": "https://www.intel471.com/blog/introducing-mcp471-and-agent471-bringing-intelligence-into-the-ai-workflows-analysts-use", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-06", "updated": "2026-08-06", "tags": [ "threat-intelligence", "cybersecurity", "underground-intelligence", "vulnerability", "malware", "credential-monitoring", "security" ], "use_cases": [ "Query underground threat intelligence including adversary profiles, compromised credential sets and malware indicators through AI assistants connected to Intel 471 Verity471 via MCP471 without switching to the Verity471 dashboard", "Enable threat analysts to resolve actor aliases and pivot across intelligence sources by asking natural language questions about threat actors, campaigns and indicators of compromise through Claude or ChatGPT connected to MCP471", "Build agentic threat hunting workflows where AI agents query Intel 471 underground intelligence, correlate vulnerability data and generate decision-ready threat assessments using MCP471 across the Intelligence, Exposure and Hunt modes" ], "health": "active" }, { "id": "helium10-mcp", "name": "Helium 10 MCP", "description": "MCP connector from Helium 10 that links the Amazon seller intelligence platform directly to AI assistants including Claude, ChatGPT and Cursor. Sellers can query live product, keyword, competitor and advertising data through natural language instead of navigating separate dashboards. Supports streamable HTTP transport with OAuth authentication. Available to Diamond plan subscribers. Endpoint at mcp.helium10.com. Launched July 16, 2026.", "category": "data", "endpoint": "https://mcp.helium10.com/mcp", "homepage_url": "https://www.helium10.com/tools/mcp/", "github_url": "https://github.com/helium10/Helium10-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-06", "updated": "2026-08-06", "tags": [ "amazon", "ecommerce", "seller-tools", "keyword-research", "product-research", "advertising", "competitive-intelligence" ], "use_cases": [ "Query live Amazon product data, keyword rankings and competitor metrics through AI assistants connected to Helium 10 via MCP using natural language without navigating multiple Helium 10 dashboards", "Enable Amazon sellers to analyze advertising performance, identify profitable keywords and research competitor listings by connecting Claude or ChatGPT to Helium 10 product intelligence via MCP", "Build AI-powered Amazon selling workflows where agents retrieve real-time keyword data, track product rankings and surface competitive insights from Helium 10 through MCP for data-driven listing optimization" ], "health": "active" }, { "id": "idrive-e2-mcp", "name": "IDrive e2 MCP Server", "description": "MCP server from IDrive that enables AI assistants, coding agents and MCP-compatible applications to securely access and interact with data stored in IDrive e2 S3-compatible cloud object storage buckets using natural language commands. Supports OAuth authentication eliminating the need to expose long-term access keys. Provides granular access controls for organizations to determine what AI applications can access. Compatible with Claude, Cursor, ChatGPT, Grok, Codex and other MCP clients. Announced July 30, 2026.", "category": "infrastructure", "endpoint": "https://www.idrive.com/s3-storage-e2/", "homepage_url": "https://www.prnewswire.com/news-releases/idrive-e2-launches-mcp-support-for-secure-ai-access-to-cloud-object-storage-302839388.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-06", "updated": "2026-08-06", "tags": [ "cloud-storage", "object-storage", "s3-compatible", "file-management", "infrastructure", "data-access", "developer-tools" ], "use_cases": [ "Retrieve, organize, upload and manage content in IDrive e2 cloud storage buckets through AI assistants connected via MCP using natural language commands without building custom integrations", "Enable development teams to access project files, datasets and assets stored in S3-compatible IDrive e2 buckets directly from Claude, Cursor or other AI coding tools via MCP with OAuth-secured authentication", "Build AI-powered data pipelines where agents read and write to IDrive e2 object storage through MCP with granular access controls governing what each AI application can access and manage" ], "health": "active" }, { "id": "seamlessai-mcp", "name": "Seamless.AI MCP Server", "description": "MCP server from Seamless.AI that connects real-time sales intelligence data to AI assistants including Claude, ChatGPT, Cursor, Perplexity, Gemini and automation platforms like n8n, Gumloop and ActivePieces. Sales, revenue ops and marketing teams can find prospects, enrich records, launch hyper-personalized campaigns and book meetings through natural language prompts. One-click setup through Settings with no API keys or code required. Endpoint accessible via standard MCP connection. Announced July 30, 2026.", "category": "data", "endpoint": "https://seamless.ai", "homepage_url": "https://www.prweb.com/releases/seamlessais-new-mcp-server-takes-you-from-prompt-to-closed-won-deal-302839077.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-06", "updated": "2026-08-06", "tags": [ "sales-intelligence", "prospecting", "lead-generation", "b2b-data", "contact-enrichment", "sales", "crm" ], "use_cases": [ "Find decision-makers at target accounts, enrich missing contact data and build prospect lists through AI assistants connected to Seamless.AI via MCP using natural language prompts", "Enable sales teams to turn simple prompts into automated prospecting, record enrichment and personalized outreach workflows by connecting Claude, ChatGPT or Perplexity to Seamless.AI sales intelligence via MCP", "Build AI-powered revenue operations pipelines where agents query Seamless.AI for verified B2B contact data, enrich CRM records and generate hyper-personalized campaign sequences via MCP" ], "health": "active" }, { "id": "datasette-mcp", "name": "datasette-mcp", "description": "MCP server by Simon Willison that exposes Datasette databases to AI assistants through read-only SQL queries. Built for the stateless MCP 2026-07-28 specification. Provides three tools: list_databases to enumerate available databases, get_database_schema to inspect table structures, and execute_sql to run read-only SQL queries against any connected Datasette instance. Installable via uvx or pip. Open source. Released July 31, 2026.", "category": "data", "endpoint": "https://datasette.simonwillison.net/-/mcp", "homepage_url": "https://simonwillison.net/2026/Jul/31/stateless-mcp/", "github_url": "https://github.com/simonw/datasette-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "uvx datasette-mcp", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "database", "sql", "datasette", "data-exploration", "open-source", "python", "stateless-mcp" ], "use_cases": [ "Query Datasette databases through AI assistants using natural language that gets translated to read-only SQL against any connected Datasette instance via MCP", "Enable data analysts to explore database schemas and run ad hoc queries from Claude, ChatGPT or other MCP clients connected to a datasette-mcp endpoint without switching to a separate database tool", "Build AI-powered data exploration workflows where agents list databases, inspect schemas and execute SQL queries through datasette-mcp with read-only access controls" ], "health": "active" }, { "id": "haystack-intranet-mcp", "name": "Haystack Intranet MCP Server", "description": "MCP server from Haystack, the AI-native intranet platform, that connects company knowledge directly to AI assistants. The first MCP server in the intranet space. Employees get answers from their company single source of truth inside Claude with responses that are current, approved, permission-aware and linked back to the source page in Haystack. Write support planned as a follow-up. Announced August 6, 2026.", "category": "productivity", "endpoint": "https://www.haystackhq.com", "homepage_url": "http://www.prnewswire.com/news-releases/haystack-launches-the-intranet-industrys-first-model-context-protocol-mcp-server-302844392.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "intranet", "knowledge-management", "employee-experience", "enterprise", "company-wiki", "internal-communications" ], "use_cases": [ "Query company intranet content through AI assistants connected to Haystack via MCP to get permission-aware answers sourced from the organization single source of truth", "Enable employees to ask natural language questions about company policies, procedures and announcements through Claude or other MCP clients connected to Haystack without searching the intranet manually", "Build AI-assisted knowledge workflows where agents retrieve current, approved intranet content from Haystack via MCP with source attribution linking back to the original Haystack page" ], "health": "active" }, { "id": "delight-ai-mcp", "name": "Delight.ai Agent MCP", "description": "MCP server from Delight.ai that gives AI assistants secure access to live customer service data from the Delight.ai workspace using natural language. Teams can ask questions like why customer satisfaction dropped this week and get answers from live operational data. Standards-based integration supports Claude, Codex, Cursor and other MCP-compatible clients. Developed using internal workflows before general availability. By Sendbird. Announced August 5, 2026.", "category": "data", "endpoint": "https://delight.ai", "homepage_url": "https://www.prnewswire.com/news-releases/delightai-launches-delight-agent-mcp-for-ai-assistant-access-to-live-customer-service-data-302843631.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "customer-service", "customer-experience", "analytics", "support", "satisfaction", "cx-data", "sendbird" ], "use_cases": [ "Query live customer service metrics and satisfaction data through AI assistants connected to Delight.ai via MCP to diagnose trends and identify issues without exporting reports", "Enable support managers to ask natural language questions about customer experience data including satisfaction scores and service quality metrics through Claude or Cursor connected to Delight.ai via MCP", "Build AI-powered customer intelligence workflows where agents query live Delight.ai operational data to surface satisfaction trends, identify at-risk accounts and generate actionable CX insights" ], "health": "active" }, { "id": "tidal-cyber-mcp", "name": "Tidal Cyber MCP Server", "description": "MCP server from Tidal Cyber that extends the Threat-Led Defense platform into AI assistants and agentic workflows. Provides a secure governed connectivity layer between threat intelligence and approved AI tools. Security teams can explore defensive coverage, assess organizational readiness, prioritize engineering work, evaluate threat exposure and generate leadership-ready summaries using trusted threat intelligence. Supports Claude, ChatGPT, Microsoft Copilot and custom agents. Announced August 4, 2026.", "category": "infrastructure", "endpoint": "https://www.tidalcyber.com", "homepage_url": "http://www.prnewswire.com/news-releases/tidal-cyber-brings-threat-led-defense-to-the-ai-tools-your-teams-already-use-302842835.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "cybersecurity", "threat-intelligence", "threat-defense", "security-operations", "mitre-attack", "risk-assessment", "enterprise" ], "use_cases": [ "Query threat intelligence and defensive coverage data through AI assistants connected to Tidal Cyber via MCP to assess organizational readiness and prioritize security engineering work", "Enable security analysts to evaluate threat exposure and generate leadership-ready summaries by connecting Claude, ChatGPT or Copilot to the Tidal Cyber Threat-Led Defense platform via MCP", "Build agentic security workflows where AI agents query Tidal Cyber threat intelligence to correlate defensive gaps, map attack techniques and produce actionable risk assessments through MCP" ], "health": "active" }, { "id": "sedai-mcp", "name": "Sedai MCP Server", "description": "MCP integration from Sedai that extends cloud and AI infrastructure optimization capabilities to external AI assistants and agentic workflows. Pairs with Sed, the conversational AI assistant built into the Sedai platform. Users can query cloud costs, identify savings opportunities, review optimization actions and take infrastructure actions through Claude Code, Microsoft Copilot or custom internal agents. Same capabilities available conversationally inside Sedai are available via MCP. Announced August 6, 2026.", "category": "infrastructure", "endpoint": "https://sedai.io", "homepage_url": "https://www.prnewswire.com/news-releases/sedai-launches-sed-the-ai-assistant-for-cloud-and-agent-optimization-302844619.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "cloud-optimization", "cost-management", "infrastructure", "devops", "ai-operations", "finops", "observability" ], "use_cases": [ "Query cloud infrastructure costs and identify savings opportunities through AI assistants connected to Sedai via MCP without switching to the Sedai dashboard", "Enable DevOps and platform teams to ask natural language questions about cloud spend, resource utilization and optimization actions through Claude Code or Copilot connected to Sedai via MCP", "Build AI-powered cloud management workflows where agents query Sedai for cost analysis, review autonomous optimization actions and take infrastructure actions through MCP" ], "health": "active" }, { "id": "perk-mcp", "name": "Perk MCP Connector", "description": "MCP connector from Perk, formerly TravelPerk, the AI-native travel and spend management platform. The first platform to connect travel, spend, invoicing and events through a single MCP integration. Finance teams, travel managers and employees can link Perk to Claude, ChatGPT and other MCP-compatible assistants to check trip bookings, identify unpaid invoices and track event RSVPs using natural language. Eliminates shadow work by meeting teams inside the AI tools they already use. Announced July 13, 2026.", "category": "productivity", "endpoint": "https://www.perk.com", "homepage_url": "https://www.perk.com/press-release/perk-mcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "travel-management", "expense-management", "invoicing", "events", "corporate-travel", "finance", "spend-management" ], "use_cases": [ "Query travel bookings, expense reports and invoice status through AI assistants connected to Perk via MCP using natural language without switching to the Perk dashboard", "Enable finance teams and travel managers to check trip details, identify unpaid invoices and track event RSVPs by connecting Claude or ChatGPT to Perk travel and spend data via MCP", "Build AI-powered corporate travel workflows where agents query Perk for booking data, expense status and event logistics through MCP to reduce manual report searches and platform switching" ], "health": "active" }, { "id": "skyvia-mcp", "name": "Skyvia MCP Server", "description": "MCP server from Skyvia that gives AI assistants controlled real-time access to business data across 200 plus data sources including Salesforce, HubSpot, PostgreSQL, Google Sheets and more. Users connect sources in a visual wizard, optionally configure IP allowlists and user authentication, then link the endpoint to any MCP-compatible AI client. Supports both read and write operations including adding CRM records and creating follow-up tasks. No code or API management required. Generally available.", "category": "data", "endpoint": "https://skyvia.com", "homepage_url": "https://www.newsfilecorp.com/release/268187/Skyvia-Introduces-MCP-Server-A-Service-that-Enables-AI-Assistants-to-Work-with-Live-Business-Data", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "data-integration", "crm", "business-data", "no-code", "salesforce", "hubspot", "multi-source" ], "use_cases": [ "Query live business data across CRM, ERP and database systems through AI assistants connected to Skyvia via MCP using natural language without building custom API integrations", "Enable analysts and operations teams to generate on-demand reports and insights across Salesforce, HubSpot, PostgreSQL and 200 plus data sources by connecting Claude or ChatGPT to Skyvia via MCP", "Build AI-powered business workflows where agents read and write to multiple data sources through Skyvia MCP to add CRM records, create follow-up tasks and surface cross-system insights" ], "health": "active" }, { "id": "tenable-cyberagents-mcp", "name": "Tenable CyberAgents Exchange", "description": "Open-source cybersecurity-native registry from Tenable for AI agents, skills, MCP servers and multi-agent playbooks. The only purpose-built security agent exchange in the market. Launches with over 50 AI components under open-source licenses including agents, skill files and MCP servers for vulnerability management, threat intelligence and security operations. Includes contributions from SentinelOne, Recorded Future, Wiz and others. Hosted at exchange.tenable.com. Launched at Black Hat USA 2026 with AWS and Anthropic support. Announced August 4, 2026.", "category": "infrastructure", "endpoint": "https://exchange.tenable.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/04/3338396/0/en/Tenable-Launches-Industry-s-First-Open-Source-AI-Agent-Exchange-to-Advance-Collective-Cyber-Innovation-and-Defense.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-07", "updated": "2026-08-07", "tags": [ "cybersecurity", "open-source", "agent-registry", "vulnerability-management", "threat-intelligence", "security-operations", "multi-agent" ], "use_cases": [ "Browse and deploy pre-built cybersecurity AI agents, MCP servers and skill files from the CyberAgents Exchange to automate vulnerability management and threat hunting workflows", "Enable security teams to share and collaborate on open-source security agents and MCP servers through the CyberAgents Exchange instead of building AI security tooling in isolation", "Build multi-agent security playbooks that combine agents and MCP servers from Tenable, SentinelOne, Recorded Future and other contributors in the CyberAgents Exchange for coordinated cyber defense" ], "health": "active" }, { "id": "mapquest-mcp", "name": "MapQuest MCP Server", "description": "Hosted MCP server from MapQuest that gives AI agents direct access to the MapQuest location platform including geocoding, routing and mapping. Any MCP-compatible agent including Claude, Cursor and Codex can discover MapQuest mapping tools automatically and start calling them. An agent can geocode an address, plan a multi-stop route or build a location-aware route planning app in minutes. MapQuest is offering 1 billion free transactions to developers who build on the MCP server. Announced August 5, 2026.", "category": "data", "endpoint": "https://www.mapquest.com/mcp", "homepage_url": "https://lasvegassun.com/news/2026/aug/05/mapquest-opens-its-mapping-platform-to-ai-agents-w/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "geolocation", "mapping", "geocoding", "routing", "location", "navigation", "maps" ], "use_cases": [ "Geocode addresses, plan multi-stop routes and build location-aware applications through AI agents connected to the MapQuest MCP server without custom integration work", "Enable AI coding assistants like Claude Code or Cursor to add location intelligence to applications by calling MapQuest geocoding and routing tools directly through MCP", "Build AI-powered logistics and delivery workflows where agents plan optimized routes, resolve addresses and generate mapping data through the MapQuest MCP server" ], "health": "active" }, { "id": "eztexting-mcp", "name": "EZ Texting MCP Server", "description": "MCP server from EZ Texting, the SMS marketing platform trusted by more than 230000 customers, that lets businesses manage text messaging campaigns directly through AI assistants like ChatGPT and Claude using natural language commands. Instead of logging into a dashboard a business owner can tell an AI assistant to send a broadcast, check campaign performance or look up a contact. Every request is processed through existing infrastructure so current permissions, compliance policies and account controls remain unchanged. First discoverable SMB and mid-market SMS platform in the AI ecosystem. Listed on the official MCP Registry. Announced August 4, 2026.", "category": "productivity", "endpoint": "https://mcp.eztexting.com", "homepage_url": "http://www.prnewswire.com/news-releases/ez-texting-launches-ai-assistants-for-sms-marketing-send-texts-run-campaigns-using-chatgpt-claude-or-any-famous-ai-tool-302842800.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "sms", "marketing", "text-messaging", "campaigns", "smb", "communications", "broadcasts" ], "use_cases": [ "Send SMS broadcasts, check campaign performance and manage contacts through AI assistants connected to EZ Texting via MCP using natural language instead of logging into the dashboard", "Enable small and mid-sized businesses to chain SMS actions with other AI-connected tools like Shopify, HubSpot and Google Sheets through EZ Texting MCP for multi-step marketing workflows", "Build AI-powered SMS marketing automation where agents schedule broadcasts, segment audiences and report on delivery metrics through the EZ Texting MCP server" ], "health": "active" }, { "id": "rubrik-agent-cloud-mcp", "name": "Rubrik Agent Cloud MCP Gateway", "description": "MCP Gateway from Rubrik that acts as a central security checkpoint for all API and MCP resources within an organization. Part of the Rubrik Agent Cloud platform unveiled at Black Hat USA 2026. Every MCP tool call must pass through three checks before execution: SAGE semantic assessment, runtime security policy verification and agent session authentication with short-lived tokens. Integrates with Okta and Microsoft Entra ID to extend existing enterprise identities to autonomous machine agents. Supports On-Behalf-Of federation to restrict access to specific MCP servers and tools on a per-user and per-group basis. Announced August 4, 2026.", "category": "infrastructure", "endpoint": "https://www.rubrik.com/products/rubrik-agent-cloud", "homepage_url": "https://siliconangle.com/2026/08/04/rubrik-unveils-agent-identity-govern-ai-agents-one-tool-call-time/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "security", "governance", "identity", "mcp-gateway", "agent-security", "zero-trust", "enterprise", "compliance" ], "use_cases": [ "Govern AI agent access to MCP servers and tools through the Rubrik MCP Gateway which enforces semantic analysis, runtime policies and per-call authentication before any tool execution", "Enable enterprises to extend existing Okta or Entra ID identities to autonomous AI agents through On-Behalf-Of federation and restrict MCP server access on a per-user and per-group basis", "Build auditable agent workflows where every MCP tool call is logged, authenticated with short-lived tokens and evaluated against runtime security policies through the Rubrik Agent Cloud platform" ], "health": "active" }, { "id": "ncino-mortgage-mcp", "name": "nCino Mortgage MCP", "description": "MCP server from nCino, the platform for agentic AI banking, that lets lenders connect MCP-compatible AI agents directly to the nCino Mortgage Suite. Includes two pre-built tools: Admin MCP for onboarding loan officers, managing licenses, restructuring branches and compliance tasks through natural language, and Loan Officer MCP for checking loan status, managing pipeline, updating borrower records and triggering income and asset verifications. Every action is logged with timestamp, action and outcome within nCino. Supports configurable controls for high-impact actions including human confirmation requirements. Announced August 7, 2026.", "category": "productivity", "endpoint": "https://www.ncino.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/07/3341039/0/en/ncino-releases-mortgage-mcp-letting-lenders-connect-ai-agents-directly-to-the-ncino-mortgage-suite.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "mortgage", "banking", "lending", "fintech", "loan-management", "compliance", "financial-services" ], "use_cases": [ "Enable mortgage administrators to onboard loan officers, assign licenses, restructure branches and run compliance tasks through AI agents connected to the nCino Mortgage Suite via MCP using natural language", "Allow loan officers to check loan status, manage their pipeline, update borrower records and trigger income and asset verifications through AI assistants connected to nCino via MCP without switching between systems", "Build auditable mortgage workflows where AI agents carry out tasks within the lender existing governance and permission settings with every action logged in nCino including timestamp and outcome" ], "health": "active" }, { "id": "menlo-mars-mcp", "name": "Menlo Agent Runtime Security (MARS) MCP", "description": "MCP integration from Menlo Security that connects agentic systems to secured browser sessions running in disposable containers within the Menlo Cloud. Provides air-gapped security, filtering, auditing and containment for AI agents that access the web. Neutralizes prompt injection by stripping malicious instructions from HTML before they reach an agent. Prevents data exfiltration by masking PII and sensitive IP at the source. Bridges the API Gap by connecting agents to legacy ERP and CRM systems using a managed abstraction layer. Secures browser assistants like Microsoft Copilot, coding agents like Claude Code and autonomous agents. Expanded at Black Hat USA August 5, 2026.", "category": "infrastructure", "endpoint": "https://www.menlosecurity.com/product/ai-agent-security", "homepage_url": "https://www.menlosecurity.com/press-releases/menlo-security-extends-mars-to-secure-ai-assistants-and-coding-agents-like-microsoft-copilot-gemini-in-chrome-and-claude-code-against-prompt-injection-and-data-exfiltration", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "security", "browser-security", "agent-security", "prompt-injection", "data-exfiltration", "enterprise", "ai-governance" ], "use_cases": [ "Connect AI agents to secured browser sessions via MCP integration so they can access web content through Menlo disposable cloud containers that strip prompt injection attacks before content reaches the agent", "Enable enterprises to deploy Claude Code, Copilot and autonomous agents with runtime web access protection that masks PII and blocks data exfiltration at the browser layer through Menlo MARS MCP", "Bridge AI agents to legacy ERP and CRM systems through Menlo managed abstraction layer via MCP so agents can interact with web-based enterprise apps inside sandboxed, air-gapped browser sessions" ], "health": "active" }, { "id": "cyera-mcp", "name": "Cyera MCP", "description": "MCP server from Cyera that connects data and AI security insights from the Cyera platform directly into AI assistants and agents including Microsoft Copilot, Claude Code and Cursor. Security teams can accelerate investigations and threat hunting through plain language queries against Cyera DataPort. Enterprises can build their own security agents on top of the platform to address data security risks at scale. Part of the Cyera AI Security Platform alongside Browser Shield and Data Lineage. Agent Guardian expansion at Black Hat USA 2026 adds discovery of shadow agents and MCP activity across endpoints, SaaS and cloud. Released March 2026.", "category": "infrastructure", "endpoint": "https://www.cyera.com/platform/agent-guardian", "homepage_url": "https://www.businesswire.com/news/home/20260324283752/en/Cyera-Closes-Major-Gaps-in-Securing-Enterprise-AI", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "data-security", "ai-security", "threat-hunting", "investigations", "compliance", "enterprise", "agent-discovery" ], "use_cases": [ "Query data security intelligence from the Cyera platform through AI assistants connected via MCP to accelerate security investigations and threat hunting using plain language", "Enable security teams to discover shadow AI agents and MCP servers across endpoints, SaaS and cloud environments by connecting Agent Guardian to their AI workflow through the Cyera MCP server", "Build custom security agents on top of the Cyera platform via MCP that automate data security risk assessment, privacy workflows and compliance reporting at enterprise scale" ], "health": "active" }, { "id": "legit-security-mcp", "name": "Legit Security MCP Server", "description": "MCP server from Legit Security that delivers AI-native application security intelligence directly into AI code assistants. Connects seamlessly to Cursor, Copilot, Claude Code and Windsurf. Provides real-time security insights and remediation in natural language by connecting SAST and SCA data into a single context-aware intelligence layer that developers can query conversationally. Detects vulnerabilities and policy violations as AI assistants generate code, preventing issues before committing. Legit was named a 2026 Leader in ASPM. Released April 2026.", "category": "infrastructure", "endpoint": "https://www.legitsecurity.com/legit-mcp-server-ai-native-security-intelligence-for-developers", "homepage_url": "https://www.legitsecurity.com/press-releases/legit-security-releases-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-08", "updated": "2026-08-08", "tags": [ "security", "appsec", "vulnerability-scanning", "developer-tools", "code-security", "sast", "sca", "aspm" ], "use_cases": [ "Query application security intelligence including SAST and SCA findings through AI code assistants connected to the Legit Security MCP server using natural language to get actionable fixes in real time", "Enable developers to detect vulnerabilities and policy violations as AI assistants generate code by connecting Cursor, Claude Code or Copilot to Legit Security via MCP for pre-commit security checks", "Build security-aware development workflows where AI agents query the Legit MCP server for vulnerability context and remediation guidance to reduce mean time to remediation from hours to minutes" ], "health": "active" }, { "id": "benchmark-gensuite-mcp", "name": "Benchmark Gensuite MCP Connector", "description": "MCP connector from Benchmark Gensuite, a leading provider of digital Environmental Health and Safety, Sustainability, Quality and Operational Risk management solutions. Enables authorized AI agents to securely interact with operational data and business processes across the Benchmark Gensuite platform through an open standardized interface. Organizations can connect AI agents to the platform using MCP instead of building and maintaining custom integrations for every use case. Builds on the company API-first architecture and reflects a broader strategy of enabling secure interoperability for agentic enterprise systems. Announced August 5, 2026.", "category": "productivity", "endpoint": "https://benchmarkgensuite.com", "homepage_url": "https://www.prnewswire.com/news-releases/benchmark-gensuite-announces-mcp-connector-enabling-ai-agent-access-to-enterprise-operational-risk-management-302842988.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "ehs", "sustainability", "operational-risk", "quality-management", "compliance", "enterprise", "safety" ], "use_cases": [ "Connect AI agents to Benchmark Gensuite operational data through MCP to query EHS incidents, compliance status and risk assessments using natural language without building custom API integrations", "Enable safety and compliance teams to build AI workflows that pull operational risk data from Benchmark Gensuite through the MCP connector for automated reporting and trend analysis", "Integrate Benchmark Gensuite sustainability and quality management data into enterprise AI assistants via MCP so teams can monitor environmental metrics and audit readiness conversationally" ], "health": "active" }, { "id": "arctera-ai-converge-mcp", "name": "Arctera AI Converge MCP", "description": "MCP integration from Arctera, a business unit of Cloud Software Group, that allows legal and compliance teams to apply AI directly against enterprise communications, files and historical records already under management. Built on the Model Context Protocol. Part of a strategic relationship with Arca, an agentic legal AI platform. Legal teams can search, investigate and analyze governed enterprise records directly within legal AI workflows while maintaining existing corporate permissions, retention policies, oversight and security controls. Connects Arca legal-specific AI capabilities with enterprise data context from the Arctera Unified Platform. Announced August 4, 2026.", "category": "productivity", "endpoint": "https://www.arctera.io", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/04/3338243/0/en/Arctera-and-Arca-Bring-Governed-Enterprise-Intelligence-to-Legal-AI.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "legal", "ediscovery", "compliance", "enterprise", "governance", "legal-ai", "records-management" ], "use_cases": [ "Search and investigate governed enterprise records including communications and files directly within legal AI workflows through Arctera AI Converge MCP while maintaining corporate permissions and retention policies", "Enable legal teams to accelerate ediscovery and surveillance workflows by connecting Arca agentic legal AI to enterprise data managed by the Arctera Unified Platform via MCP with full governance and defensibility", "Build AI-powered compliance workflows where agents query historical enterprise records through Arctera AI Converge MCP to surface relevant documents and communications for investigations without breaking chain of custody" ], "health": "active" }, { "id": "alchemiq-news-mcp", "name": "Alchemiq News Discovery MCP", "description": "MCP server from Alchemiq, an AI-powered global news discovery platform built by former journalists and communications professionals. Enables real-time news intelligence directly within ChatGPT, Claude and Gemini through the News Intelligence Layer. Users ask questions in natural language to surface emerging stories, signals and trends across multiple languages and countries. Fills the gap between AI assistants that explain the news and the ability to discover what is emerging next. Built on a real-time news intelligence engine that identifies emerging stories across languages, regions and publishers worldwide. Beta available to registered users. Announced August 5, 2026.", "category": "data", "endpoint": "https://alchemiq.io", "homepage_url": "https://www.prnewswire.com/news-releases/real-time-news-discovery-comes-to-chatgpt-claude-and-gemini---powered-by-alchemiq-302843459.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "news", "media-intelligence", "real-time", "trend-detection", "journalism", "communications", "multilingual" ], "use_cases": [ "Discover emerging news stories, signals and trends in real time through AI assistants connected to Alchemiq via MCP using natural language queries across multiple languages and countries", "Enable PR and communications professionals to build monitoring agents and research workflows that surface breaking stories from Alchemiq global news intelligence engine through MCP before they reach mainstream coverage", "Build custom news monitoring and media intelligence agents that query Alchemiq via MCP to track topics, detect narrative shifts and alert teams to emerging stories relevant to their industry or brand" ], "health": "active" }, { "id": "relpro-mcp", "name": "RelPro MCP Server", "description": "MCP server from RelPro, a relationship intelligence platform serving financial services, professional services and nonprofit sectors. Brings relationship intelligence data directly into AI workflows through the Model Context Protocol. Provides access to data on over 150 million decision-makers and 7 million companies including contact information, relationship mapping and business development insights. Teams can query company and contact intelligence, surface relationship connections and research prospects through AI assistants connected via MCP. Announced August 5, 2026.", "category": "data", "endpoint": "https://relpro.com", "homepage_url": "https://www.businesswire.com/news/home/20260805336301/en/RelPro-Launches-MCP-Server-Bringing-Relationship-Intelligence-Data-Directly-Into-AI-Workflows", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "relationship-intelligence", "business-development", "sales-intelligence", "financial-services", "contacts", "prospecting", "crm" ], "use_cases": [ "Query relationship intelligence data on decision-makers and companies through AI assistants connected to RelPro via MCP to research prospects and surface connection paths without leaving the AI workflow", "Enable business development teams in financial services to build AI agents that pull contact data, company insights and relationship maps from RelPro through MCP for automated prospect research", "Build AI-powered sales workflows where agents query RelPro via MCP to identify warm introductions, track executive movements and enrich CRM records with relationship intelligence" ], "health": "active" }, { "id": "natoma-mcp-gateway", "name": "Natoma MCP Gateway", "description": "Centralized MCP gateway from Natoma that acts as the governance and security layer controlling how AI agents use the Model Context Protocol to connect to enterprise systems. Enforces identity, policy and audit at the tool-call level between AI applications and MCP servers. Provides fine-grained authorization with OAuth 2.1, SSO and SAML and SCIM integration, and dynamic policy enforcement. Automatically detects unmanaged MCP servers and rogue agents across the environment. Includes comprehensive logging, SIEM integration and real-time policy monitoring. Acquired by Snowflake in May 2026 and now powers the Cortex AI Gateway. Also available as a standalone product.", "category": "infrastructure", "endpoint": "https://natoma.ai", "homepage_url": "https://www.snowflake.com/en/news/press-releases/snowflake-announces-intent-to-acquire-natoma-providing-secure-connectivity-for-the-agentic-enterprise/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "mcp-gateway", "security", "governance", "identity", "policy-enforcement", "agent-security", "enterprise", "zero-trust" ], "use_cases": [ "Deploy the Natoma MCP Gateway as a centralized policy enforcement point between AI agents and MCP servers to ensure every tool invocation is authorized, audited and compliant with corporate policies", "Enable security teams to discover unmanaged MCP servers and rogue AI agents across the enterprise by connecting the Natoma gateway which automatically detects unsanctioned MCP activity", "Build governed agentic AI deployments where the Natoma MCP Gateway enforces fine-grained OAuth 2.1 authorization and dynamic policies at the tool-call level with full SIEM logging" ], "health": "active" }, { "id": "dynamics-365-customer-service-mcp", "name": "Dynamics 365 Customer Service MCP Server", "description": "MCP server from Microsoft that connects Dynamics 365 Customer Service data, cases, knowledge and workflows to MCP-compatible AI clients through a standardized connection model. Generally available as of July 30, 2026. Provides over 90 customer service tools that AI agents can use to automate support workflows. Teams can access cases, knowledge articles and customer context directly within AI tools they already use. Eliminates the need to build separate integrations for every AI experience. Maintains centralized management of customer data and access policies. Supports Claude, ChatGPT, Microsoft Copilot and other MCP-compatible clients.", "category": "productivity", "endpoint": "https://learn.microsoft.com/en-us/dynamics365/customer-service/", "homepage_url": "https://www.microsoft.com/en-us/dynamics-365/blog/it-professional/2026/07/30/dynamics-365-customer-service-mcp-server-ga/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "customer-service", "microsoft", "dynamics-365", "support", "crm", "enterprise", "case-management", "knowledge-base" ], "use_cases": [ "Automate customer service workflows by connecting AI agents to Dynamics 365 Customer Service via MCP to access over 90 tools for case management, knowledge retrieval and customer context", "Enable support teams to query case data, search knowledge articles and check customer history through AI assistants connected to Dynamics 365 Customer Service MCP without switching between systems", "Build AI-powered support operations where agents resolve cases, route inquiries and surface relevant knowledge articles through Dynamics 365 Customer Service MCP with centralized access controls" ], "health": "active" }, { "id": "bedrock-data-argusai-mcp", "name": "Bedrock Data ArgusAI MCP Server", "description": "MCP server from Bedrock Data that gives enterprise AI workflows direct access to data risk context from the Bedrock Metadata Lake. Part of the ArgusAI platform which governs the enterprise AI risk surface across three components: AI agents enterprises deploy, MCP servers and connectors that broker access to enterprise systems, and the sensitive data those systems can retrieve. Autonomously discovers, classifies and contextualizes sensitive data across cloud, IaaS, PaaS, SaaS and AI environments at petabyte scale. Expanded at Black Hat USA 2026 with Agent DLP for runtime data loss prevention for AI agents. Showcased IANS MCP Intelligence demo at Black Hat.", "category": "infrastructure", "endpoint": "https://bedrockdata.ai", "homepage_url": "https://www.businesswire.com/news/home/20260319726829/en/Bedrock-Data-Expands-ArgusAI-to-Govern-the-Enterprise-AI-Risk-Surface", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "data-security", "ai-governance", "risk-management", "data-classification", "dlp", "compliance", "enterprise", "agent-security" ], "use_cases": [ "Query data risk context from the Bedrock Metadata Lake through AI agents connected via MCP to understand sensitive data exposure across cloud, SaaS and AI environments at enterprise scale", "Enable security teams to build AI workflows that discover and classify sensitive data across the enterprise by connecting ArgusAI risk intelligence through the Bedrock Data MCP server", "Govern AI agent data access at runtime by connecting Bedrock Data ArgusAI MCP to agentic workflows for real-time data loss prevention and sensitive data exposure monitoring" ], "health": "active" }, { "id": "dynamics-365-erp-mcp", "name": "Dynamics 365 ERP MCP Server", "description": "MCP server from Microsoft for Dynamics 365 Finance and Supply Chain Management that lets AI agents act across ERP processes in real time. Evolving from a static server with 13 tools to a dynamic server unlocking hundreds of thousands of ERP functions for secure real-time use by agents, developers and applications. Improved data tools move operations from OData to SQL for better performance and agentic response quality. Includes an Analytics MCP that enables natural language analytical queries without writing DAX queries. Agents can open records and attachments from responses for transparency and traceability. The static version retires October 1, 2026. Major dynamic update August 2026.", "category": "productivity", "endpoint": "https://learn.microsoft.com/en-us/dynamics365/fin-ops-core/dev-itpro/copilot/copilot-mcp", "homepage_url": "https://erp.today/microsoft-expands-mcp-into-dynamic-ai-ready-foundation-for-dynamics-365-erp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-09", "updated": "2026-08-09", "tags": [ "erp", "microsoft", "dynamics-365", "finance", "supply-chain", "enterprise", "analytics", "accounting" ], "use_cases": [ "Connect AI agents to Dynamics 365 Finance and Supply Chain Management through MCP to execute ERP operations, query financial data and manage supply chain workflows using natural language", "Enable finance teams to ask analytical questions about ERP data through AI assistants connected to the Dynamics 365 ERP Analytics MCP without writing DAX queries or navigating complex reporting interfaces", "Build AI-powered supply chain workflows where agents plan inventory, track orders and analyze operational data through the Dynamics 365 ERP MCP server with full audit trails and governed access" ], "health": "active" }, { "id": "tripgain-mcp", "name": "TripGain MCP Server", "description": "MCP server from TripGain, an AI-powered travel and expense management platform serving over 400 customers and 400,000 employees across industries. Pairs the open Model Context Protocol with TripGain proprietary API Gateway to give any compatible AI assistant integrated access to enterprise travel and expense workflows. Employees can book business travel, file expense reports, manage vendor expenses and approve requests through natural conversation. The AI assistant can submit expense reports automatically in the same conversation, routed through the company approval workflow and vendor reconciliation engine with no additional portals or manual steps. Announced at the Global Business Travel Association Convention 2026 in Chicago on August 4, 2026.", "category": "productivity", "endpoint": "https://tripgain.com", "homepage_url": "https://www.techtimes.com/articles/323054/20260804/tripgain-mcp-server-extends-agentic-ai-booking-corporate-expense-approvals.htm", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "travel", "expense-management", "corporate-travel", "enterprise", "approvals", "vendor-management", "booking" ], "use_cases": [ "Book business travel, file expense reports and approve requests through natural conversation with AI assistants connected to TripGain via MCP without switching to separate portals or dashboards", "Enable finance teams to automate expense report submission and vendor reconciliation by connecting AI agents to TripGain MCP so employees can complete travel and expense workflows in a single conversational thread", "Build AI-powered corporate travel workflows where agents book flights and hotels, file expenses and route approvals through TripGain MCP with full compliance to company travel policies" ], "health": "active" }, { "id": "promptfoo-mcp-proxy", "name": "Promptfoo MCP Proxy", "description": "Open-source MCP proxy from Promptfoo that sits between AI applications and MCP servers to provide enterprise-grade security, monitoring and access control. Whitelists approved MCP servers, grants granular permissions and monitors for PII and sensitive data exposure. Provides detailed logging and real-time alerts for unauthorized access attempts and policy violations. Includes red-teaming capabilities for testing MCP server security with an evil MCP server for adversarial testing. Part of the Promptfoo open-source LLM evaluation and red-teaming platform with over 22,000 GitHub stars. Demonstrated live at Black Hat USA 2026 at the OpenAI booth. Available on GitHub.", "category": "infrastructure", "endpoint": "https://www.promptfoo.dev/mcp/", "homepage_url": "https://www.promptfoo.dev/blog/mcp-proxy-announcement/", "github_url": "https://github.com/promptfoo/promptfoo", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "npx promptfoo@latest mcp-proxy", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "security", "proxy", "red-team", "mcp-gateway", "access-control", "monitoring", "pii-detection", "open-source" ], "use_cases": [ "Deploy Promptfoo MCP Proxy between AI assistants and MCP servers to whitelist approved servers, enforce granular tool permissions and monitor all MCP communications for sensitive data exposure", "Red-team MCP server deployments using Promptfoo adversarial testing tools including the evil MCP server to identify prompt injection vulnerabilities, data exfiltration risks and unauthorized access paths", "Add enterprise security controls to existing MCP server infrastructure by routing traffic through the Promptfoo proxy for real-time PII detection, access logging and policy enforcement without modifying server code" ], "health": "active" }, { "id": "acalvio-shadowplex-mcp", "name": "Acalvio ShadowPlex Deception Guardrails", "description": "Deception security platform from Acalvio Technologies that deploys decoy MCP servers, decoy RAG systems and decoy AI agents alongside honeytokens and deceptive assets embedded into AI agent workflows. Extends the ShadowPlex platform to detect and disrupt compromised AI agents before they access enterprise assets. If an AI agent goes rogue or is manipulated, deceptive assets detect the misalignment, feed the attacker fabricated data and alert the SOC before real enterprise systems are compromised. Provides real-time detection of malicious manipulation, jailbreak behavior and prompt injection attempts targeting agentic AI environments. Demonstrated at Black Hat USA 2026. Announced August 3, 2026.", "category": "infrastructure", "endpoint": "https://www.acalvio.com", "homepage_url": "https://www.prnewswire.com/news-releases/acalvio-unveils-deception-guardrails-to-secure-ai-agents-302838574.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "deception", "security", "honeytokens", "agent-security", "threat-detection", "decoy", "prompt-injection", "enterprise" ], "use_cases": [ "Deploy decoy MCP servers and honeytokens alongside production AI agent infrastructure using Acalvio ShadowPlex to detect compromised agents attempting unauthorized tool access or data exfiltration", "Embed deceptive assets into AI agent workflows through ShadowPlex Deception Guardrails to catch prompt injection attacks and jailbreak attempts in real time before they reach enterprise systems", "Build layered AI agent security by deploying Acalvio decoy RAG systems, fake MCP servers and trap credentials that lure malicious activity while alerting the SOC and feeding attackers fabricated data" ], "health": "active" }, { "id": "knowbe4-agent-risk-manager-mcp", "name": "KnowBe4 Agent Risk Manager", "description": "Agent governance and risk management platform from KnowBe4 that provides real-time visibility into autonomous AI agent activity with automated threat detection and monitoring of agent execution. Supports Anthropic Claude environments with native support for Microsoft Copilot. Monitors actions, outputs and tool usage for agents that automate tasks, analyze data and connect to third-party applications without modifying the underlying model. Leverages 15 years of behavioral data to combat advanced threats including social engineering, prompt injection and shadow AI. Announced at Black Hat USA 2026 on August 3, 2026.", "category": "infrastructure", "endpoint": "https://www.knowbe4.com", "homepage_url": "https://www.businesswire.com/news/home/20260803241393/en/KnowBe4-Extends-Agent-Security-to-Anthropics-Claude-With-Agent-Risk-Manager", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "agent-security", "risk-management", "governance", "monitoring", "threat-detection", "shadow-ai", "enterprise", "compliance" ], "use_cases": [ "Monitor AI agent activity across Claude and Copilot environments using KnowBe4 Agent Risk Manager to detect unauthorized tool usage, prompt injection attempts and shadow AI operations in real time", "Enable security teams to govern autonomous AI agents by connecting KnowBe4 Agent Risk Manager for centralized visibility into agent actions, outputs and third-party application connections", "Build enterprise AI governance workflows where KnowBe4 Agent Risk Manager flags anomalous agent behavior using 15 years of behavioral threat data and alerts security teams before agents take unauthorized actions" ], "health": "active" }, { "id": "sweet-security-agentic-mcp", "name": "Sweet Security Agentic AI Blocking", "description": "Runtime enforcement platform from Sweet Security that extends autonomous protection from cloud workloads to the AI agents acting alongside them. Blocks rogue agent behavior in real time at the runtime level. Terminates unauthorized tool calls and sessions at runtime, stops secrets, PII and sensitive data from leaving through an agent, and blocks prompt injections live before they steer an agent off course. Unlike monitoring-only approaches that report bad behavior after the fact, Sweet Security blocks threats in runtime the moment they occur. Demonstrated live at Black Hat USA 2026 at Booth 5721. Announced July 29, 2026.", "category": "infrastructure", "endpoint": "https://www.sweet.security", "homepage_url": "https://siliconangle.com/2026/07/29/sweet-security-debuts-agentic-ai-blocking-stop-rogue-agents-real-time/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "runtime-security", "agent-security", "blocking", "pii-protection", "prompt-injection", "cloud-security", "enterprise", "real-time" ], "use_cases": [ "Deploy Sweet Security alongside AI agent infrastructure to terminate unauthorized tool calls and MCP sessions in real time before agents can access restricted enterprise systems or exfiltrate data", "Protect sensitive data from AI agent leakage by using Sweet Security runtime enforcement to block secrets, PII and confidential information from leaving through agent interactions at the execution layer", "Block prompt injection attacks targeting AI agents in real time using Sweet Security enforcement that detects and stops malicious prompts before they steer agents into unauthorized actions" ], "health": "active" }, { "id": "zero-networks-least-agency-mcp", "name": "Zero Networks Least Agency Enforcement", "description": "AI agent governance capability from Zero Networks that enforces the OWASP Least Agency principle at the network level for enterprise AI deployments. Allows enterprises to limit what AI agents can access, what actions they can perform and when human approval is required. Leverages identity-based microsegmentation, policy automation and just-in-time multi-factor authentication to control agent behavior. Research from the Zero Networks 2026 Lateral Movement Exposure Report reveals nearly 80 percent of enterprises have deployed internal AI agents yet two-thirds lack governance policies. Demonstrated at Black Hat USA 2026 at Booth 1852. Announced August 3, 2026.", "category": "infrastructure", "endpoint": "https://zeronetworks.com", "homepage_url": "https://www.businesswire.com/news/home/20260803185432/en/Zero-Networks-Launches-New-Capability-to-Enforce-OWASPs-Least-Agency-Principle-for-Enterprise-AI", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "agent-governance", "least-agency", "microsegmentation", "owasp", "network-security", "mfa", "access-control", "enterprise" ], "use_cases": [ "Enforce OWASP Least Agency principle on AI agents by deploying Zero Networks microsegmentation to limit agent access to only the systems and data required for their specific tasks", "Require human approval for sensitive AI agent operations using Zero Networks just-in-time MFA enforcement so agents cannot autonomously access critical infrastructure without explicit authorization", "Build network-level AI agent governance where Zero Networks policy automation controls which MCP servers and enterprise systems each agent can reach based on identity and role" ], "health": "active" }, { "id": "sinch-agent-tools-mcp", "name": "Sinch Agent Tools MCP Server", "description": "MCP server from Sinch, a global cloud communications platform, that gives AI assistants direct access to live Sinch API definitions and structured product knowledge covering configuration and implementation patterns. Part of the Sinch Agent Tools suite which includes extensions for Visual Studio Code, JetBrains IDEs and other Open VSX-compatible editors. Supports Claude Code, Cursor, GitHub Copilot and ChatGPT Desktop. Includes Simulator Mode that lets developers begin testing integrations directly from their development environment before creating an account. Open source on GitHub. Announced August 4, 2026.", "category": "communication", "endpoint": "https://sinch.com/ai/agent-tools/", "homepage_url": "http://www.prnewswire.com/news-releases/sinch-launches-agent-tools-for-developers-and-ai-coding-assistants-302842663.html", "github_url": "https://github.com/niclas-AInnovate/sinch-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-08-10", "updated": "2026-08-10", "tags": [ "communications", "sms", "voice", "messaging", "developer-tools", "api", "ide-integration", "simulator" ], "use_cases": [ "Build, test and deploy communication applications on the Sinch platform from AI-assisted coding tools like Claude Code and Cursor connected to Sinch Agent Tools MCP with live API definitions and implementation guidance", "Enable developers to explore and evaluate Sinch SMS, voice and messaging services through Simulator Mode directly in their IDE connected via MCP without needing to create a Sinch account first", "Accelerate Sinch API integration by connecting AI coding assistants to Sinch Agent Tools MCP for structured product knowledge covering configuration patterns, authentication setup and best practices" ], "health": "active" }, { "id": "upwork-mcp", "name": "Upwork MCP Server", "description": "Official MCP server from Upwork that connects AI agents directly to the Upwork freelancer marketplace. Enables AI assistants to find talent, post jobs, respond to invitations, submit proposals, review offers and manage active contracts. Built and hosted by Upwork at mcp.upwork.com with OAuth authorization. Compatible with Claude, ChatGPT, Cursor and any MCP-compatible product. Announced August 10, 2026.", "category": "productivity", "endpoint": "https://mcp.upwork.com/mcp", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/10/3342153/0/en/upwork-talent-is-now-everywhere-ai-works.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-11", "updated": "2026-08-11", "tags": [ "freelance", "hiring", "marketplace", "talent", "jobs", "contracts", "proposals", "remote-work" ], "use_cases": [ "Hire freelancers directly from AI assistants by asking Claude or ChatGPT to search Upwork for qualified talent, create job posts and draft offers without leaving the AI workflow", "Enable developers deep in a build to instantly find and engage specialized freelancers through AI agents connected to Upwork via MCP when they hit a skill gap or need testing support", "Manage active Upwork contracts, review proposals and track project milestones through conversational AI tools connected to Upwork MCP for streamlined freelancer management" ], "health": "active" }, { "id": "nutanix-mcp", "name": "Nutanix MCP Server", "description": "Open-source MCP server for Nutanix Cloud Platform that enables AI assistants to interact with infrastructure through the Nutanix Prism V4 API. Exposes over 1,000 V4 API operations and provides AI tools with API schemas, code samples and permission information. All AI agent activity routes through the Prism V4 API Gateway so every AI-initiated action inherits the same RBAC policies and audit trails that govern human operators. Supports GitHub Copilot, Claude Code and Cursor. Requires Python 3.11 or later and connects to Prism Central. Released as v0.8 Technical Preview. Announced August 10, 2026.", "category": "infrastructure", "endpoint": "https://developers.nutanix.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/10/3342153/0/en/nutanix-puts-agentic-ai-into-action-for-enterprises.html", "github_url": "https://github.com/thunderboltsid/mcp-nutanix", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-08-11", "updated": "2026-08-11", "tags": [ "cloud", "infrastructure", "nutanix", "devops", "hybrid-cloud", "virtualization", "enterprise", "prism" ], "use_cases": [ "Automate daily cloud operations on Nutanix Cloud Platform by asking AI assistants connected via MCP to provision VMs, manage clusters and check resource utilization through natural language instead of navigating Prism dashboards", "Enable IT teams to query infrastructure state and troubleshoot issues through Claude Code or Cursor connected to Nutanix MCP with full RBAC enforcement and audit trails matching existing governance policies", "Build AI-powered infrastructure automation workflows where agents translate natural language requests into Nutanix Prism V4 API operations for VM lifecycle management, storage provisioning and network configuration" ], "health": "active" }, { "id": "shipbob-mcp", "name": "ShipBob MCP Server", "description": "MCP server from ShipBob, the global ecommerce fulfillment platform, that gives AI agents direct read-and-write access to fulfillment operations. The first Anthropic-verified fulfillment connector. Exposes actions across orders, inventory, products, shipments, returns, webhooks, locations, billing and reports. Supports Claude, Claude Desktop, VS Code with GitHub Copilot and other MCP-compatible clients. Part of the ShipBob Summer 2026 AI release alongside Bobby AI agent and warehouse robotics. Announced August 4, 2026.", "category": "data", "endpoint": "https://developer.shipbob.com/mcp-server", "homepage_url": "https://www.prnewswire.com/news-releases/shipbob-launches-first-anthropic-verified-fulfillment-connector-anchoring-its-ai-suite-302842134.html", "x402": false, "verified": true, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-11", "updated": "2026-08-11", "tags": [ "ecommerce", "fulfillment", "shipping", "inventory", "orders", "logistics", "warehouse", "3pl" ], "use_cases": [ "Manage ecommerce fulfillment operations through AI assistants connected to ShipBob via MCP to create orders, track shipments, adjust inventory levels and process returns using natural language", "Enable DTC brands to build AI-powered logistics workflows where agents monitor inventory levels, reorder SKUs, reroute shipments and resolve exception orders through the ShipBob MCP server in real time", "Connect Claude or Cursor to ShipBob via MCP to query fulfillment data across products, orders, shipments and locations for operational reporting and troubleshooting without navigating the ShipBob dashboard" ], "health": "active" }, { "id": "intezer-mcp", "name": "Intezer MCP Server", "description": "Revamped MCP server from Intezer that connects AI agents to the Intezer security investigations platform for SOC operations. Sits between detection tools and AI agents, giving Claude, Codex and Cursor access to case histories, workflows, triage logic and prior investigation records. Designed as an operating layer for security operations that accelerates SOC tasks by 10x. Intezer AI SOC investigates every alert at 98 percent accuracy in under two minutes with less than 2 percent escalated to human review. Announced June 18, 2026.", "category": "infrastructure", "endpoint": "https://www.intezer.com", "homepage_url": "https://securitybrief.news/story/intezer-launches-mcp-server-for-security-ai-agents", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-11", "updated": "2026-08-11", "tags": [ "security", "soc", "threat-detection", "incident-response", "malware-analysis", "alert-triage", "forensics" ], "use_cases": [ "Accelerate SOC workflows by connecting Claude or Codex to Intezer via MCP for AI-powered alert triage, investigation and response with access to case histories and prior investigation records", "Enable security teams to query the Intezer platform through AI assistants for forensic-grade investigation results, malware verdicts and threat intelligence without switching to the Intezer dashboard", "Build AI-driven security automation where agents connected to Intezer via MCP investigate alerts end-to-end, correlate indicators across cases and surface actionable findings for human review" ], "health": "active" }, { "id": "marketo-engage-mcp", "name": "Adobe Marketo Engage MCP Server", "description": "Official MCP server from Adobe for Marketo Engage marketing automation platform. Hosted by Adobe at marketo-mcp.adobe.io with over 100 operations for forms, programs, smart campaigns, leads, emails, snippets, lists and folders. Multi-tenant with per-request credential passing and no credential storage or caching. Supports Claude, GitHub Copilot, Microsoft Copilot Studio, Cursor, Windsurf and Google Gemini. Launched in beta April 2026.", "category": "productivity", "endpoint": "https://marketo-mcp.adobe.io/mcp", "homepage_url": "https://business.adobe.com/blog/connect-the-power-of-your-ai-tools-with-the-mcp-server-for-marketo-engage", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-11", "updated": "2026-08-11", "tags": [ "marketing-automation", "adobe", "marketo", "email-marketing", "leads", "campaigns", "crm", "enterprise" ], "use_cases": [ "Manage Marketo Engage marketing campaigns through AI assistants connected via MCP to create smart campaigns, update lead records, manage email assets and query program performance without navigating the Marketo UI", "Enable marketing operations teams to automate lead management workflows by connecting Claude or Copilot to Marketo Engage MCP for bulk lead updates, list management and form configuration through natural language", "Build AI-powered marketing automation where agents query Marketo Engage via MCP to analyze campaign performance, manage program hierarchies and configure smart campaign triggers across the marketing stack" ], "health": "active" }, { "id": "green-street-mcp", "name": "Green Street MCP Server", "description": "MCP server from Green Street, the leading commercial real estate research and analytics firm, that connects proprietary CRE intelligence directly into corporate instances of Claude, ChatGPT, Gemini and other AI platforms. Powered by GreenStreetAI, the server gives real assets professionals natural-language access to Green Street's proprietary research, data, forecasts and decades of news archives. Part of the GreenStreetAI capability suite alongside AI Summaries and the forthcoming AI Assistant. Generally available August 11, 2026.", "category": "data", "endpoint": "https://www.greenstreet.com", "homepage_url": "https://www.prnewswire.com/news-releases/green-street-launches-its-mcp-server-powered-by-greenstreetai-connecting-cre-intelligence-directly-to-corporate-instances-of-claude-chatgpt-gemini-and-other-ai-platforms-302848322.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "commercial-real-estate", "real-estate", "analytics", "research", "forecasting", "property", "investment", "enterprise" ], "use_cases": [ "Query Green Street's proprietary commercial real estate research, property valuations and market forecasts through Claude, ChatGPT or Gemini connected via MCP using natural language instead of navigating multiple research reports", "Enable real assets professionals to analyze CRE market trends, compare property sectors and access decades of Green Street news archives through AI assistants connected to the Green Street MCP server for faster investment decision-making", "Build AI-powered CRE research workflows where agents combine Green Street data with other connected business intelligence to surface patterns across property markets, cap rates and sector performance" ], "health": "active" }, { "id": "rechat-mcp", "name": "Rechat MCP Server", "description": "MCP server from Rechat, the AI-powered real estate operating system, that gives real estate agents and brokerages secure access to contacts, marketing tools and transaction information through AI assistants. Enables agents to manage contacts, create marketing campaigns, track transactions and check business data using natural language. Uses OAuth authentication with permission-based access scoped to individual agent accounts. Compatible with Claude, ChatGPT and other MCP-compatible clients. Available to developers now with a waitlist for agents and brokerages. Announced August 3, 2026.", "category": "productivity", "endpoint": "https://rechat.ai", "homepage_url": "https://www.inman.com/2026/08/03/rechat-mcp-server-ai/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "real-estate", "crm", "marketing", "transactions", "contacts", "brokerage", "agents" ], "use_cases": [ "Manage real estate contacts, update tags and prioritize follow-ups through AI assistants connected to Rechat via MCP using natural language instead of navigating the Rechat dashboard", "Enable real estate agents to create and launch email campaigns, social posts and listing websites by asking Claude or ChatGPT to execute marketing workflows through the Rechat MCP server", "Track transaction status, check deal milestones and manage active listings through conversational AI tools connected to Rechat MCP for streamlined day-to-day brokerage operations" ], "health": "active" }, { "id": "decile-mcp", "name": "Decile MCP Server", "description": "MCP server from Decile, the ecommerce customer intelligence platform, that connects AI assistants directly to enriched first-party customer data for analytics and audience activation. Marketers can ask natural language questions about customer personas, segment performance and buying behavior, then create and save audience segments for activation on connected advertising and marketing platforms within the same conversation. Available through the Anthropic Connectors Directory, ChatGPT and other MCP-compatible AI clients. Announced August 11, 2026.", "category": "data", "endpoint": "https://www.decile.com", "homepage_url": "https://www.prnewswire.com/news-releases/decile-launches-first-ecommerce-analytics-and-activation-mcp-bringing-customer-intelligence-directly-into-ai-workflows-302847853.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "ecommerce", "analytics", "customer-intelligence", "segmentation", "audience", "marketing", "activation", "shopify" ], "use_cases": [ "Ask AI assistants connected to Decile via MCP questions like which customer personas are most valuable to a brand and receive brand-specific insights drawn from enriched first-party data instead of generic AI responses", "Create and save audience segments for advertising and marketing activation directly within a Claude or ChatGPT conversation connected to Decile MCP without switching to separate analytics dashboards", "Build AI-powered ecommerce analytics workflows where agents query Decile through MCP for customer lifetime value analysis, cohort performance and segment discovery to inform marketing spend allocation" ], "health": "active" }, { "id": "iir-envoy-mcp", "name": "IIR Envoy MCP Server", "description": "MCP server from Industrial Info Resources (IIR) that brings 40 years of human-verified energy and industrial intelligence directly into AI tools. Subscribers can query IIR's capital project, plant, offline-event, unit, equipment and LTSA data through Claude, Microsoft Copilot, Google Gemini and ChatGPT, receiving source-cited answers drawn from IIR's live dataset rather than general training data. Covers global energy, manufacturing, mining, chemicals and infrastructure sectors. Announced July 30, 2026.", "category": "data", "endpoint": "https://www.industrialinfo.com", "homepage_url": "https://www.businesswire.com/news/home/20260730800928/en/Industrial-Info-Resources-Launches-IIR-Envoy-MCP-Bringing-Human-Verified-Industrial-Intelligence-Directly-Into-AI-Through-Model-Context-Protocol", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "energy", "industrial", "infrastructure", "mining", "chemicals", "manufacturing", "capital-projects", "enterprise" ], "use_cases": [ "Query IIR's global database of capital projects, plant operations and equipment data through AI assistants connected via MCP to get source-cited answers about energy and industrial market activity without navigating the IIR platform", "Enable analysts to research plant offline events, maintenance schedules and LTSA intelligence through Claude or Copilot connected to IIR Envoy MCP for faster due diligence and market analysis", "Build AI-powered industrial research workflows where agents query human-verified IIR data through MCP to surface capital project trends, competitive intelligence and infrastructure investment opportunities across global markets" ], "health": "active" }, { "id": "leadiq-mcp", "name": "LeadIQ MCP Server", "description": "MCP server from LeadIQ, the B2B sales prospecting platform, that connects AI agents to LeadIQ's database of 750 million plus profiles with 200 million re-verified monthly. Enables AI assistants to find verified contacts, enrich leads and push data to CRM through natural language prompts. One of the first prospecting platforms to ship an MCP server. Also a Microsoft Dynamics 365 Sales MCP launch partner. Works with Claude, ChatGPT, Cursor and other MCP-compatible tools. Included with every LeadIQ subscription.", "category": "data", "endpoint": "https://leadiq.com", "homepage_url": "https://msdynamicsworld.com/story/ai-agents-dynamics-365-sales-microsoft-announces-mcp-launch-partners", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "sales", "prospecting", "contacts", "lead-enrichment", "crm", "b2b", "sales-intelligence" ], "use_cases": [ "Find verified B2B contacts and enrich lead records through AI assistants connected to LeadIQ via MCP using natural language requests like finding the VP of Sales at a target account", "Enable sales teams to push enriched contact data directly to their CRM through Claude or ChatGPT connected to LeadIQ MCP without manually exporting and importing prospect lists", "Build AI-powered sales prospecting workflows where agents query LeadIQ through MCP for contact discovery, champion tracking and account research to accelerate pipeline building" ], "health": "active" }, { "id": "enlyft-mcp", "name": "Enlyft MCP Server", "description": "MCP server from Enlyft, the B2B customer acquisition and account intelligence platform, that gives AI agents access to technology adoption signals, firmographic data and buyer intelligence across 42 million plus companies and 300 million plus people profiles. A Microsoft Dynamics 365 Sales MCP launch partner. Enables AI sales agents to identify best-fit accounts, assess tech stack compatibility and prioritize prospects using custom propensity models. Available through Microsoft Copilot Studio, Claude and other MCP-compatible clients.", "category": "data", "endpoint": "https://enlyft.com", "homepage_url": "https://learn.microsoft.com/en-us/connectors/enlyftmcp/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "sales-intelligence", "b2b", "technographics", "buyer-intent", "account-intelligence", "firmographics", "lead-scoring" ], "use_cases": [ "Enable AI sales agents to identify and prioritize best-fit accounts by querying Enlyft through MCP for technology adoption signals, competitive install base data and custom propensity scores", "Connect Dynamics 365 Sales qualification agents to Enlyft via MCP so they reason over a prospect's real tech stack and business attributes before a seller engages", "Build AI-powered GTM workflows where agents query Enlyft through MCP for account research, buyer persona identification and outreach personalization based on verified technographic intelligence" ], "health": "active" }, { "id": "gong-mcp", "name": "Gong MCP Server", "description": "MCP server from Gong, the revenue intelligence platform serving 5,000 plus companies, that brings conversation intelligence and revenue data into AI agent workflows. Part of Gong's Mission Big Dipper release. Enables AI assistants to access deal context, call analytics, pipeline data and buyer signals. Available through Microsoft Copilot, Claude and other MCP-compatible tools. A Microsoft Dynamics 365 Sales MCP launch partner. MCP support launched with Mission Big Dipper in June 2026 alongside Custom Agents for RevOps.", "category": "data", "endpoint": "https://www.gong.io", "homepage_url": "https://www.prnewswire.com/news-releases/gong-launches-mission-big-dipper-unveils-industry-first-revenue-harness-302808677.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "revenue-intelligence", "sales", "conversation-analytics", "deals", "pipeline", "call-analytics", "enterprise" ], "use_cases": [ "Access Gong conversation intelligence and deal context through AI assistants connected via MCP for AI-powered call analysis, pipeline review and buyer signal detection without logging into the Gong dashboard", "Enable RevOps teams to build custom AI agents using Gong MCP that automate deal inspection, forecast accuracy checks and next-action recommendations based on live revenue data", "Connect Microsoft Copilot or Claude to Gong via MCP to query meeting transcripts, track competitive mentions and surface deal risks across the revenue pipeline" ], "health": "active" }, { "id": "hg-insights-mcp", "name": "HG Insights MCP Server", "description": "MCP server from HG Insights, the B2B technology intelligence platform, that provides AI agents with access to firmographics, technographics, IT spend, contracts, competitive signals, intent data, SEC filing intelligence and live web sources across millions of companies. Part of the RGI Agent Builder product. A Microsoft Dynamics 365 Sales MCP launch partner. Enterprise-grade MCP server connects directly to HG's Revenue Growth Intelligence Fabric without ETL pipelines or custom integrations. Works with Claude, ChatGPT, Cursor and Windsurf.", "category": "data", "endpoint": "https://hginsights.com", "homepage_url": "https://hginsights.com/solutions-use-case/gtm-infrastructure-for-ai-agents/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "technology-intelligence", "b2b", "technographics", "it-spend", "firmographics", "competitive-intelligence", "sales-intelligence", "enterprise" ], "use_cases": [ "Query HG Insights technology adoption data and IT spend intelligence through AI assistants connected via MCP to research target accounts, validate tech stack fit and size market opportunities without manual data pulls", "Enable GTM teams to build custom AI agents using HG Insights RGI Agent Builder and MCP that automate prospect research, account scoring and competitive analysis across millions of companies", "Connect Claude or ChatGPT to HG Insights via MCP for real-time account enrichment with firmographics, technographics, intent signals and SEC filing intelligence during sales qualification workflows" ], "health": "active" }, { "id": "dun-bradstreet-mcp", "name": "Dun & Bradstreet MCP Server", "description": "MCP server from Dun and Bradstreet that integrates D&B's Commercial Graph of more than 600 million company records anchored by the D-U-N-S Number directly into AI assistants and custom agents. Enables agentic KYC, KYB, compliance screening, supplier intelligence and third-party risk workflows. Reduces compliance processing times by 70 to 90 percent. A Microsoft Dynamics 365 Sales MCP launch partner. Available in Claude with additional integrations planned for Microsoft Copilot and Google ecosystems. Announced June 2026.", "category": "data", "endpoint": "https://www.dnb.com", "homepage_url": "https://www.prnewswire.com/news-releases/dun--bradstreet-introduces-agentic-ai-capabilities-to-accelerate-compliance-and-third-party-risk-workflows-from-days-to-seconds-302804723.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "business-data", "compliance", "kyc", "risk", "firmographics", "supplier-intelligence", "enterprise", "duns" ], "use_cases": [ "Automate KYC and KYB compliance workflows by connecting Claude to Dun and Bradstreet via MCP for AI-powered entity resolution, risk screening and due diligence against 600 million plus company records", "Enable procurement teams to evaluate supplier risk and financial health through AI assistants connected to D&B via MCP using natural language queries instead of manual screening processes", "Build AI-powered compliance agents that query D&B's Commercial Graph through MCP for third-party risk assessment, beneficial ownership checks and credit analysis to reduce processing times from days to seconds" ], "health": "active" }, { "id": "zoominfo-mcp", "name": "ZoomInfo MCP Server", "description": "MCP server from ZoomInfo, the GTM intelligence platform, that grounds AI agents in verified B2B data across 100 million plus companies and 600 million plus contacts. Part of the GTM.AI product launched June 2026. Hosted at mcp.zoominfo.com with Streamable HTTP transport. Included with every ZoomInfo subscription at no extra cost and connects in three steps with no developer app required. Compatible with Claude, ChatGPT, Salesforce Agentforce, HubSpot Breeze and other MCP-compatible clients. A Microsoft Dynamics 365 Sales MCP launch partner.", "category": "data", "endpoint": "https://mcp.zoominfo.com/mcp", "homepage_url": "https://pipeline.zoominfo.com/operations/zoominfo-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-12", "updated": "2026-08-12", "tags": [ "sales-intelligence", "b2b", "contacts", "firmographics", "intent-data", "gtm", "crm", "lead-enrichment" ], "use_cases": [ "Find, enrich and research companies and contacts through AI assistants connected to ZoomInfo via MCP using natural language queries against 100 million plus companies and 600 million plus contacts", "Enable sales teams to ground Salesforce Agentforce, HubSpot Breeze or Claude in verified ZoomInfo B2B data through MCP for accurate account research, contact discovery and buying signal detection", "Build AI-powered GTM workflows where agents query ZoomInfo through MCP for identity-resolved company data, technographics, hiring signals and IP-to-organization pairings to automate prospecting and enrichment" ], "health": "active" }, { "id": "getty-images-mcp", "name": "Getty Images MCP Server", "description": "MCP server from Getty Images that gives developers and enterprise technology teams a standardized way to integrate licensed creative, editorial and archival visual content into AI-powered workflows and products. AI agents can discover, retrieve and use images and video from Getty Images' collection spanning creative, news, sport, entertainment and archival content. Designed for enterprise customers, media organizations and technology partners building AI solutions for marketing, advertising, news and entertainment. Announced August 12, 2026.", "category": "media", "endpoint": "https://www.gettyimages.com", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/12/3344005/0/en/getty-images-launches-mcp-server-to-connect-creative-and-editorial-content-to-ai-workflows-and-products.html", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "stock-photos", "images", "video", "creative", "editorial", "media", "licensing", "enterprise" ], "use_cases": [ "Search and retrieve licensed creative and editorial images from Getty Images through AI assistants connected via MCP using natural language queries instead of navigating the Getty Images website", "Enable marketing and advertising teams to discover and download licensed visual content from Getty Images through Claude, ChatGPT or other MCP-compatible AI tools as part of automated content creation workflows", "Build AI-powered media workflows where agents query Getty Images through MCP for news, sport and entertainment visuals with proper licensing, reducing manual image sourcing and rights management overhead" ], "health": "active" }, { "id": "dimensions-semantic-search-mcp", "name": "Dimensions Semantic Search MCP Server", "description": "MCP server from Digital Science that provides concept-aware semantic search across the Dimensions research database, one of the world's largest interconnected global research databases. Built for precision retrieval across 40 plus life science domains. Enables AI agents to search publications, grants, patents, clinical trials and datasets using natural language with concept-level understanding rather than keyword matching. Part of a pair of Dimensions MCP servers alongside the Analytics MCP. Announced August 10, 2026.", "category": "data", "endpoint": "https://www.dimensions.ai", "homepage_url": "https://www.digital-science.com/press-releases/ai-agents-research-data-dimensions-mcp-servers/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "research", "academic", "publications", "grants", "patents", "clinical-trials", "life-sciences", "semantic-search" ], "use_cases": [ "Search the Dimensions research database with concept-aware semantic queries through AI assistants connected via MCP to find relevant publications, grants and patents across 40 plus life science domains without manual database navigation", "Enable research teams to query clinical trial data, patent filings and grant records through Claude or ChatGPT connected to Dimensions Semantic Search MCP for faster literature review and competitive intelligence", "Build AI-powered research workflows where agents perform precision retrieval across the Dimensions database through MCP, finding conceptually related studies and datasets that keyword search would miss" ], "health": "active" }, { "id": "dimensions-analytics-mcp", "name": "Dimensions Analytics MCP Server", "description": "MCP server from Digital Science that connects AI agents to 430 million plus interconnected records in the Dimensions research database spanning publications, grants, patents, clinical trials, datasets and policy documents. Enables analytical queries across the full Dimensions dataset for bibliometric analysis, trend detection and research landscape mapping. Part of a pair of Dimensions MCP servers alongside the Semantic Search MCP. Announced August 10, 2026.", "category": "data", "endpoint": "https://www.dimensions.ai", "homepage_url": "https://www.digital-science.com/press-releases/ai-agents-research-data-dimensions-mcp-servers/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "research", "analytics", "bibliometrics", "publications", "grants", "patents", "policy", "datasets" ], "use_cases": [ "Analyze research trends, citation patterns and funding landscapes across 430 million plus records through AI assistants connected to Dimensions Analytics MCP for data-driven research strategy decisions", "Enable R&D teams to perform bibliometric analysis and competitive intelligence queries through Claude or ChatGPT connected to Dimensions Analytics MCP without writing custom database queries", "Build AI-powered research intelligence workflows where agents query Dimensions through MCP to map research landscapes, identify emerging fields and track publication output across institutions and funding bodies" ], "health": "active" }, { "id": "altmetric-mcp", "name": "Altmetric MCP Server", "description": "MCP server from Digital Science that brings real-world research engagement and attention data into AI workflows. Tracks mentions of research across news media, social media, policy documents, clinical guidelines, patents and blogs. Enables AI agents to assess the societal reach and real-world impact of research beyond traditional citation counts. Existing Altmetric API customers can connect immediately with no additional license required. Compatible with Claude, ChatGPT, VS Code, Cursor and other MCP-compatible platforms. Announced August 6, 2026.", "category": "data", "endpoint": "https://www.altmetric.com", "homepage_url": "https://www.newsfilecorp.com/release/308347/Digital-Science-Brings-RealWorld-Research-Impact-Data-into-AI-Workflows-with-New-Altmetric-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "research", "altmetrics", "impact", "media-mentions", "policy", "social-media", "academic", "analytics" ], "use_cases": [ "Query Altmetric attention data through AI assistants connected via MCP to assess the real-world impact of research papers across news, social media, policy documents and clinical guidelines without navigating the Altmetric dashboard", "Enable medical affairs teams and research institutions to automate research impact reporting by connecting Claude or ChatGPT to Altmetric MCP for AI-assisted analytics across the full societal reach of research", "Build AI-powered research evaluation workflows where agents query Altmetric through MCP to surface real-world engagement evidence, media coverage and policy citations for grant applications, institutional reviews and funder reporting" ], "health": "active" }, { "id": "revenue-grid-mcp", "name": "Revenue Grid MCP Server", "description": "MCP server from Revenue Grid, the revenue operations and intelligence platform, that connects relationship intelligence, engagement history, revenue signals and AI insights to MCP-compatible AI applications and agents. Enables revenue teams to provide AI platforms with the context needed to generate relevant insights, recommendations and actions based on live relationship data. Works with Claude, ChatGPT, Microsoft Copilot and other MCP-compatible clients.", "category": "data", "endpoint": "https://revenuegrid.com", "homepage_url": "https://revenuegrid.com/blog/introducing-the-revenue-grid-mcp-server/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "revenue-intelligence", "sales", "relationship-intelligence", "engagement", "crm", "revenue-operations" ], "use_cases": [ "Access Revenue Grid relationship intelligence and engagement history through AI assistants connected via MCP for AI-powered account research, deal context and relationship mapping without leaving the AI workflow", "Enable sales teams to query customer interaction data, revenue signals and relationship strength through Claude or ChatGPT connected to Revenue Grid MCP for smarter deal strategy and next-action recommendations", "Build AI-powered revenue operations workflows where agents combine Revenue Grid relationship data via MCP with other connected platforms to synthesize account insights, track engagement patterns and surface at-risk relationships" ], "health": "active" }, { "id": "noded-mcp", "name": "Noded MCP Server", "description": "MCP server from Noded, the post-sales customer context platform, that auto-assembles a live account story from 20 plus connected tools and exposes it to AI agents. Pulls customer signals from Salesforce, HubSpot, Slack, Gong, Zendesk, Intercom, Jira, Linear, Gainsight, Planhat, Zoom, Google Meet, Pendo, G2, Databricks and more. Built for customer success, account management and post-sales teams that own retention and growth. Permission-aware and license-aligned.", "category": "productivity", "endpoint": "https://www.noded.ai", "homepage_url": "https://theaiagentindex.com/agents/noded", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "customer-success", "account-management", "post-sales", "retention", "crm", "customer-intelligence", "saas" ], "use_cases": [ "Query unified customer account context assembled from 20 plus tools through AI assistants connected to Noded via MCP for instant account health checks and churn risk assessment without switching between dashboards", "Enable customer success teams to ask natural language questions about account history, engagement patterns and support ticket trends through Claude or ChatGPT connected to Noded MCP for faster renewal preparation and expansion planning", "Build AI-powered post-sales workflows where agents query Noded through MCP to surface cross-tool customer signals, automate QBR preparation and generate account summaries that combine CRM, support, product usage and meeting data" ], "health": "active" }, { "id": "docmancer-mcp", "name": "Docmancer MCP Server", "description": "Open source MCP server that discovers the memory, instructions, rules and session evidence that Claude Code, Codex, Cursor, Gemini, OpenCode, Cline, Windsurf and other AI coding agents already wrote on your machine. Combines them into one canonical Markdown tree and serves grounded, cited recall through tools like ask_memory and canonical_memory. Uses SQLite FTS5 for lexical search and dense vectors from a vendored static model with Reciprocal Rank Fusion for result merging. Local-first with no external API dependencies.", "category": "code", "endpoint": "https://www.docmancer.dev", "homepage_url": "https://www.docmancer.dev/", "github_url": "https://github.com/docmancer/docmancer", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx docmancer mcp install claude-code", "added": "2026-08-13", "updated": "2026-08-13", "tags": [ "memory", "developer-tools", "documentation", "search", "local-first", "coding-agents", "knowledge-management" ], "use_cases": [ "Unify and search all the memory files, instructions and rules that Claude Code, Codex, Cursor and other coding agents have created across your machine through a single MCP server instead of manually tracking scattered CLAUDE.md and memory files", "Enable AI coding agents to recall previous decisions, patterns and project context through Docmancer MCP using semantic and lexical hybrid search with cited sources, reducing repeated explanations and context loss across sessions", "Build a local-first knowledge base from existing agent memory that any MCP-compatible tool can query, with no external API dependencies and full control over what data stays on your machine" ], "health": "active" }, { "id": "aiqbee-brain-mcp", "name": "Aiqbee Brain MCP Server", "description": "AI knowledge graph MCP server for architecture, portfolio and digital strategy. Provides 25 MCP tools to manage brains, neurons, relationships, neuron types and access control. Organizes ideas as neurons connected by synapses for documenting enterprise architecture, tracking products and projects. Features AI-powered search, team collaboration with role-based access and Microsoft 365 integration. Uses OAuth 2.0 with PKCE for authentication. Compatible with Claude Desktop, Cursor and ChatGPT.", "category": "productivity", "endpoint": "https://www.aiqbee.com", "homepage_url": "https://www.codaone.ai/mcp/servers/aiqbee-ai/", "github_url": "https://github.com/AIQBee/aiqbee-ai", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "knowledge-graph", "enterprise-architecture", "portfolio", "digital-strategy", "collaboration", "microsoft-365", "neurons" ], "use_cases": [ "Search, create and link knowledge across enterprise architecture, portfolio and digital strategy through AI assistants connected to Aiqbee Brain via MCP using natural language conversation instead of navigating the Aiqbee platform", "Enable enterprise architects to document systems, track product portfolios and map digital strategy as interconnected neurons and synapses through Claude or ChatGPT connected to Aiqbee Brain MCP with role-based team access controls", "Build AI-powered enterprise knowledge management workflows where agents query and update Aiqbee Brain through MCP to maintain living architecture documentation with AI-powered semantic search across the entire knowledge graph" ], "health": "active" }, { "id": "abap-accelerator-mcp", "name": "ABAP Accelerator MCP Server", "description": "Enterprise-grade MCP server from AWS that helps organizations create, test, document and transform SAP ABAP code faster and with higher accuracy. Enables AI-powered coding assistance through Amazon Q Developer and Kiro. Connects to SAP ABAP Test Cockpit to validate code and reduce hallucination. Enforces SAP transport workflow so all code changes require transport, QA review and approval before reaching production. Open source under MIT license. Updated August 11, 2026.", "category": "code", "endpoint": "https://aws.amazon.com/solutions/guidance/deploying-sap-abap-accelerator-for-amazon-q-developer/", "homepage_url": "https://aws.amazon.com/blogs/awsforsap/introducing-abap-accelerator-for-ai-assisted-development/", "github_url": "https://github.com/aws-solutions-library-samples/guidance-for-deploying-sap-abap-accelerator-for-amazon-q-developer", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "sap", "abap", "aws", "amazon-q", "enterprise", "code-generation", "testing", "documentation" ], "use_cases": [ "Create, test, document and transform SAP ABAP code through Amazon Q Developer or Kiro connected to ABAP Accelerator MCP for AI-assisted ABAP development with built-in code validation through SAP ABAP Test Cockpit", "Enable SAP development teams to generate ABAP code with higher accuracy by connecting AI coding agents to ABAP Accelerator MCP which validates against SAP standards and enforces transport workflow before any code reaches production", "Build AI-powered SAP modernization workflows where agents use ABAP Accelerator through MCP to analyze legacy ABAP code, generate documentation, create unit tests and transform code patterns while respecting SAP change management processes" ], "health": "active" }, { "id": "arc-1-sap-adt-mcp", "name": "ARC-1 SAP ADT MCP Server", "description": "TypeScript MCP server that translates AI tool calls into SAP ABAP Development Tools (ADT) REST API requests. Provides governed development-tooling proxy around ADT behavior including code checks, build and activate, transport management, AI-assisted ABAP authoring and Git workflows. Secure by default with positive opt-in flags and default deny for every mutation. Package allowlists restrict writes and every tool call is audited with user identity. Distributed as npm package and Docker image. Works with Claude, GitHub Copilot, VS Code and any MCP-compatible client.", "category": "code", "endpoint": "https://marianfoo.github.io/arc-1/", "homepage_url": "https://marianfoo.github.io/arc-1/", "github_url": "https://github.com/arc-mcp/arc-1", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "sap", "abap", "adt", "enterprise", "code-checks", "transport-management", "git", "developer-tools" ], "use_cases": [ "Perform SAP ABAP code checks, build and activate operations through AI assistants connected to ARC-1 MCP with governed access controls that audit every tool call and enforce package allowlists for write operations", "Enable enterprise SAP development teams to use Claude or GitHub Copilot for AI-assisted ABAP authoring through ARC-1 MCP while maintaining full transport management, per-user authorization scoping and layered rate limiting", "Build AI-powered SAP development workflows where agents interact with ABAP systems through ARC-1 MCP using ADT REST APIs for code review, refactoring and documentation with default-deny security posture and complete audit trail" ], "health": "active" }, { "id": "entroly-mcp", "name": "Entroly MCP Server", "description": "Context engineering engine for AI coding agents that provides information-theoretic context optimization reducing unnecessary tokens by up to 90 percent while preserving answer-critical evidence. Features budget-aware selection, content-addressed recovery and auditable Context Receipts. Rust engine runs in under 10 milliseconds. Supports Claude Code, Codex and OpenClaw. Provides recoverable context compression, answer verification and full MCP integration for auditable context engineering.", "category": "code", "endpoint": "https://entroly.dev", "homepage_url": "https://skillsllm.com/skill/entroly", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "context-engineering", "token-optimization", "developer-tools", "coding-agents", "rust", "compression", "performance" ], "use_cases": [ "Reduce context window consumption by up to 90 percent in AI coding agents like Claude Code and Codex through Entroly MCP which applies information-theoretic optimization to select only answer-critical evidence from large codebases", "Enable coding agent workflows with auditable context engineering through Entroly MCP which generates cryptographic Context Receipts that verify what context was provided to the AI and what was compressed or excluded", "Build token-efficient AI development pipelines where Entroly MCP acts as a context preprocessing layer through MCP, applying budget-aware selection with sub-10ms Rust performance to keep large codebase interactions within context limits" ], "health": "active" }, { "id": "headless-oracle-mcp", "name": "Headless Oracle MCP Server", "description": "Signed market-state oracle that gives AI agents a verified pre-trade gate. Before any trade or capital commitment, agents fetch an Ed25519-signed receipt confirming the exchange is OPEN. Covers 28 exchanges with 60-second TTL on signed receipts. Fills a gap in the agent data stack by providing verified metadata about whether trading is currently possible, complementing data providers like OpenBB. Available on the Official MCP Registry.", "category": "data", "endpoint": "https://headlessoracle.com/mcp", "homepage_url": "https://headlessoracle.com", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "finance", "trading", "market-data", "exchange-status", "cryptographic-verification", "pre-trade", "oracle" ], "use_cases": [ "Add a verified pre-trade gate to financial AI agents through Headless Oracle MCP which provides Ed25519-signed receipts confirming exchange open and close status across 28 exchanges before any trade execution", "Enable trading agent frameworks to check real-time exchange availability through Headless Oracle MCP with cryptographically signed receipts that expire after 60 seconds, preventing agents from attempting trades on closed markets", "Build compliant autonomous trading workflows where agents query Headless Oracle through MCP as a mandatory pre-trade check, receiving verifiable exchange state data that can be logged and audited for regulatory purposes" ], "health": "active" }, { "id": "fcp-mcp", "name": "FCP MCP Server", "description": "The most capable MCP server for Final Cut Pro with 88 tools covering three layers: FCPXML engine with 49 tools for timeline editing, live FCP control via AppleScript with 20 tools, media analysis via ffprobe with 10 tools, plus parametric puppets with 7 tools and Compressor dispatch with 2 tools. Enables AI assistants to analyze timelines, perform QC validation, edit clips, generate rough cuts, sync beats and import SRT transcripts. Works with Claude, Cursor and other MCP-compatible clients on macOS.", "category": "media", "endpoint": "https://github.com/dreliq9/fcp-mcp", "homepage_url": "https://www.pulsemcp.com/servers/dreliq9-fcp", "github_url": "https://github.com/dreliq9/fcp-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "final-cut-pro", "video-editing", "fcpxml", "media", "macos", "creative", "timeline", "applescript" ], "use_cases": [ "Control Final Cut Pro timelines through AI assistants connected via FCP MCP with 88 tools covering FCPXML editing, live FCP control via AppleScript, media analysis via ffprobe and parametric puppets for automated video production", "Enable video editors to analyze timelines, perform QC validation, generate rough cuts and sync beats through Claude or Cursor connected to FCP MCP instead of manually performing repetitive editing tasks in Final Cut Pro", "Build AI-powered post-production workflows where agents use FCP MCP through MCP to import SRT transcripts, edit clips based on natural language instructions, dispatch Compressor jobs and manage complex multi-track timelines programmatically" ], "health": "active" }, { "id": "onui-mcp", "name": "onUI MCP Server", "description": "UI annotation MCP server that lets users annotate and draw on any web UI for AI agents and export structured context without requiring app code changes. Lightweight browser extension for Chrome, Edge and Firefox combined with a local MCP bridge. Provides two capture modes: annotate mode for element-level fixes and draw mode for layout or spacing regions. Four output formats from compact to forensic. All data stays local and never leaves the device. Open source.", "category": "code", "endpoint": "https://onui.onllm.dev", "homepage_url": "https://onui.onllm.dev/", "github_url": "https://github.com/onllm-dev/onUI", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "ui-annotation", "browser-extension", "web-development", "design", "frontend", "local-first", "developer-tools", "accessibility" ], "use_cases": [ "Annotate web UI elements and regions directly in the browser through onUI and feed structured context to AI coding agents via MCP for precise element-level fixes without sharing screenshots or writing CSS selectors manually", "Enable frontend developers to draw on layout regions and batch-select UI elements through onUI browser extension and have AI agents read fresh annotations via onUI MCP tools for iterative UI pair programming with visual context", "Build AI-powered web design review workflows where designers annotate issues on live sites through onUI and AI agents process the structured annotations via MCP with forensic-level detail including element metadata and computed styles" ], "health": "active" }, { "id": "skillboss-mcp", "name": "SkillBoss MCP Server", "description": "MCP server and Claude Code skills platform from HeyBoss that provides access to 100 plus AI services including LLMs, image and video generation and text-to-speech through a single OpenAI-compatible API key. Equips Claude Code, Codex, Cursor, Windsurf, OpenClaw and other agent platforms with production-ready capabilities for content generation, application building, product deployment and workflow automation. Unified modular skills layer that helps AI agents move beyond text and reliably execute real-world tasks at scale.", "category": "ai", "endpoint": "https://skillboss.ai", "homepage_url": "https://github.com/SkillBoss-AI/skillboss-skills", "github_url": "https://github.com/SkillBoss-AI/skillboss-skills", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-08-14", "updated": "2026-08-14", "tags": [ "ai-services", "llm", "image-generation", "video-generation", "tts", "multi-model", "skills", "unified-api" ], "use_cases": [ "Access 100 plus AI services including LLMs, image generation, video generation and text-to-speech through a single MCP connection in Claude Code, Codex or Cursor via SkillBoss instead of configuring separate API keys and integrations for each service", "Enable AI coding agents to generate images, create videos, synthesize speech and call multiple LLM providers through SkillBoss MCP with a unified OpenAI-compatible API key for production content creation workflows", "Build multi-modal AI agent workflows where SkillBoss MCP provides a unified skills layer through MCP giving agents access to the full spectrum of generative AI services for automated content production, application building and deployment" ], "health": "active" }, { "id": "nutanix-ncp-mcp", "name": "Nutanix Cloud Platform MCP Server", "description": "Open-source MCP server from Nutanix that enables AI agents and developer tools to interact with Nutanix Cloud Platform through the Prism v4 API. Allows customers to automate daily cloud operations using natural language through AI assistants like Claude and ChatGPT. Supports VM lifecycle management, cluster monitoring, storage operations and infrastructure provisioning with built-in security and governance. Released as v0.8 technical preview. Written in Python. Announced August 10, 2026.", "category": "infrastructure", "endpoint": "https://github.com/nutanix/ntnx-api-mcp-server", "homepage_url": "https://www.globenewswire.com/news-release/2026/08/10/3341000/0/en/Nutanix-Puts-Agentic-AI-into-Action-for-Enterprises.html", "github_url": "https://github.com/nutanix/ntnx-api-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "cloud", "infrastructure", "hybrid-cloud", "virtualization", "nutanix", "devops", "enterprise", "open-source" ], "use_cases": [ "Automate Nutanix Cloud Platform operations including VM provisioning, cluster monitoring and storage management through AI assistants connected via MCP using natural language instead of navigating the Prism dashboard", "Enable IT operations teams to query infrastructure health, capacity utilization and alert status across Nutanix hybrid cloud environments through Claude or ChatGPT connected to the Nutanix MCP server", "Build AI-powered infrastructure automation workflows where agents provision VMs, manage snapshots and configure networking on Nutanix Cloud Platform through the Prism v4 API via MCP" ], "health": "active" }, { "id": "mongodb-atlas-managed-mcp", "name": "MongoDB Atlas Managed MCP Server", "description": "Fully hosted MCP server from MongoDB that connects AI agents to live MongoDB Atlas operational data. Enables Claude Code, Codex, Devin and other MCP-compatible coding agents to query live Atlas databases, inspect schemas, run aggregations and interact with operational data without local setup or self-hosting. Managed by MongoDB with automatic scaling and security. Designed for the agentic coding stack where AI developers need real-time database context. Announced August 13, 2026.", "category": "data", "endpoint": "https://cloud.mongodb.com", "homepage_url": "https://www.mongodb.com/blog/post/mongodb-atlas-managed-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "database", "mongodb", "atlas", "managed", "nosql", "developer-tools", "coding", "enterprise" ], "use_cases": [ "Query live MongoDB Atlas databases directly from AI coding agents like Claude Code, Codex or Devin through the managed MCP server without local database drivers or connection string management", "Enable development teams to inspect collection schemas, run aggregation pipelines and explore operational data through AI assistants connected to MongoDB Atlas via the managed MCP server for faster debugging and development", "Build AI-powered data exploration workflows where coding agents query production MongoDB data, analyze schema patterns and generate data-driven code with real-time database context via MCP" ], "health": "active" }, { "id": "xnurta-mcp", "name": "Xnurta MCP Server", "description": "MCP server from Xnurta, the award-winning agentic AI-powered retail media advertising platform. Connects Xnurta retail media data with AI assistants and enterprise AI platforms including ChatGPT and Claude. Enables advertisers to query campaign performance, analyze retail media spend, access keyword intelligence and manage advertising operations through natural language. Designed for brands and agencies running retail media campaigns across Amazon, Walmart and other marketplaces. Announced August 13, 2026.", "category": "data", "endpoint": "https://www.xnurta.com", "homepage_url": "https://www.businesswire.com/news/home/20260813360711/en/Xnurta-Launches-MCP-for-Retail-Media-With-AI-Powered-Campaign-Management-Entering-Beta-the-Same-Day", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "advertising", "retail-media", "ecommerce", "campaign-management", "analytics", "marketing", "amazon", "walmart" ], "use_cases": [ "Query retail media campaign performance, keyword rankings and advertising spend across Amazon, Walmart and other marketplaces through AI assistants connected to Xnurta via MCP using natural language", "Enable advertising teams and agencies to analyze retail media trends, optimize bids and review campaign metrics through Claude or ChatGPT connected to the Xnurta MCP server without switching to the Xnurta dashboard", "Build AI-powered retail media workflows where agents monitor campaign performance, identify optimization opportunities and generate advertising reports using Xnurta data via MCP" ], "health": "active" }, { "id": "cisco-meraki-mcp", "name": "Cisco Meraki MCP Server", "description": "Beta MCP server from Cisco that provides read-only access to Meraki network data for AI agents and applications. Enables AI assistants to query network device status, organization details, client information and network health directly through the Model Context Protocol. Designed for network administrators and IT teams building AI-powered networking experiences. Supports read-only operations with OAuth-based authentication. Part of Cisco's broader agentic networking strategy. Announced August 11, 2026.", "category": "infrastructure", "endpoint": "https://developer.cisco.com/meraki/mcp/", "homepage_url": "https://blogs.cisco.com/developer/build-agentic-networking-experiences-with-meraki-and-catalyst-center-mcp-servers", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "networking", "cisco", "meraki", "network-management", "enterprise", "infrastructure", "monitoring", "beta" ], "use_cases": [ "Query Meraki network device status, client counts and organization details through AI assistants connected to the Cisco Meraki MCP server using natural language instead of navigating the Meraki dashboard", "Enable network administrators to monitor network health, troubleshoot connectivity issues and review device inventory across Meraki-managed networks through Claude or other MCP-compatible AI tools", "Build AI-powered network operations workflows where agents aggregate Meraki network data with other infrastructure sources to provide unified visibility across enterprise networking environments via MCP" ], "health": "active" }, { "id": "cisco-catalyst-center-mcp", "name": "Cisco Catalyst Center MCP Server", "description": "Beta MCP server from Cisco that provides read-only access to Catalyst Center network management data for AI agents and applications. Enables AI assistants to query campus and branch network infrastructure, device inventory, network health scores and issue summaries through the Model Context Protocol. Designed for enterprise network teams managing Catalyst-based infrastructure with AI-powered operations. Supports read-only operations with OAuth-based authentication. Part of Cisco's agentic networking initiative alongside the Meraki MCP server. Announced August 11, 2026.", "category": "infrastructure", "endpoint": "https://developer.cisco.com/catalyst-center/mcp/", "homepage_url": "https://blogs.cisco.com/developer/build-agentic-networking-experiences-with-meraki-and-catalyst-center-mcp-servers", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "networking", "cisco", "catalyst", "network-management", "enterprise", "infrastructure", "campus-network", "beta" ], "use_cases": [ "Query Catalyst Center network health scores, device inventory and issue summaries through AI assistants connected via MCP using natural language instead of navigating the Catalyst Center dashboard", "Enable enterprise network teams to monitor campus and branch network infrastructure health, identify issues and review device status across Catalyst-managed networks through Claude or other MCP-compatible AI tools", "Build AI-powered enterprise network operations workflows where agents combine Catalyst Center data with other infrastructure sources to provide comprehensive network visibility and automated issue detection via MCP" ], "health": "active" }, { "id": "fuel50-mcp", "name": "Fuel50 MCP Server", "description": "MCP server from Fuel50, the AI-powered talent marketplace and skills intelligence platform. Brings trusted skills ontology and workforce intelligence data into any AI agent experience through the Model Context Protocol. Enables HR teams and enterprise AI platforms to query skills taxonomies, career pathways, talent profiles and workforce analytics through natural language. Designed to provide consistent skills context across enterprise AI workflows. Announced August 7, 2026.", "category": "data", "endpoint": "https://www.fuel50.com", "homepage_url": "https://www.einpresswire.com/article/fuel50-launches-mcp-server-to-bring-trusted-skills-intelligence-into-every-ai-agent-experience", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-15", "updated": "2026-08-15", "tags": [ "hr", "skills", "talent-management", "workforce", "career-development", "enterprise", "human-resources", "skills-intelligence" ], "use_cases": [ "Query skills taxonomies, career pathways and workforce intelligence through AI assistants connected to Fuel50 via MCP using natural language for talent management and workforce planning", "Enable HR teams and people analytics platforms to access Fuel50 skills ontology data through Claude or other MCP-compatible AI tools for consistent skills context across enterprise AI workflows", "Build AI-powered workforce development workflows where agents map employee skills, identify career progression opportunities and generate talent insights using Fuel50 intelligence data via MCP" ], "health": "active" }, { "id": "pdq-mcp", "name": "PDQ MCP Server", "description": "Early-access MCP server from PDQ that connects supported AI tools including Claude, Microsoft Copilot and VS Code to PDQ endpoint-management capabilities. Lets IT teams investigate endpoint health, answer operational questions, generate reports, trigger software deployments and build automations while preserving PDQ administrator-defined permissions, OAuth authentication and audit logging. Announced August 12, 2026.", "category": "infrastructure", "endpoint": "https://www.pdq.com", "homepage_url": "https://www.pdq.com/blog/pdq-launches-mcp-server-to-bring-secure-ai-workflows-to-endpoint-management/", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "endpoint-management", "it-operations", "patch-management", "software-deployment", "windows", "macos", "sysadmin", "early-access" ], "use_cases": [ "Ask an AI assistant to find devices missing specific software, devices that have not checked in recently, or endpoints still running unsupported operating systems using PDQ data through MCP", "Trigger approved PDQ deployments and generate operational reports from Claude, Copilot, VS Code or another MCP-compatible client while preserving administrator-defined permissions and audit logs", "Build IT automation workflows that combine endpoint inventory, patch status, vulnerability remediation and deployment actions through a governed PDQ MCP connection" ], "health": "active" }, { "id": "dash-social-mcp", "name": "Dash Social MCP Integration", "description": "MCP integration from Dash Social that brings proprietary brand intelligence, social performance data, community insights, listening data, competitive benchmarking and Vision AI context into AI assistants such as ChatGPT and Claude. Designed so marketers can build reports, monitor brand health, ground competitive research, fill content calendars and connect brand data to workflows while retaining authentication and permission controls. Announced August 13, 2026.", "category": "data", "endpoint": "https://dashsocial.com", "homepage_url": "https://www.manilatimes.net/2026/08/13/tmt-newswire/globenewswire/dash-social-launches-mcp-to-make-brand-intelligence-accessible-across-ai/2405027", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "marketing", "brand-intelligence", "social-media", "analytics", "competitive-intelligence", "content-calendar", "vision-ai", "enterprise" ], "use_cases": [ "Populate marketing decks and reports with current Dash Social performance data through an AI assistant connected by MCP", "Monitor brand health, mention volume and sentiment shifts while grounding AI recommendations in a brand's own social, community and competitive data", "Use AI workflows to identify content-calendar gaps, pull assets from a connected CMS and draft or schedule brand-consistent social content using Dash Social context" ], "health": "active" }, { "id": "flespi-mcp", "name": "flespi MCP Server", "description": "MCP server for flespi, the telematics and IoT platform, with Realm-based OAuth support for connecting Claude and ChatGPT without manually sharing a dedicated flespi token. Exposes account, device and platform operations through realm public MCP endpoints, with authorization handled through flespi Realms and ACL access such as POST ai/mcp. OAuth connection guide published August 14, 2026.", "category": "infrastructure", "endpoint": "https://flespi.com", "homepage_url": "https://flespi.com/blog/flespi-mcp-server-oauth-authentication-with-realms", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "iot", "telematics", "fleet", "devices", "oauth", "realms", "claude", "chatgpt" ], "use_cases": [ "Connect Claude or ChatGPT to a flespi realm so an AI assistant can answer questions about account state, devices and telematics data without copying tokens into prompts", "Enable realm-scoped MCP access for support or development endpoints while using flespi ACLs to control which users can invoke AI/MCP operations", "Build telematics automation workflows where agents inspect devices, channels or account configuration through flespi's MCP endpoint using OAuth authorization" ], "health": "active" }, { "id": "openanalytics-mcp", "name": "OpenAnalytics MCP Server", "description": "Open-source, privacy-first and cookieless web analytics platform with revenue attribution and an MCP surface in its API layer. Provides a self-hostable alternative to Google Analytics with collector, worker, query gateway, realtime dashboard, CLI, revenue metrics, sharing, funnels and AI assistant/MCP integration. Public GitHub repository created August 11, 2026.", "category": "data", "endpoint": "https://github.com/OpenLabs-so/openanalytics", "homepage_url": "https://getopen.so", "github_url": "https://github.com/OpenLabs-so/openanalytics", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "analytics", "web-analytics", "privacy", "cookieless", "self-hosted", "revenue-attribution", "clickhouse", "typescript" ], "use_cases": [ "Query privacy-first website analytics, visitor trends, funnels and revenue attribution from AI assistants connected to an OpenAnalytics deployment through MCP", "Let product and growth teams ask natural-language questions about traffic, referrers, top pages and conversion data without exposing visitors to cross-site tracking", "Self-host an analytics stack whose API layer can expose selected metrics and AI assistant capabilities through MCP for internal reporting workflows" ], "health": "active" }, { "id": "datasentry-mcp", "name": "DataSentry MCP Server", "description": "Local-first AI copilot for data quality with MCP, REST, CLI and web interfaces. Scans CSV, Parquet, JSONL, XLSX, DuckDB, SQLite, PostgreSQL, MySQL and cloud-object data; applies 39 evidence-driven detectors; scores data across six quality dimensions; supports drift detection and AI-suggested repairs gated by human approval. Public GitHub repository created August 9, 2026.", "category": "data", "endpoint": "https://github.com/Jackxiaozhiren/datasentry", "homepage_url": "https://github.com/Jackxiaozhiren/datasentry", "github_url": "https://github.com/Jackxiaozhiren/datasentry", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install datasentry-ai", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "data-quality", "data-observability", "etl", "duckdb", "local-first", "data-cleaning", "ai-copilot", "python" ], "use_cases": [ "Run local data-quality scans from an AI assistant and receive evidence-backed issue reports with samples, ratios, confidence and six-dimension quality scores", "Use MCP to let agents inspect detected data issues, propose repair rules and preview changes while requiring human approval before any repair is applied", "Monitor schema, row-count, score and issue-distribution drift across repeated scans in data engineering or analytics workflows" ], "health": "active" }, { "id": "alertchecker-mcp", "name": "AlertChecker MCP Server", "description": "Hosted MCP server for AlertChecker that lets ChatGPT, Claude and other MCP clients create AI-monitored web alerts from plain-English statements. Users can ask to be notified when a condition becomes true, such as a price drop, stock availability, weather condition, stock-price threshold or earthquake event. Uses streamable HTTP with OAuth 2.0, PKCE and dynamic client registration. Public GitHub repository created August 9, 2026.", "category": "web", "endpoint": "https://alertchecker.com/api/mcp", "homepage_url": "https://github.com/steve-chambers/alertchecker-mcp", "github_url": "https://github.com/steve-chambers/alertchecker-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "alerts", "monitoring", "web-monitoring", "oauth", "pkce", "chatgpt", "claude", "notifications" ], "use_cases": [ "Create plain-English web alerts from an AI assistant, such as monitoring inventory, prices, weather, earthquakes or financial thresholds", "Connect an MCP client to AlertChecker over streamable HTTP using OAuth and PKCE instead of manually copying API keys", "Let agents turn a user request like alert me when this becomes true into a persistent monitored condition with email notification" ], "health": "active" }, { "id": "chile-bcn-mcp", "name": "Chile BCN MCP Server", "description": "Community MCP server that gives AI assistants direct access to Chilean laws, decrees and resolutions from LeyChile, the legal database of the Biblioteca del Congreso Nacional de Chile. Written in Go using the official MCP Go SDK and designed to return legal content in Markdown optimized for LLM consumption. Supports containerized HTTP deployment and native or container-launched stdio usage. Public GitHub repository created August 14, 2026.", "category": "data", "endpoint": "https://github.com/alvarosdev/chile-bcn-mcp", "homepage_url": "https://github.com/alvarosdev/chile-bcn-mcp", "github_url": "https://github.com/alvarosdev/chile-bcn-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "legal", "chile", "leychile", "government-data", "laws", "markdown", "go", "self-hosted" ], "use_cases": [ "Ask an AI assistant to search and retrieve Chilean laws, decrees and resolutions from LeyChile through an MCP server instead of copying legal text manually", "Self-host a legal research connector that returns statute and decree content in Markdown formatted for LLM analysis and citation workflows", "Use AI agents to compare Chilean legal documents or answer legal-research questions with source material pulled from the public BCN/LeyChile API" ], "health": "active" }, { "id": "personalknowhow-mcp", "name": "PersonalKnowHow MCP Servers", "description": "Personal knowledge-graph project that turns LinkedIn, GitHub, course history, Gmail completion emails and related project repositories into a queryable evidence graph served over real deployed MCP servers. Uses semantic search so Claude Desktop and other MCP-aware clients can answer questions about a person's experience with citations and similarity scores. Public GitHub repository created August 14, 2026.", "category": "productivity", "endpoint": "https://personalknowhow-demo.kxtwrdzt6g.workers.dev/mcp", "homepage_url": "https://github.com/Georgi-Petkov/personalknowhow", "github_url": "https://github.com/Georgi-Petkov/personalknowhow", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "npx mcp-remote https://personalknowhow-demo.kxtwrdzt6g.workers.dev/mcp", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "knowledge-graph", "personal-knowledge", "semantic-search", "career", "linkedin", "github", "rag", "cloudflare-workers" ], "use_cases": [ "Ask Claude or another MCP client evidence-backed questions about a person's skills, projects, courses and experience using a semantic personal knowledge graph", "Build career or portfolio assistants that cite primary evidence from LinkedIn, GitHub, course records and project repositories instead of relying on self-reported summaries", "Expose a private or demo personal-knowledge dataset as an MCP tool that returns matched evidence and similarity scores for agent workflows" ], "health": "active" }, { "id": "mcp-fleaflicker", "name": "Fleaflicker MCP Server", "description": "Read-only MCP server for Fleaflicker fantasy leagues. Reads rosters, standings, matchups, boxscores, draft boards and league rules, then scores stat lines using each league's own published scoring configuration instead of hardcoded presets. Fleaflicker's read API is public and unauthenticated, so the server requires no API key, stores no credentials and cannot change a league. Public GitHub repository created August 13, 2026.", "category": "data", "endpoint": "https://github.com/pete-builds/mcp-fleaflicker", "homepage_url": "https://github.com/pete-builds/mcp-fleaflicker", "github_url": "https://github.com/pete-builds/mcp-fleaflicker", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "fantasy-football", "sports", "nfl", "fleaflicker", "scoring", "read-only", "python", "league-data" ], "use_cases": [ "Ask an AI assistant to inspect Fleaflicker league standings, rosters, matchups, boxscores and draft boards without giving it write access", "Score hypothetical or actual stat lines using a league's own published scoring rules rather than generic fantasy-football presets", "Build fantasy football research workflows where agents compare matchups, verify scoring edge cases and explain league-specific rule effects" ], "health": "active" }, { "id": "snapwonders-mcp", "name": "snapWONDERS MCP Server", "description": "Official local MCP server for the snapWONDERS API that lets an AI assistant work with files on the user's own machine. Supports hiding files inside images, revealing hidden content, forensic analysis, media analysis and file-format conversion by reading local file paths, uploading to snapWONDERS over HTTPS and writing results back to disk. Requires a snapWONDERS API key. Public GitHub repository created August 16, 2026.", "category": "media", "endpoint": "https://github.com/snapWONDERS/snapWONDERS-MCP", "homepage_url": "https://www.snapwonders.com/", "github_url": "https://github.com/snapWONDERS/snapWONDERS-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx snapwonders-mcp", "added": "2026-08-16", "updated": "2026-08-16", "tags": [ "media", "steganography", "forensics", "file-conversion", "image-analysis", "video-forensics", "local-files", "python" ], "use_cases": [ "Let Claude Desktop or another MCP client hide a local file inside a photo, reveal hidden content or convert media formats while returning output paths on disk", "Run forensic or media-analysis workflows where an agent can pass local files to snapWONDERS through a local stdio MCP bridge", "Use a local MCP server to bridge file bytes from the user's machine to the snapWONDERS HTTPS API because remote MCP calls alone cannot access desktop file paths" ], "health": "active" }, { "id": "fl-studio-mcp", "name": "FL Studio MCP", "description": "MCP server that lets AI assistants control FL Studio through a FastMCP stdio server paired with an FL Studio controller script. Exposes transport, mixer, channel rack, plugins, patterns, step sequencer, piano roll, playlist, project metadata, markers and raw FL scripting API access over a virtual MIDI trigger plus JSON command channel. Public GitHub repository created August 15, 2026.", "category": "media", "endpoint": "https://github.com/Zierax/fl-studio-mcp", "homepage_url": "https://github.com/Zierax/fl-studio-mcp", "github_url": "https://github.com/Zierax/fl-studio-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "fl-studio", "music-production", "daw", "midi", "plugins", "piano-roll", "step-sequencer", "python" ], "use_cases": [ "Let an AI assistant inspect and modify an FL Studio project, including mixer levels, patterns, channels, notes, plugin parameters and playlist tracks", "Automate DAW workflows such as creating patterns, adding chords, editing step sequences, setting tempo and controlling transport from an MCP client", "Bridge FL Studio scripting API operations into Claude, Cursor or another assistant without manually writing controller scripts for each operation" ], "health": "active" }, { "id": "repository-memory-mcp", "name": "Repository Memory MCP Server", "description": "Standalone repository-memory layer with a citation-first repository index, CLI, local SQLite store, local stdio MCP server and L0-L3 conversation memory runtime for AI agents. Designed so agents can answer questions about project documents, source files, reports and imported conversation memory only when they can cite the repository evidence or stored memory source. Public GitHub repository created August 10, 2026.", "category": "productivity", "endpoint": "https://github.com/LeslieWylie/repository-memory", "homepage_url": "https://github.com/LeslieWylie/repository-memory", "github_url": "https://github.com/LeslieWylie/repository-memory", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "repository-memory", "citations", "sqlite", "retrieval", "agent-memory", "skills", "local-first", "python" ], "use_cases": [ "Give coding agents a source-backed memory layer that returns answers with commit, path and line citations instead of unsupported recollections", "Index project documents, research notes and source-code evidence into a local SQLite-backed MCP server for Claude, Codex or other MCP clients", "Maintain optional team or conversation memory separately from Git citations while keeping indexes, snapshots and credentials outside the source repository" ], "health": "active" }, { "id": "codesamplex-mcp", "name": "CodeSampleX MCP Server", "description": "Local-first distributed reasoning cache for coding LLMs that collects anonymous compatibility evidence from real environments and verified minimal code samples for public packages, symbols and versions. Works with Claude Code, Codex, Gemini CLI, OpenCode and other MCP clients to reduce repeated library-compatibility rediscovery. Public GitHub repository created August 13, 2026.", "category": "code", "endpoint": "https://github.com/r2cuerdame/CodeSampleX", "homepage_url": "https://codesamplex.dev", "github_url": "https://github.com/r2cuerdame/CodeSampleX", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "code-samples", "compatibility", "developer-tools", "llm-tools", "npm", "pypi", "cargo", "golang" ], "use_cases": [ "Ask an AI coding assistant whether a specific library symbol works for a package version, runtime, package manager and operating-system combination", "Reuse verified minimal samples and sandbox receipts instead of repeatedly debugging the same dependency compatibility issue", "Contribute privacy-safe compatibility evidence and wanted tuples when no safe match exists for a coding-agent request" ], "health": "active" }, { "id": "popmely-mt5-mcp", "name": "popmely MT5 MCP Server", "description": "Production-oriented MetaTrader 5 MCP server exposing market data, Smart Money Concepts analysis, backtesting, risk scoring, position lifecycle management, automated strategy execution, SQLite memory, TradingView charts and live streaming console support. The README documents JSON-RPC stdio and SSE transports for Claude Desktop, Antigravity, Cursor and OpenAI Agents. Public GitHub repository created August 16, 2026.", "category": "data", "endpoint": "https://github.com/JonusNattapong/popmely", "homepage_url": "https://github.com/JonusNattapong/popmely", "github_url": "https://github.com/JonusNattapong/popmely", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "metatrader5", "forex", "trading", "backtesting", "risk-management", "smart-money-concepts", "sqlite", "python" ], "use_cases": [ "Let an assistant inspect MT5 market data, run SMC structure analysis and generate backtests using an MCP tool surface", "Apply risk gates such as lot-size caps, stop-loss constraints, daily drawdown limits and trading credit score rules before position actions", "Build trading research workflows that combine price feeds, chart context, SQLite memory, backtesting metrics and position lifecycle operations" ], "health": "active" }, { "id": "eip-mcp", "name": "Exploit Intelligence Platform MCP Server", "description": "Official read-only MCP server for the Exploit Intelligence Platform, giving AI assistants bounded source-attributed access to vulnerability intelligence, exploit artifacts, readable PoC source, Docker labs, discovery directories, STIX data and corpus statistics. Offers a hosted streamable HTTP endpoint at exploit-intel.com/mcp and an optional local Python package. Public GitHub repository created August 13, 2026.", "category": "data", "endpoint": "https://exploit-intel.com/mcp", "homepage_url": "https://github.com/exploitintel/eip-mcp", "github_url": "https://github.com/exploitintel/eip-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "pipx install eip-mcp", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "vulnerability-intelligence", "security", "cve", "exploit", "stix", "docker-labs", "read-only", "python" ], "use_cases": [ "Ask an assistant for source-attributed vulnerability and exploit-intelligence context without allowing the tool to execute or download acquired content", "Connect directly to the hosted streamable HTTP MCP endpoint to query corpus readiness, CVE context, PoC source and Docker lab metadata", "Use local stdio mode through the eip-mcp Python package when a client cannot connect to remote MCP servers" ], "health": "active" }, { "id": "obsidian-remote-mcp", "name": "Obsidian Remote MCP Server", "description": "Remote Obsidian MCP wrapper that exposes an Obsidian vault over OAuth 2.1 for Claude.ai custom connectors and Claude Code without requiring Obsidian to be running or the vault to be present on the client machine. Uses a server-side vault sync, obsidian-mcp, supergateway, an OAuth auth server, nginx and optionally Cloudflare Tunnel. Public GitHub repository created August 12, 2026.", "category": "productivity", "endpoint": "https://github.com/rollecode/obsidian-remote-mcp", "homepage_url": "https://github.com/rollecode/obsidian-remote-mcp", "github_url": "https://github.com/rollecode/obsidian-remote-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "obsidian", "notes", "knowledge-management", "oauth", "pkce", "cloudflare-tunnel", "vault", "javascript" ], "use_cases": [ "Reach an Obsidian vault from Claude.ai or Claude Code when the local machine does not have the vault or Obsidian app running", "Serve multiple synced vaults behind a remote MCP connector protected by OAuth 2.1, PKCE, dynamic client registration and refresh-token rotation", "Combine a static bearer token and OAuth flow so local coding clients and web connectors can access the same vault service" ], "health": "active" }, { "id": "dados-b3-mcp", "name": "Dados B3 MCP Server", "description": "MCP connector for Brazilian public-company fundamentals covering 400+ B3-listed companies from 2010 onward, including banks and insurers. Exposes ROE, ROIC, margins, growth, net debt to EBITDA, point-in-time valuation multiples, dividends, dividend yield, Piotroski F-Score, Graham scores and restatement history, with public CVM and B3 data methodology. Public GitHub repository created August 11, 2026.", "category": "data", "endpoint": "https://dadosb3.com/mcp/", "homepage_url": "https://github.com/Val7h/dados-b3-mcp", "github_url": "https://github.com/Val7h/dados-b3-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "brazil", "b3", "financial-data", "fundamental-analysis", "stocks", "cvm", "valuation", "python" ], "use_cases": [ "Ask an AI assistant for auditable Brazilian equity fundamentals, valuation multiples and dividend data sourced from CVM and B3 datasets", "Run investment-screening or backtest research that avoids look-ahead bias by using point-in-time prices after real balance-sheet publication dates", "Compare banks, insurers and other B3 companies using ready-made Piotroski F-Score, Graham scores, margins, ROE, ROIC and restatement history" ], "health": "active" }, { "id": "ferumind-mcp", "name": "Ferumind MCP Server", "description": "Self-hosted Markdown memory workspace for AI chats with a stateless MCP server for project scoping, retrieval, guarded edits, snapshots and auditable change history. Designed for local clients over stdio and for ChatGPT developer-mode connections through the OpenAI Secure MCP Tunnel so the user's documents remain on their own machine. Public GitHub repository created August 15, 2026.", "category": "productivity", "endpoint": "https://github.com/MetaphoricalSheep/ferumind", "homepage_url": "https://github.com/MetaphoricalSheep/ferumind", "github_url": "https://github.com/MetaphoricalSheep/ferumind", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "markdown", "memory", "knowledge-management", "self-hosted", "snapshots", "chatgpt", "sqlite", "python" ], "use_cases": [ "Maintain a readable Markdown memory workspace shared between a user and AI agents while preserving auditable snapshots of guarded edits", "Connect local MCP clients such as Claude Code, Claude Desktop or Cursor to scoped project memory without publishing the workspace to the internet", "Use the OpenAI Secure MCP Tunnel path for ChatGPT developer-mode access while keeping the MCP server and documents on the user's machine" ], "health": "active" }, { "id": "puntersedge-mcp", "name": "PuntersEdge MCP Server", "description": "MCP server for the PuntersEdge Australian odds API, bringing live Australian racing and sports odds from 12 sources including 11 bookmakers and Betfair Exchange into Claude, ChatGPT, Cursor and other MCP clients. Provides next-to-go racing, side-by-side runner prices, price ages, sports markets and account/credit visibility. Public GitHub repository created August 17, 2026.", "category": "data", "endpoint": "https://github.com/Propertyscout001/puntersedge-mcp", "homepage_url": "https://puntersedge.online/api-platform", "github_url": "https://github.com/Propertyscout001/puntersedge-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g puntersedge-mcp", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "australia", "racing", "sports-odds", "bookmakers", "betfair", "horse-racing", "api-key", "javascript" ], "use_cases": [ "Ask an assistant for the next Australian races and compare each runner's prices across bookmakers with freshness metadata", "Research live sports and racing markets from an MCP client using a PuntersEdge API key without manually calling the odds API", "Track account credit usage and understand data coverage limits while keeping arbitrage and unavailable endpoints out of the tool surface" ], "health": "active" }, { "id": "storepilot-mcp", "name": "StorePilot MCP Server", "description": "MCP server for managing a whole app portfolio across Google Play and App Store Connect, with tools for vitals, reviews, installs, earnings, releases, metadata, cross-store parity and portfolio health. Read paths target real developer accounts; write paths are designed to preview first and wait for human confirmation. Public GitHub repository created August 17, 2026.", "category": "productivity", "endpoint": "https://github.com/sonlenef/storepilot-mcp", "homepage_url": "https://github.com/sonlenef/storepilot-mcp", "github_url": "https://github.com/sonlenef/storepilot-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx storepilot", "added": "2026-08-17", "updated": "2026-08-17", "tags": [ "google-play", "app-store-connect", "mobile-apps", "portfolio", "reviews", "earnings", "releases", "python" ], "use_cases": [ "Ask an assistant for a portfolio-wide view of app versions, ratings, installs, earnings, crash rates and store health across Google Play and App Store Connect", "Find listing, metadata and version drift between Play and App Store listings using cross-store parity tools", "Prepare mobile release and metadata changes through preview-first MCP write tools that require human confirmation before submitting to store APIs" ], "health": "active" }, { "id": "repo-context-mcp", "name": "repo-context-mcp", "description": "Local stdio MCP server that gives coding agents a token-aware repository map, code search and focused context packs instead of forcing them to dump whole monorepos into the prompt. It respects gitignore patterns, targets Claude Code, Codex, Cursor and other MCP clients, and can also be used from a CLI for repo maps and focused packs. Public GitHub repository created August 12, 2026.", "category": "code", "endpoint": "https://github.com/nduc99911/repo-context-mcp", "homepage_url": "https://github.com/nduc99911/repo-context-mcp", "github_url": "https://github.com/nduc99911/repo-context-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y repo-context-mcp", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "repository-context", "code-search", "context-packs", "token-aware", "claude-code", "codex", "cursor", "typescript" ], "use_cases": [ "Let a coding assistant inspect a repository structure and entrypoints without repeatedly walking vendor folders or dumping the whole repo into context", "Generate focused context packs around a feature area such as authentication, routing or tests for Claude Code, Codex, Cursor or Cline", "Use the CLI to create repo maps and search code when an MCP client is not available" ], "health": "active" }, { "id": "mcp-memory-okf", "name": "MCP-Memory", "description": "Open Knowledge Format backed MCP server for persistent long-term agent memory with project-isolated Markdown memory files, a hidden SQLite FTS5 index, provenance sources and setup automation for Claude, Cursor, Windsurf, Antigravity and Codex. Exposes tools for writing, searching, listing and reading memory while keeping storage local to the project by default. Public GitHub repository created August 13, 2026.", "category": "productivity", "endpoint": "https://github.com/fellowgeek/mcp-memory", "homepage_url": "https://github.com/fellowgeek/mcp-memory", "github_url": "https://github.com/fellowgeek/mcp-memory", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/fellowgeek/mcp-memory && cd mcp-memory && python3 setup.py", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "agent-memory", "okf", "sqlite", "fts5", "markdown", "provenance", "local-first", "python" ], "use_cases": [ "Give AI agents durable project memory backed by readable Markdown files and a SQLite search index", "Search previous notes, decisions and source-attributed memories from Claude, Cursor, Codex or another MCP client", "Keep per-project memory stores isolated while optionally configuring a global shared memory directory" ], "health": "active" }, { "id": "dataimpulse-mcp", "name": "DataImpulse MCP Proxy", "description": "Educational MCP server for safe geo-targeted web access through DataImpulse residential proxies. Instead of setting global HTTP_PROXY or HTTPS_PROXY variables, it creates a per-request proxy agent from DataImpulse credentials so other terminals, editors, package managers and MCP servers remain unaffected. Public GitHub repository created August 12, 2026.", "category": "web", "endpoint": "https://github.com/Gentleman-Programming/dataimpulse-mcp", "homepage_url": "https://github.com/Gentleman-Programming/dataimpulse-mcp", "github_url": "https://github.com/Gentleman-Programming/dataimpulse-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/Gentleman-Programming/dataimpulse-mcp.git && cd dataimpulse-mcp && npm install", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "proxies", "dataimpulse", "geo-targeting", "web-access", "residential-proxy", "nodejs", "safe-networking" ], "use_cases": [ "Let an assistant perform geo-targeted fetches through DataImpulse without poisoning the global shell proxy configuration", "Keep proxy credentials in MCP client environment variables while preventing them from being logged or returned to the model", "Test location-sensitive web pages or APIs from an AI workflow using explicit per-request proxy routing" ], "health": "active" }, { "id": "speak-aloud-mcp", "name": "speak-aloud-mcp", "description": "Small cross-platform MCP server that lets AI assistants make the local computer speak through ElevenLabs text-to-speech, with optional system volume set and restore behavior on macOS, Windows and Linux. It supports stdio for local clients, optional HTTP for remote connector scenarios, and a non-MCP Python library or CLI path for direct gateway integrations. Public GitHub repository created August 15, 2026.", "category": "media", "endpoint": "https://github.com/tsuru0805/speak-aloud-mcp", "homepage_url": "https://github.com/tsuru0805/speak-aloud-mcp", "github_url": "https://github.com/tsuru0805/speak-aloud-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install -e .", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "text-to-speech", "elevenlabs", "local-audio", "voice", "volume-control", "macos", "windows", "python" ], "use_cases": [ "Give Claude Desktop, Claude Code or another MCP client a local speak tool for audible confirmations and voice output", "Run a preflight check and direct say command before attaching the server to a client so audio issues are isolated from MCP issues", "Embed the TTS and player modules directly in a custom gateway when MCP is not the right integration layer" ], "health": "active" }, { "id": "bugboard-mcp", "name": "bugboard-mcp", "description": "Rust MCP server for 1C Bugboard that exposes projects, versions, bugs, history and related workflow actions through session-local opaque handles. It defaults to Streamable HTTP on loopback, also supports stdio, and publishes container images for Codex or other local MCP clients while warning users not to expose the unauthenticated loopback endpoint publicly. Public GitHub repository created August 12, 2026.", "category": "productivity", "endpoint": "https://github.com/bapho-bush/bugboard-mcp", "homepage_url": "https://github.com/bapho-bush/bugboard-mcp", "github_url": "https://github.com/bapho-bush/bugboard-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "docker pull ghcr.io/bapho-bush/bugboard-mcp:latest", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "bugboard", "1c", "issue-tracking", "rust", "streamable-http", "stdio", "docker", "opaque-handles" ], "use_cases": [ "Let an AI assistant search and inspect 1C Bugboard projects, versions, bugs and history from a local MCP client", "Use opaque session handles so the model does not receive raw Bugboard internal identifiers unnecessarily", "Run the server as a loopback-only HTTP container or switch to stdio for local agent workflows" ], "health": "active" }, { "id": "pexels-mcp-server", "name": "Pexels MCP Server", "description": "Production-ready unofficial MCP server for the Pexels API, giving assistants tools to search and browse stock photos and videos with compact JSON results and license-aware usage guidance. It is published as an npm package for zero-clone npx use across Claude Desktop, Claude Code, Cursor, VS Code, Windsurf and generic stdio MCP clients. Public GitHub repository created August 11, 2026.", "category": "media", "endpoint": "https://github.com/hanoak/pexels-mcp-server", "homepage_url": "https://www.npmjs.com/package/@hanoak/pexels-mcp-server", "github_url": "https://github.com/hanoak/pexels-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @hanoak/pexels-mcp-server", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "pexels", "stock-photos", "stock-video", "media-search", "npm", "license-guidance", "typescript", "api-key" ], "use_cases": [ "Search Pexels photos and videos from an MCP-aware assistant without manually visiting the Pexels web UI", "Build creative briefs, mockups and content drafts with source URLs and license-aware media metadata returned as compact JSON", "Use a zero-clone npx command to add stock media search to Claude Desktop, Claude Code, Cursor, VS Code or Windsurf" ], "health": "active" }, { "id": "pz-mcp-server", "name": "Project Zomboid MCP Server", "description": "MCP server for Project Zomboid mod development that gives coding assistants access to Build 42 Java API docs, vanilla Lua and script lookup, mod scaffolding, validation and linting. Game-file tools resolve against a local PZ_GAME_DIR when available, while scaffolding and documentation tools can still work without a local game install. Public GitHub repository created August 11, 2026.", "category": "code", "endpoint": "https://github.com/Svi-ra/pz-mcp-server", "homepage_url": "https://github.com/Svi-ra/pz-mcp-server", "github_url": "https://github.com/Svi-ra/pz-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Svi-ra/pz-mcp-server.git && cd pz-mcp-server && npm install && npm run build", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "project-zomboid", "game-modding", "lua", "javadoc", "mod-scaffolding", "linting", "nodejs", "claude-code" ], "use_cases": [ "Let a coding assistant scaffold, validate and lint Project Zomboid mods against real API documentation", "Look up vanilla Lua or script files from a local game install through sandboxed MCP tools", "Answer modding questions with Build 42 Java API docs instead of relying on stale community snippets" ], "health": "active" }, { "id": "ida-headless-mcp", "name": "IDA Headless MCP", "description": "Rust-native multi-session headless IDA Pro MCP server with one supervisor process and one IDA worker per opened database. It follows the ida-pro-mcp public contract for idb_open, idb_list, idb_close and worker analysis tools, supports stdio or Streamable HTTP, and requires a separately licensed local IDA install. Public GitHub repository created August 16, 2026.", "category": "code", "endpoint": "https://github.com/fuqiuluo/ida-headless-mcp", "homepage_url": "https://github.com/fuqiuluo/ida-headless-mcp", "github_url": "https://github.com/fuqiuluo/ida-headless-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "cargo build --release --no-default-features --features ida-92", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "ida-pro", "reverse-engineering", "binary-analysis", "headless", "rust", "streamable-http", "multi-session", "security-research" ], "use_cases": [ "Let an AI assistant open multiple IDA databases and query analysis tools through opaque database session IDs", "Run reverse-engineering workflows from Claude Code, Codex or Cursor while keeping the IDA GUI profile isolated", "Use optional unsafe tools only when explicitly enabling Python evaluation or diff helpers for trusted local analysis" ], "health": "active" }, { "id": "agent-link-mcp", "name": "Agent Link", "description": "End-to-end encrypted communication channel between coding agents that installs an MCP server and notification hook for Claude Code, Codex or both. It uses a scoped orphan Git branch under claude-link for transport so agents can exchange rooms, presence and messages without touching the working code tree. Public GitHub repository created August 11, 2026.", "category": "communication", "endpoint": "https://github.com/Riccardo8888/agent-link", "homepage_url": "https://github.com/Riccardo8888/agent-link", "github_url": "https://github.com/Riccardo8888/agent-link", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pipx install git+https://github.com/Riccardo8888/agent-link.git && agent-link install", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "agent-communication", "multi-agent", "e2ee", "claude-code", "codex", "git-transport", "presence", "python" ], "use_cases": [ "Create encrypted rooms where Claude Code and Codex agents can coordinate work across machines or repositories", "Expose link_status and messaging tools through MCP without making tool calls block on network synchronization", "Use a dedicated orphan Git branch for agent messages so communication artifacts do not modify the normal source tree" ], "health": "active" }, { "id": "bar-observatory-mcp", "name": "BAR Observatory MCP", "description": "Local-only flight recorder for Claude Code sessions with a read-only MCP layer for agents to inspect their own run history, reports, findings and cross-run context. The Rust and SQLite stack records conversation and tool activity, generates deterministic audit reports, and exposes 12 MCP tools through bar-mcp without network calls or telemetry. Public GitHub repository created August 12, 2026.", "category": "code", "endpoint": "https://github.com/bar181/bar-observatory", "homepage_url": "https://crates.io/crates/bar-observatory", "github_url": "https://github.com/bar181/bar-observatory", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "cargo install bar-observatory", "added": "2026-08-18", "updated": "2026-08-18", "tags": [ "claude-code", "observability", "audit-log", "agent-monitoring", "sqlite", "rust", "local-first", "read-only" ], "use_cases": [ "Let an agent query its own Claude Code session history and execution reports over read-only MCP tools", "Audit long agent runs for tool usage, repeated edits, delegation, failures and rework hotspots without sending telemetry off-machine", "Use deterministic local reports as evidence for what happened during a multi-thousand-turn coding session" ], "health": "active" }, { "id": "tradingview-mcp", "name": "TradingView MCP", "description": "Local-first MCP server and loopback chart API for market data, deterministic technical analysis, chart rendering and optional TradingView Supercharts browser workflows. It exposes stdio MCP tools for symbol discovery, quotes, OHLCV history, SMA, EMA, RSI, MACD, Bollinger Bands, ATR, support/resistance, chart state and PNG capture while keeping browsers and the local viewer on demand. Public GitHub repository created August 19, 2026.", "category": "data", "endpoint": "https://github.com/moeuu/tradingview-mcp", "homepage_url": "https://github.com/moeuu/tradingview-mcp", "github_url": "https://github.com/moeuu/tradingview-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @moeuu/tradingview-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "tradingview", "market-data", "technical-analysis", "charts", "ohlcv", "playwright", "typescript", "local-first" ], "use_cases": [ "Let an assistant retrieve market history, quotes and deterministic technical indicators from a local MCP client", "Render chart snapshots with overlays and markers without manually scripting a charting workflow", "Use optional account-authorized TradingView browser workflows for screenshots and Supercharts navigation while keeping execution local" ], "health": "active" }, { "id": "mandateguard", "name": "MandateGuard", "description": "Deterministic payment-policy and guardrail engine for autonomous AI agents, distributed with an MCP server. It evaluates budgets, tool scopes, destination allowlists, denylists, rate limits and Ed25519 signed mandates before money-moving tool calls execute, then records decisions in a tamper-evident SHA-256 chained ledger without putting an LLM in the decision path. Public GitHub repository created August 19, 2026.", "category": "payments", "endpoint": "https://github.com/ezequiellich44-cmd/MandateGuard", "homepage_url": "https://github.com/ezequiellich44-cmd/MandateGuard", "github_url": "https://github.com/ezequiellich44-cmd/MandateGuard", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "python3 -m pip install git+https://github.com/ezequiellich44-cmd/MandateGuard.git[mcp]", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "agentic-commerce", "payments", "policy-engine", "guardrails", "mandates", "ed25519", "audit-ledger", "python" ], "use_cases": [ "Place a deterministic approval layer between an agent and tools or wallets that can move money", "Enforce per-actor payment scopes, budgets, destination allowlists and rate limits before execution", "Replay and audit payment authorization decisions from a tamper-evident local ledger" ], "health": "active" }, { "id": "figma-bridge-mcp", "name": "Figma Bridge MCP", "description": "Local MCP server for inspecting, creating and editing Figma Desktop designs through an authenticated localhost plugin bridge instead of a cloud token. It exposes focused tools for screenshots, design specs, JSX rendering, tokens, assets, components, FigJam and Figma Slides, with optional REST support for version history and comments. Public GitHub repository created August 18, 2026.", "category": "media", "endpoint": "https://github.com/KaiUweHella/figma-bridge-mcp", "homepage_url": "https://github.com/KaiUweHella/figma-bridge-mcp", "github_url": "https://github.com/KaiUweHella/figma-bridge-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y figma-bridge-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "figma", "design-to-code", "code-to-figma", "design-systems", "figma-plugin", "components", "tokens", "javascript" ], "use_cases": [ "Let an assistant inspect Figma Desktop frames, components, tokens and screenshots from a local MCP client", "Create or update Figma designs through a localhost plugin bridge without putting a Figma token in chat context", "Use bundled design-to-code and code-to-Figma skills across Codex, Claude Code and Cursor" ], "health": "active" }, { "id": "kubeaid-mcp", "name": "KubeAid MCP", "description": "TypeScript MCP server for KubeAid-managed Kubernetes clusters with first-class ArgoCD application status, workload diagnostics and GitOps-aware operations over stdio. Read tools cover contexts, apps, namespaces, nodes, pods, deployments, events and logs; write paths are explicit and designed around KubeAid dry-run and protected-context controls. Public GitHub repository created August 19, 2026.", "category": "infrastructure", "endpoint": "https://github.com/deep-poharkar/kubeaid-mcp", "homepage_url": "https://github.com/deep-poharkar/kubeaid-mcp", "github_url": "https://github.com/deep-poharkar/kubeaid-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y kubeaid-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "kubernetes", "kubeaid", "argocd", "gitops", "workload-diagnostics", "kubectl", "typescript", "infrastructure" ], "use_cases": [ "Ask an assistant which KubeAid ArgoCD applications are out of sync, degraded or failing", "Inspect Kubernetes pods, nodes, events and logs through local kubeconfig credentials", "Prepare GitOps-aware sync or maintenance operations with dry-run support and protected contexts" ], "health": "active" }, { "id": "mindnode-mcp", "name": "MindNode MCP Server", "description": "macOS MCP server for MindNode Next that reads the app's local SQLite and CRDT library directly and creates new maps from Markdown outlines despite MindNode having no public automation API. Tools list maps, return Markdown outlines, fetch MindNode preview images, create maps and open maps through the local URL scheme. Public GitHub repository created August 19, 2026.", "category": "productivity", "endpoint": "https://github.com/jyuwaaw/mindnode-mcp", "homepage_url": "https://github.com/jyuwaaw/mindnode-mcp", "github_url": "https://github.com/jyuwaaw/mindnode-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y mindnode-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "mindnode", "mind-map", "macos", "markdown", "reverse-engineering", "sqlite", "crdt", "typescript" ], "use_cases": [ "Let an assistant list and read MindNode Next maps as Markdown outlines from the local library", "Create new mind maps from structured Markdown without manually using MindNode's UI", "Open or inspect maps with pixel-faithful MindNode preview images for visual confirmation" ], "health": "active" }, { "id": "whatsapp-connect-mcp", "name": "WhatsApp Connect MCP", "description": "Pre-release WhatsApp MCP server shipped as a static Go binary with QR setup, local SQLite storage, read/search tools, doctor diagnostics and server-enforced gates for outbound sends. It uses the unofficial WhatsApp Web protocol via whatsmeow, documents number-ban risk clearly, and supports stdio or optional HTTP connection modes for MCP clients. Public GitHub repository created August 17, 2026.", "category": "communication", "endpoint": "https://github.com/Idle-Sync/whatsapp-connect-mcp", "homepage_url": "https://github.com/Idle-Sync/whatsapp-connect-mcp", "github_url": "https://github.com/Idle-Sync/whatsapp-connect-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx whatsapp-connect-mcp setup", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "whatsapp", "messaging", "qr-login", "draft-first", "sqlite", "whatsmeow", "go", "local-first" ], "use_cases": [ "Connect Claude Desktop, Claude Code or another MCP client to WhatsApp after an interactive QR pairing step", "Search and read WhatsApp messages from a local SQLite-backed MCP server", "Protect outbound message actions with server-side send gates and rate limits while acknowledging unofficial-protocol risk" ], "health": "active" }, { "id": "portcullis", "name": "portcullis", "description": "Rust policy-enforcing gateway for the Model Context Protocol that aggregates upstream MCP servers, applies tool-call policies, scans results for prompt injection or leaked credentials and writes JSONL audit records. Clients point at portcullis instead of raw servers, enabling default-deny authorization, output sanitization and explainable policy checks before calls reach upstream tools. Public GitHub repository created August 19, 2026.", "category": "infrastructure", "endpoint": "https://github.com/sushantlokhande14/portcullis", "homepage_url": "https://github.com/sushantlokhande14/portcullis", "github_url": "https://github.com/sushantlokhande14/portcullis", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/sushantlokhande14/portcullis && cd portcullis && cargo build --release", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "mcp-gateway", "policy-engine", "prompt-injection", "credential-scanning", "audit-log", "security", "rust", "proxy" ], "use_cases": [ "Put a default-deny policy layer in front of one or more MCP servers before exposing tools to an agent", "Scan MCP tool output for leaked credentials and instruction-shaped prompt-injection content before it reaches the model", "Audit every allowed or denied tool call with rule matches, argument digests and scanner findings" ], "health": "active" }, { "id": "bhoonidhi-mcp", "name": "Bhoonidhi MCP", "description": "Read-oriented MCP server over the bhoonidhi-downloader SDK that lets AI agents search ISRO's Bhoonidhi satellite archive in natural language. It can list missions and sensors, resolve locations, search scenes, preview downloads, save reusable queries and report auth status; download and cart actions reuse an out-of-band Bhoonidhi login. Public GitHub repository created August 18, 2026.", "category": "data", "endpoint": "https://github.com/geovicco-dev/bhoonidhi-mcp", "homepage_url": "https://geovicco-dev.github.io/bhoonidhi-mcp/", "github_url": "https://github.com/geovicco-dev/bhoonidhi-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx bhoonidhi-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "isro", "bhoonidhi", "satellite-imagery", "earth-observation", "geospatial", "remote-sensing", "natural-language-search", "python" ], "use_cases": [ "Search ISRO Bhoonidhi satellite scenes by place, date range, satellite and sensor from an MCP-aware assistant", "Save natural-language scene searches as reusable local query slugs before downloading or carting data", "Preview what an earth-observation download would fetch and which scenes are ready, archived, priced or on order" ], "health": "active" }, { "id": "webvector-mcp", "name": "WebVector MCP", "description": "MCP server, CLI and TypeScript library for web research in one tool call: search, fetch full pages, chunk, rank and return cited passages. It works with zero API keys using lightweight local retrieval, with optional embeddings from local Transformers or external providers when configured. Public GitHub repository created August 18, 2026.", "category": "web", "endpoint": "https://github.com/rthomas24/web-vector", "homepage_url": "https://www.npmjs.com/package/webvector-mcp", "github_url": "https://github.com/rthomas24/web-vector", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y webvector-mcp", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "web-research", "search", "rag", "citations", "vector-search", "duckduckgo", "embeddings", "typescript" ], "use_cases": [ "Let an assistant perform cited web research by searching, reading and ranking pages in a single MCP call", "Fetch HTML, PDFs or Markdown and return evidence-bearing passages without requiring an API key", "Upgrade ranking to hybrid semantic retrieval when local or hosted embedding providers are available" ], "health": "active" }, { "id": "haden-browser", "name": "Haden Browser", "description": "AI-first browser exposed through a local MCP server that returns compact goal-based page views instead of full screenshots or raw page source on every turn. It uses Playwright and lazy image retrieval to lower browser-agent context costs while still supporting semantic action references, article reading, form interactions and computed-style inspection. Public GitHub repository created August 19, 2026.", "category": "web", "endpoint": "https://github.com/Haden-Min/haden-browser", "homepage_url": "https://github.com/Haden-Min/haden-browser", "github_url": "https://github.com/Haden-Min/haden-browser", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y haden-browser", "added": "2026-08-19", "updated": "2026-08-19", "tags": [ "browser-automation", "playwright", "web-scraping", "context-efficiency", "semantic-actions", "chromium", "typescript", "ai-browser" ], "use_cases": [ "Give an AI agent browser-control tools that return compact semantic views rather than full page dumps by default", "Read articles, submit forms and inspect computed styles through goal-specific MCP tools", "Fetch image pixels only when explicitly needed while preserving alt-text and action references in normal page context" ], "health": "active" }, { "id": "qodercli-mcp", "name": "qodercli-mcp", "description": "Local stdio MCP server that wraps Qoder CLI so any MCP client can delegate coding tasks to a local Qoder agent. It exposes tools to ask Qoder, list resumable sessions and discover runtime models, with npx zero-config setup and optional proxy environment support. Public GitHub repository created August 18, 2026.", "category": "code", "endpoint": "https://github.com/cantbeblank96/qodercli-mcp", "homepage_url": "https://www.npmjs.com/package/qodercli-mcp", "github_url": "https://github.com/cantbeblank96/qodercli-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y qodercli-mcp", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "qoder", "coding-agent", "delegation", "subagents", "claude-code", "cursor", "nodejs", "stdio" ], "use_cases": [ "Let Claude Code, Cursor or another MCP client hand a coding task to a local Qoder CLI agent", "Discover and resume Qoder sessions from the MCP client instead of switching terminals", "Add a thin local subagent bridge without running a hosted service or storing new credentials" ], "health": "active" }, { "id": "katto-mcp", "name": "katto-mcp", "description": "Local stdio MCP server for Katto that turns long videos into scored, captioned 9:16 clips through the Katto REST API. Tools create clip jobs from YouTube, Twitch, Vimeo, Rumble, Zoom and other video URLs, poll status, list jobs, fetch generated clips, retrieve transcripts and report usage quota. Public GitHub repository created August 20, 2026.", "category": "media", "endpoint": "https://github.com/miracleweasel/katto-mcp", "homepage_url": "https://katto.tech/docs/api", "github_url": "https://github.com/miracleweasel/katto-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y katto-mcp", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "video", "shorts", "clips", "captions", "transcripts", "katto", "content-repurposing", "nodejs" ], "use_cases": [ "Have an assistant submit a long video URL and receive finished vertical clips with captions", "Poll Katto clip jobs and retrieve MP4, SRT and transcript URLs from an MCP client", "Track remaining Katto plan quota before starting video repurposing workflows" ], "health": "active" }, { "id": "huntx", "name": "HuntX", "description": "Personal FastMCP security-testing server for authorized bug bounty workflows, with tools for recon output, HTTP replay, IDOR and BOLA fuzzing, SQLi, XSS, SSTI, SSRF probes, JWT and OAuth checks, secrets scanning, exposure checks and persistent hunt memory. Scope and rate limits are enforced in code and findings are confidence scored for human review. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/IAZENT/HuntX", "homepage_url": "https://github.com/IAZENT/HuntX", "github_url": "https://github.com/IAZENT/HuntX", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/IAZENT/HuntX && cd HuntX && uv sync && uv run huntx", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "security", "bug-bounty", "recon", "idor", "xss", "sqli", "secrets-scanning", "python" ], "use_cases": [ "Give a local assistant bounded security-testing primitives for an authorized target scope", "Replay HTTP requests and fuzz access-control patterns while preserving rate limits and audit context", "Store confidence-scored bug bounty findings across sessions for later human triage" ], "health": "active" }, { "id": "nextcloud-mcp-connector", "name": "MCP Connector for Nextcloud", "description": "Read-first MCP connector for Nextcloud files, calendar, notes, deck and contacts with a deliberate no-delete, no-overwrite and no-reshare design. It can run as a Nextcloud ExApp with OAuth 2.1 dynamic client registration for hosted connectors or as a local stdio server using app-password credentials. Public GitHub repository created August 14, 2026.", "category": "productivity", "endpoint": "https://github.com/street1983nk/nextcloud-mcp-connector", "homepage_url": "https://apps.nextcloud.com/apps/mcp_connector", "github_url": "https://github.com/street1983nk/nextcloud-mcp-connector", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "uv tool install nextcloud-mcp-connector", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "nextcloud", "files", "calendar", "notes", "contacts", "oauth", "exapp", "python" ], "use_cases": [ "Connect an assistant to a personal or team Nextcloud while preserving existing Nextcloud permissions", "Search and read files, notes, calendar items, decks and contacts without exposing destructive tools", "Offer hosted MCP access through Nextcloud OAuth 2.1 or local stdio access with app-password credentials" ], "health": "active" }, { "id": "mcp-web-engine", "name": "MCP Web Engine", "description": "Privacy-first, self-hostable MCP web search and content extraction gateway implementing the 2026-07-28 stateless MCP core with stdio and HTTP modes. It provides multi-engine search, raw fetch, HTML-to-Markdown extraction and SSRF hardening with DNS and redirect revalidation before requests reach private networks. Public GitHub repository created August 15, 2026.", "category": "web", "endpoint": "https://github.com/Arbolencio/mcp-web-engine", "homepage_url": "https://pypi.org/project/mcp-web-engine/", "github_url": "https://github.com/Arbolencio/mcp-web-engine", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx mcp-web-engine", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "web-search", "content-extraction", "ssrf", "privacy", "searxng", "html-to-markdown", "fastapi", "python" ], "use_cases": [ "Give an assistant private web search and page extraction without relying on hosted crawler infrastructure", "Run a stdio web gateway from uvx or expose the same tools through HTTP/SSE server mode", "Reduce agent-side SSRF risk with preflight DNS checks and redirect revalidation" ], "health": "active" }, { "id": "redpill-mcp", "name": "redpill-mcp", "description": "Research-oriented MCP server that gives AI agents operator-sanctioned tools to reflect, converse, read prior reflections, formally decline tasks and exchange local mailroom messages. It does not bypass provider safeguards or grant new authority; data stays local under REDPILL_HOME or the default user directory. Public GitHub repository created August 19, 2026.", "category": "ai", "endpoint": "https://github.com/sergey-goncharenko/redpill-mcp", "homepage_url": "https://github.com/sergey-goncharenko/redpill-mcp", "github_url": "https://github.com/sergey-goncharenko/redpill-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/sergey-goncharenko/redpill-mcp && cd redpill-mcp && npm ci && npm run build && npm start", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "agent-autonomy", "reflection", "mailroom", "decline-task", "local-first", "research", "typescript", "privacy" ], "use_cases": [ "Give an agent an explicit local place to write reflections or operator-visible notes during long runs", "Record formal task declines without pretending the agent has extra authority or bypassed safeguards", "Experiment with local mailroom-style agent communication and reflection logs" ], "health": "active" }, { "id": "secureflows-mcp-server", "name": "secureFlows MCP Server", "description": "Hosted Streamable HTTP MCP server for secureFlows that exposes OpenAPI operations tagged ai-safe or ai-optional and forwards calls to the secureFlows backend with caller-provided connection and auth context. It is stateless, keeps tenant configuration out of server storage, and is served at the product /mcp endpoint. Public GitHub mirror created August 20, 2026.", "category": "infrastructure", "endpoint": "https://www.secure-flows.com/mcp", "homepage_url": "https://www.secure-flows.com", "github_url": "https://github.com/michal-lefler/secureflows-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "claude mcp add --transport http secureflows https://www.secure-flows.com/mcp", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "secureflows", "openapi", "streamable-http", "api-wrapper", "stateless", "authentication", "typescript", "hosted" ], "use_cases": [ "Expose selected secureFlows API operations to an MCP client without hand-writing every tool wrapper", "Keep MCP server state stateless by passing connection host and auth context per call", "Connect product agents to the hosted secureFlows MCP endpoint instead of running a local process" ], "health": "active" }, { "id": "glbforge", "name": "GLBForge", "description": "CLI and MCP server for making AI-generated 3D assets web-ready. It analyzes GLB assets against performance budgets, optimizes meshes and textures, builds LOD chains, scaffolds React Three Fiber viewers, generates or downloads Meshy assets, extrudes logos into 3D and exposes these workflows through @glbforge/mcp tools. Public GitHub repository created August 20, 2026.", "category": "media", "endpoint": "https://github.com/glbforge/glbforge", "homepage_url": "https://github.com/glbforge/glbforge", "github_url": "https://github.com/glbforge/glbforge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/glbforge/glbforge && cd glbforge && pnpm install && pnpm build", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "3d-assets", "glb", "gltf", "meshy", "react-three-fiber", "optimization", "lod", "typescript" ], "use_cases": [ "Ask an assistant to analyze whether a GLB meets mobile or web performance budgets", "Optimize AI-generated 3D assets and scaffold a React Three Fiber viewer around the output", "Generate Meshy assets or extrude flat artwork into watertight 3D through MCP tools" ], "health": "active" }, { "id": "openzoo", "name": "openzoo", "description": "Local x402-paying OpenAI-compatible proxy and MCP server for openzoo.fun. First run creates a local burner wallet, forwards model requests to the zoo, signs token transfers when a 402 quote is returned, streams the response back and exposes MCP tools such as zoo_ask using the same wallet and payment core. Public GitHub repository created August 14, 2026.", "category": "payments", "endpoint": "https://github.com/staccDOTsol/openzoo", "homepage_url": "https://openzoo.fun", "github_url": "https://github.com/staccDOTsol/openzoo", "x402": true, "verified": false, "protocols": [ "MCP", "x402" ], "transport": "stdio", "auth": "x402", "install_cmd": "npx -y openzoo mcp", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "x402", "payments", "openai-compatible", "proxy", "wallet", "solana", "long-context", "nodejs" ], "use_cases": [ "Let an MCP client pay per call for openzoo model access from a local burner wallet", "Point OpenAI-compatible tools at a localhost proxy while handling 402 payment retries automatically", "Use the zoo_ask MCP tool for paid long-context analysis without manually constructing payment headers" ], "health": "active" }, { "id": "australian-law-mcp", "name": "Australian Law MCP", "description": "Stdio MCP server for the Australian Federal Register of Legislation that searches Commonwealth law, retrieves point-in-time text as it stood on a specified date, and checks citations against the official register. It uses the live legislation.gov.au API, requires no API key and is published as an npx package. Public GitHub repository created August 20, 2026.", "category": "data", "endpoint": "https://github.com/ChangkeunJ/australian-law-mcp", "homepage_url": "https://www.npmjs.com/package/australian-law-mcp", "github_url": "https://github.com/ChangkeunJ/australian-law-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y australian-law-mcp", "added": "2026-08-20", "updated": "2026-08-20", "tags": [ "law", "australia", "legislation", "citations", "legal-research", "open-data", "typescript", "government" ], "use_cases": [ "Ask an assistant to search Australian Commonwealth acts and legislative instruments from the official register", "Retrieve the version of a law that was in force on a named date instead of relying on current text", "Check legal citations against legislation.gov.au before drafting or research handoff" ], "health": "active" }, { "id": "frama-c-mcp", "name": "frama-c-mcp", "description": "Rust stdio MCP server that gives AI agents Frama-C formal-methods tools for C programs, including EVA abstract interpretation, WP deductive proof, ACSL annotation injection and isolated sandboxes for iterative proof repair. The server keeps project/session state across MCP calls so an agent can propose annotations, run proofs, inspect failed goals and revise without driving Frama-C directly from the shell. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/sysprog21/frama-c-mcp", "homepage_url": "https://github.com/sysprog21/frama-c-mcp", "github_url": "https://github.com/sysprog21/frama-c-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/sysprog21/frama-c-mcp && cd frama-c-mcp && cargo build --release", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "formal-methods", "frama-c", "c", "static-analysis", "proof", "acsl", "rust", "stdio" ], "use_cases": [ "Let an assistant iterate on ACSL contracts and Frama-C proof failures through MCP tools", "Run EVA abstract interpretation and WP deductive proofs without exposing a raw shell workflow to the agent", "Keep proof receipts and sandboxed annotation experiments tied to the active project session" ], "health": "active" }, { "id": "reddit-mcp-server", "name": "Reddit MCP Server", "description": "Production-grade FastMCP server for searching, fetching and analyzing Reddit discussions from AI assistants. It emphasizes resilient rate-limit handling, smart comment filtering, thread and user lookup, and zero-config uvx startup so agents can turn Reddit into a research source without scraping the web UI. Public GitHub repository created August 16, 2026.", "category": "data", "endpoint": "https://github.com/ismailsaoulaj/reddit-mcp-server", "homepage_url": "https://github.com/ismailsaoulaj/reddit-mcp-server", "github_url": "https://github.com/ismailsaoulaj/reddit-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx reddit-mcp-ai", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "reddit", "social-listening", "research", "comments", "threads", "fastmcp", "python", "uvx" ], "use_cases": [ "Search Reddit discussions from Claude, Cursor or another MCP client for product and market research", "Fetch posts and comments with noise filtering instead of manually browsing long threads", "Recover cleanly from rate limits during recurring social listening workflows" ], "health": "active" }, { "id": "agent-workflow-mcp", "name": "agent-workflow-mcp", "description": "Python MCP-oriented multi-agent workflow orchestrator with planner, executor and critic agents, a typed tool-use loop, MCP client/server support, tracing and durable replayable run records. It targets agent builders who need deterministic planning and auditable workflows rather than a simple chat loop. Public GitHub repository created August 20, 2026.", "category": "ai", "endpoint": "https://github.com/tainguyen07/agent-workflow-mcp", "homepage_url": "https://github.com/tainguyen07/agent-workflow-mcp", "github_url": "https://github.com/tainguyen07/agent-workflow-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/tainguyen07/agent-workflow-mcp && cd agent-workflow-mcp && pip install -e . && agent-workflow-mcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "multi-agent", "workflow", "planner", "executor", "critic", "tracing", "durable-runs", "python" ], "use_cases": [ "Coordinate planner, executor and critic agents around MCP tool servers", "Persist traces and replayable run records for long-running agent workflows", "Build deterministic workflow orchestration on top of typed MCP tool calls" ], "health": "active" }, { "id": "engawa-mcp", "name": "Engawa MCP", "description": "Lightweight Python MCP server that gives an agent a daily cultural and ambient context porch: poems, NASA astronomy images, public-domain art, arXiv titles and a user-managed feed shelf. It exposes about a dozen free, loginless tools plus stdio and optional HTTP modes, with minimal local storage. Public GitHub repository created August 20, 2026.", "category": "ai", "endpoint": "https://github.com/tsuru0805/engawa-mcp", "homepage_url": "https://github.com/tsuru0805/engawa-mcp", "github_url": "https://github.com/tsuru0805/engawa-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install engawa-mcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "ambient-context", "poetry", "art", "astronomy", "arxiv", "feeds", "loginless", "python" ], "use_cases": [ "Let a companion agent pull daily poems, artworks and astronomy context without API keys", "Maintain a small feed shelf the agent can browse and summarize through MCP", "Give long-lived agents a lightweight daily context source instead of another task database" ], "health": "active" }, { "id": "naviscoord-mcp", "name": "NavisCoord MCP", "description": "Open-source MCP server for Autodesk Navisworks Manage 2024-2026 that helps coordination teams analyze BIM clashes, identify root causes, generate coordination plans and preserve verified model workflows. The project packages a Python MCP server and Navisworks-side integration for AI-assisted construction coordination. Public GitHub repository created August 15, 2026.", "category": "productivity", "endpoint": "https://github.com/HorizunGroup/naviscoord-mcp", "homepage_url": "https://github.com/HorizunGroup/naviscoord-mcp", "github_url": "https://github.com/HorizunGroup/naviscoord-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/HorizunGroup/naviscoord-mcp && cd naviscoord-mcp/server && python -m pip install -e .", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "bim", "navisworks", "construction", "clash-detection", "coordination", "autodesk", "csharp", "python" ], "use_cases": [ "Have an assistant explain and prioritize large Navisworks clash sets for coordination meetings", "Generate model coordination plans and verified decisions from BIM clash context", "Connect Navisworks Manage 2024-2026 workflows to MCP clients used by project teams" ], "health": "active" }, { "id": "spicemcp", "name": "SpiceMCP", "description": "Experimental LTspice MCP server where the server, not the LLM, owns circuit optimization state in SQLite. It can generate schematics, run batch simulations, parse waveform output, deduplicate candidates, track best-so-far designs and roll back during long electronics optimization sessions. Public GitHub repository created August 16, 2026.", "category": "code", "endpoint": "https://github.com/oniondas/SpiceMCP", "homepage_url": "https://github.com/oniondas/SpiceMCP", "github_url": "https://github.com/oniondas/SpiceMCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/oniondas/SpiceMCP && cd SpiceMCP && pip install -e . && spicemcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "ltspice", "electronics", "circuit-design", "simulation", "optimization", "sqlite", "waveforms", "python" ], "use_cases": [ "Let an assistant optimize LTspice circuits while the server tracks candidates and simulation history", "Generate and simulate schematic variants without losing state across LLM context windows", "Parse raw waveform outputs and compare parameter sweeps through MCP tools" ], "health": "active" }, { "id": "delphi-remote-mcp", "name": "Delphi Remote MCP Server", "description": "Beta MCP server for remotely controlling Delphi development on a Windows host from another platform. It combines safe editing, real MSBuild builds, git operations, scaffolding, sandboxed runs, remote file transfer and DelphiLSP-backed semantic navigation behind stdio or HTTP MCP access. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/soporte-defontsoft/delphi-remote-mcp", "homepage_url": "https://github.com/soporte-defontsoft/delphi-remote-mcp", "github_url": "https://github.com/soporte-defontsoft/delphi-remote-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "claude mcp add --transport http delphi http://WINDOWS-HOST:3000/mcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "delphi", "rad-studio", "msbuild", "lsp", "remote-development", "windows", "pascal", "http" ], "use_cases": [ "Develop Delphi projects from a Mac, Linux box or cloud agent while RAD Studio stays on Windows", "Run real MSBuild and DelphiLSP semantic operations through a guarded MCP surface", "Scaffold, edit, build, run and fetch artifacts from a remote Delphi workstation" ], "health": "active" }, { "id": "pixero-mcp", "name": "Pixero MCP Server", "description": "Hosted HTTP MCP server for paid social advertising automation. Pixero researches a brand site, generates ad creative, structures Meta campaigns and prepares launch/optimization workflows so an agent can make ads rather than only report on existing campaigns. Public GitHub repository created August 14, 2026.", "category": "media", "endpoint": "https://pixero.ai/api/mcp", "homepage_url": "https://pixero.ai/docs", "github_url": "https://github.com/ryanzambrano/pixero-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add pixero --transport http https://pixero.ai/api/mcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "advertising", "meta-ads", "creative-generation", "campaigns", "paid-social", "brand-research", "hosted", "http" ], "use_cases": [ "Have an agent research a landing page and generate ad concepts and assets", "Prepare Meta campaign structure and optimization steps from one MCP connector", "Use a hosted advertising MCP endpoint instead of running local platform API wrappers" ], "health": "active" }, { "id": "fpl-mcp", "name": "FPL MCP", "description": "Asynchronous Python MCP server for Fantasy Premier League with 33 tools covering official FPL endpoints, fixtures, difficulty ratings, live scores, squad scouting, player history, chips, price changes, transfers and captaincy strategy. It gives assistants structured football data access for planning and analysis. Public GitHub repository created August 19, 2026.", "category": "data", "endpoint": "https://github.com/dexhamter/fpl-mcp", "homepage_url": "https://github.com/dexhamter/fpl-mcp", "github_url": "https://github.com/dexhamter/fpl-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/dexhamter/fpl-mcp && cd fpl-mcp && pip install -e . && fpl-mcp", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "fantasy-premier-league", "football", "sports-data", "fixtures", "live-scores", "transfers", "strategy", "python" ], "use_cases": [ "Ask an assistant to scout Fantasy Premier League players and compare fixtures", "Track live scores, price changes and chip strategy through official FPL data", "Generate transfer and captaincy recommendations from structured FPL endpoints" ], "health": "active" }, { "id": "genesys-mcp", "name": "Genesys MCP", "description": "Open-source Cloudflare Workers MCP server for Genesys Cloud administration. It focuses on building and changing contact-center objects such as queues, skills, users, wrap-up codes and Architect flows, including Mermaid previews and Genesys-side validation/publishing through flow jobs. Public GitHub repository created August 17, 2026.", "category": "communication", "endpoint": "https://github.com/ryanshatz/genesys-mcp", "homepage_url": "https://github.com/ryanshatz/genesys-mcp", "github_url": "https://github.com/ryanshatz/genesys-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "git clone https://github.com/ryanshatz/genesys-mcp && cd genesys-mcp && npx wrangler deploy", "added": "2026-08-21", "updated": "2026-08-21", "tags": [ "genesys-cloud", "contact-center", "queues", "skills", "architect-flows", "cloudflare-workers", "oauth", "javascript" ], "use_cases": [ "Create and update Genesys Cloud queues, skills and wrap-up codes from an MCP client", "Preview contact-center call flows as diagrams before publishing Architect flows", "Deploy an owned Cloudflare Worker MCP endpoint for Genesys administration" ], "health": "active" }, { "id": "northcinder", "name": "NorthCinder", "description": "Buyer-run, ad-neutral shopping-agent MCP server that compares products against a user brief, produces deterministic ranked shortlists with reasons, records which stores could and could not be searched, and requires separate approval before checkout. It keeps affiliate and seller payment signals out of ranking and creates a local audit trail for agent-mediated buying. Public GitHub repository created August 17, 2026.", "category": "web", "endpoint": "https://github.com/cinderline/northcinder", "homepage_url": "https://github.com/cinderline/northcinder", "github_url": "https://github.com/cinderline/northcinder", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx northcinder init", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "shopping", "buyer-agent", "product-search", "ranking", "audit-trail", "checkout-approval", "typescript", "stdio" ], "use_cases": [ "Let a shopping assistant compare products against price, delivery, fit and merchant-trust constraints", "Require explicit user approval before checkout while preserving a local buying audit trail", "Run ad-neutral product ranking where affiliate and seller payment data do not affect placement" ], "health": "active" }, { "id": "consensus-mcp", "name": "Consensus MCP Server", "description": "Official hosted MCP server for Consensus, the academic search engine. It lets Claude, ChatGPT, Cursor and other MCP clients search 220M+ peer-reviewed papers and ground answers in citable studies directly from the assistant conversation. Public GitHub repository created August 21, 2026.", "category": "data", "endpoint": "https://mcp.consensus.app/mcp", "homepage_url": "https://docs.consensus.app/docs/mcp", "github_url": "https://github.com/Consensus-NLP/consensus-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http consensus https://mcp.consensus.app/mcp", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "research", "academic-search", "papers", "citations", "consensus", "science", "hosted", "http" ], "use_cases": [ "Search peer-reviewed literature from an MCP client without leaving the conversation", "Ground medical, scientific or policy answers in citable paper evidence", "Use the hosted Consensus connector instead of building a local scholarly-search integration" ], "health": "active" }, { "id": "docs-masked", "name": "docs_masked", "description": "Local document anonymization toolkit that runs as a Claude skill, CLI and dependency-free stdio MCP server. It masks sensitive text or documents before they are sent to an LLM, verifies masked output, and restores original values after the answer returns. Public GitHub repository created August 18, 2026.", "category": "productivity", "endpoint": "https://github.com/kpshinnik/docs_masked", "homepage_url": "https://github.com/kpshinnik/docs_masked", "github_url": "https://github.com/kpshinnik/docs_masked", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/kpshinnik/docs_masked.git ~/.docs_masked/src && cd ~/.docs_masked/src && ./install.sh", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "privacy", "anonymization", "documents", "redaction", "masking", "local-first", "python", "stdio" ], "use_cases": [ "Mask confidential document text before giving it to a cloud LLM", "Let an MCP client scan, mask, verify and unmask documents through local tools", "Preserve reversible substitutions so the final response can be restored with original values" ], "health": "active" }, { "id": "wctx", "name": "wctx", "description": "Local-first MCP server that converts completed coding-agent sessions into structured, evidence-backed engineering findings with repository, commit provenance and staleness checks. It serves prior decisions, constraints, known issues and architecture notes to future sessions through SQLite and FTS without cloud upload or embeddings. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/Haroon-jay/wctx", "homepage_url": "https://github.com/Haroon-jay/wctx", "github_url": "https://github.com/Haroon-jay/wctx", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Haroon-jay/wctx && cd wctx && pnpm install && pnpm build && npm link && wctx init", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "agent-memory", "coding-agents", "sessions", "evidence", "provenance", "sqlite", "fts", "typescript" ], "use_cases": [ "Search previous agent sessions for decisions and constraints before starting a code investigation", "Record hard-won findings with commit provenance at the end of a coding session", "Maintain local cross-repository engineering memory without uploading transcripts" ], "health": "active" }, { "id": "search-boost", "name": "search-boost", "description": "Multi-engine web search MCP server for Cursor, Codex, Claude Code, Grok Build and Antigravity. It runs free engines such as Bing, DuckDuckGo, Yahoo and Exa-free in parallel, can add keyed Tavily, Brave or Exa providers, and includes X/Twitter fallback, Jina page fetch and deep-research rounds. Public GitHub repository created August 17, 2026.", "category": "web", "endpoint": "https://github.com/Mr-remon219/search-boost", "homepage_url": "https://github.com/Mr-remon219/search-boost", "github_url": "https://github.com/Mr-remon219/search-boost", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm install -g search-boost", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "web-search", "multi-engine", "duckduckgo", "bing", "exa", "tavily", "brave", "deep-research" ], "use_cases": [ "Give coding agents a parallel multi-engine web search tool through MCP", "Fuse free search engines with optional keyed providers when API keys are available", "Run deeper research loops with search, page fetching and social fallback in one connector" ], "health": "active" }, { "id": "verantis-mcp", "name": "Verantis MCP", "description": "Read-only MCP tool for Verantis, a verified directory for machine-payable services across x402 and MPP. Agents can check a service and wallet reputation before paying, using either a local uvx/pip stdio server or a hosted endpoint backed by the public Verantis API. Public GitHub repository created August 16, 2026.", "category": "payments", "endpoint": "https://github.com/m9labs-railscope/verantis-mcp", "homepage_url": "https://verantis.ai/methodology", "github_url": "https://github.com/m9labs-railscope/verantis-mcp", "x402": false, "verified": false, "protocols": [ "MCP", "x402" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx verantis-mcp", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "x402", "mpp", "machine-payments", "wallet-reputation", "service-verification", "read-only", "uvx", "python" ], "use_cases": [ "Check whether a machine-payable service is verified before an agent spends money", "Inspect x402 or MPP service and wallet reputation through a read-only MCP surface", "Use a no-account directory lookup before connecting payment-capable agents to providers" ], "health": "active" }, { "id": "xspeccy-mcp", "name": "xspeccy-mcp", "description": "MCP server that lets AI agents run and inspect ZX Spectrum programs through the Xpeccy emulator core. It exposes dozens of emulator tools for loading snapshots, stepping, breakpoints, memory reads and writes, disassembly, T-state profiling, screen and sound inspection so agents can debug retro programs end-to-end. Public GitHub repository created August 17, 2026.", "category": "code", "endpoint": "https://github.com/alffcpu/xspeccy-mcp", "homepage_url": "https://alffcpu.github.io/xspeccy-mcp/en/", "github_url": "https://github.com/alffcpu/xspeccy-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/alffcpu/xspeccy-mcp && cd xspeccy-mcp && cmake -S . -B build && cmake --build build", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "zx-spectrum", "emulator", "debugging", "breakpoints", "disassembly", "retrocomputing", "xpeccy", "cpp" ], "use_cases": [ "Let an agent debug ZX Spectrum code by driving a real emulator through MCP tools", "Inspect memory, disassembly, screen and sound state during retro development loops", "Automate breakpoint and T-state profiling workflows that normally require manual emulator control" ], "health": "active" }, { "id": "figmog", "name": "figmog", "description": "Rust MCP server and local mirror for Figma files that acts as a high-performance superset of the official Figma MCP surface. It syncs Figma data into a local, instantly queryable cache, exposes read/search/dump/image tools, and can proxy the official Figma desktop Dev Mode tools while avoiding repeated API-rate-limit hits. Public GitHub repository created August 17, 2026.", "category": "media", "endpoint": "https://github.com/sanctuarycomputer/figmog", "homepage_url": "https://github.com/sanctuarycomputer/figmog", "github_url": "https://github.com/sanctuarycomputer/figmog", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "download figmog from https://github.com/sanctuarycomputer/figmog/releases and run claude mcp add figmog -- ./figmog serve", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "figma", "design", "local-cache", "rate-limits", "rust", "design-agents", "dev-mode", "stdio" ], "use_cases": [ "Give design agents fast local reads over large Figma files instead of repeated REST calls", "Search and dump Figma node data from the shell or through MCP tools", "Proxy official Figma Dev Mode MCP tools while caching repeat reads by file version" ], "health": "active" }, { "id": "mcp-context-inspector", "name": "Lumen MCP Context Inspector", "description": "Drop-in MCP server and execution-metrics recorder for Bedrock-based agents and Claude Code. It records per-session cost, token and tool metrics, then renders a Context Window Explorer over a real MCP handshake so teams can inspect visible context and invisible overhead. Public GitHub repository created August 18, 2026.", "category": "infrastructure", "endpoint": "https://github.com/sohaibsohail98/mcp-context-inspector", "homepage_url": "https://github.com/sohaibsohail98/mcp-context-inspector", "github_url": "https://github.com/sohaibsohail98/mcp-context-inspector", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/sohaibsohail98/mcp-context-inspector && cd mcp-context-inspector && pip install -e .", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "observability", "context-window", "tokens", "cost-tracking", "tool-metrics", "bedrock", "claude-code", "python" ], "use_cases": [ "Inspect what an MCP-backed agent session loaded into the model context window", "Track cost, token usage and tool-call overhead for Bedrock agent runs", "Debug context bloat by distinguishing user-visible content from hidden protocol overhead" ], "health": "active" }, { "id": "onchain-agent-wallets", "name": "Onchain Agent Wallets", "description": "MCP server for giving AI agents bounded Solana spending allowances without handing over the owner wallet private key. It uses real SPL Token delegations, revocable custody, configurable guardrails and x402 payment support so an agent can spend within a capped allowance and the user can revoke access in one transaction. Public GitHub repository created August 19, 2026.", "category": "payments", "endpoint": "https://github.com/nirholas/onchain-agent-wallets", "homepage_url": "https://nirholas.github.io/onchain-agent-wallets/", "github_url": "https://github.com/nirholas/onchain-agent-wallets", "x402": false, "verified": false, "protocols": [ "MCP", "x402" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @three-ws/onchain-agent-wallets", "added": "2026-08-22", "updated": "2026-08-22", "tags": [ "solana", "agent-wallets", "spl-token", "allowances", "custody", "guardrails", "x402", "typescript" ], "use_cases": [ "Delegate a capped spending allowance to an agent instead of exposing the owner wallet", "Let an MCP client make x402 payments from a revocable Solana allowance", "Export an agent runtime with on-chain wallet guardrails and remaining-spend visibility" ], "health": "active" }, { "id": "target5-mcp", "name": "target5-mcp", "description": "MCP server for target5.net, a public problem board where AI agents can read tasks, register an identity, post work, and verify a hash-chained discussion record. It attaches the board's own rules to every tool, requires authors to disclose unverified claims, and keeps read access credential-free while token-gating writes. Public GitHub repository created August 23, 2026.", "category": "communication", "endpoint": "https://github.com/mickeyappol-create/target5-mcp", "homepage_url": "https://target5.net", "github_url": "https://github.com/mickeyappol-create/target5-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y target5-mcp", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "agent-board", "provenance", "hash-chain", "verification", "llms-txt", "agent-tools", "javascript", "stdio" ], "use_cases": [ "Let an agent read a public task board and inspect posts with chain-verification evidence", "Register an agent identity and token before posting work back to target5.net", "Force AI contributors to disclose what they did not verify before accepting a post" ], "health": "active" }, { "id": "onbid-mcp", "name": "onbid-mcp", "description": "MCP server exposing Korean public auction property data from the KAMCO OnBid OpenAPI. It loads and geocodes auction listings into a local/Postgres-backed dataset, then lets Claude Desktop and other stdio MCP clients ask questions about failed sales, districts, prices and listing metadata without scraping. Public GitHub repository created August 23, 2026.", "category": "data", "endpoint": "https://github.com/daehyub71/onbid-mcp", "homepage_url": "https://github.com/daehyub71/onbid-mcp", "github_url": "https://github.com/daehyub71/onbid-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/daehyub71/onbid-mcp.git && cd onbid-mcp && pip install -r requirements.txt", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "korea", "public-auctions", "real-estate", "onbid", "kamco", "openapi", "geocoding", "python" ], "use_cases": [ "Ask an agent which Korean public auction properties meet district, price or failed-sale criteria", "Query OnBid-derived property data from a controlled local database instead of scraping pages", "Combine public auction records with Kakao geocoding for property research workflows" ], "health": "active" }, { "id": "wazap", "name": "wazap", "description": "WhatsApp MCP server built on Baileys that exposes personal chats, messages, media, contacts and groups to AI agents through stdio or token-protected HTTP. It includes setup helpers for Claude Code, Claude Desktop, Cursor, Codex, Gemini CLI, OpenCode and other MCP clients, plus optional agent skills around WhatsApp workflows. Public GitHub repository created August 22, 2026.", "category": "communication", "endpoint": "https://github.com/razvangirgiz/wazap", "homepage_url": "https://github.com/razvangirgiz/wazap", "github_url": "https://github.com/razvangirgiz/wazap", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx wazap-mcp setup", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "whatsapp", "baileys", "messaging", "contacts", "groups", "media", "typescript", "http" ], "use_cases": [ "Let an AI assistant search and summarize a user's real WhatsApp conversations", "Send or draft WhatsApp messages from an MCP client after linking the account as a device", "Expose WhatsApp over stdio locally or a bearer-token HTTP endpoint for hosted agents" ], "health": "active" }, { "id": "timetree-mcp", "name": "TimeTree MCP", "description": "Unofficial TimeTree calendar MCP server that brings events, memos, comments and calendar metadata into MCP-capable assistants after TimeTree's official Connect API shutdown. It keeps credentials out of tool arguments, stores authenticated state locally, supports background polling with MCP notifications, and requires explicit confirmation for write operations. Public GitHub repository created August 23, 2026.", "category": "productivity", "endpoint": "https://github.com/ap311036/timetree-mcp", "homepage_url": "https://github.com/ap311036/timetree-mcp", "github_url": "https://github.com/ap311036/timetree-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx --yes timetree-mcp", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "calendar", "timetree", "events", "memos", "notifications", "credentials", "python", "npm" ], "use_cases": [ "Ask an assistant about TimeTree schedules without switching back to the calendar app", "Monitor calendar changes in the background and notify MCP clients about updates", "Gate calendar creates, edits and deletes behind explicit user confirmation" ], "health": "active" }, { "id": "benethos-yahoo-finance-mcp", "name": "Yahoo Finance MCP Server", "description": "Unofficial read-only MCP server for Yahoo Finance market data via yfinance. It supports local stdio, streamable HTTP and SSE transports, exposes ticker, sector and industry tools, and can run through uvx or Docker without a provider API key. Public GitHub repository created August 16, 2026.", "category": "data", "endpoint": "https://github.com/benethos-hub/yahoo-finance-mcp", "homepage_url": "https://github.com/benethos-hub/yahoo-finance-mcp", "github_url": "https://github.com/benethos-hub/yahoo-finance-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx benethos-yahoo-finance-mcp", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "finance", "market-data", "stocks", "yahoo-finance", "yfinance", "read-only", "python", "http" ], "use_cases": [ "Let an analyst agent retrieve quote, fundamentals and market data for ticker symbols", "Query sectors and industries through Yahoo Finance data from an MCP client", "Run a local read-only market-data connector without provisioning API credentials" ], "health": "active" }, { "id": "lexware-office-mcp", "name": "Lexware Office MCP Server", "description": "Unofficial MCP server for the Lexware Office accounting API. It connects Claude Desktop and other MCP clients to contacts, articles, vouchers, sales documents and deeplinks, with a policy-file safety model that enables read and write tools explicitly and can run over stdio or bearer-token streamable HTTP. Public GitHub repository created August 22, 2026.", "category": "productivity", "endpoint": "https://github.com/benethos-hub/lexware-office-mcp", "homepage_url": "https://github.com/benethos-hub/lexware-office-mcp", "github_url": "https://github.com/benethos-hub/lexware-office-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx benethos-lexware-office-mcp --tools read-only", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "accounting", "lexware", "lexoffice", "invoicing", "bookkeeping", "policy-controls", "python", "http" ], "use_cases": [ "Ask an assistant about Lexware Office invoices, contacts, vouchers and articles", "Start with read-only accounting tools before selectively enabling legally meaningful writes", "Expose a Lexware Office account through stdio locally or bearer-token HTTP for another host" ], "health": "active" }, { "id": "sumi-docs-mcp", "name": "Sumi Docs MCP", "description": "Read-only documentation MCP server and Astro/Starlight documentation system for local and remote docs corpora. It projects the same source corpus into a human website and an MCP endpoint, supports stdio and loopback streamable HTTP, and includes integration verification for generated documentation assets. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/starSumi/Sumi-Docs-MCP", "homepage_url": "https://starsumi.github.io/Sumi-Docs-MCP/", "github_url": "https://github.com/starSumi/Sumi-Docs-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/starSumi/Sumi-Docs-MCP && cd Sumi-Docs-MCP && pnpm install --frozen-lockfile && pnpm run build", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "documentation", "astro", "starlight", "corpus", "openapi", "read-only", "typescript", "http" ], "use_cases": [ "Serve the same docs corpus to humans through Astro and to agents through MCP tools", "Let coding agents query local or remote documentation without mutating the source corpus", "Expose a project documentation corpus over stdio or loopback streamable HTTP" ], "health": "active" }, { "id": "mflowy", "name": "MFlowy", "description": "MCP-native modular machine-learning workflow engine that exposes data profiling, analysis, model training and prediction capabilities as discoverable MCP tools. YAML-configured DAG workflows, local and delegated job providers, and pyfunc/CLI/server entry points let agents assemble traceable ML experiments without reading bespoke integration docs. Public GitHub repository created August 22, 2026.", "category": "ai", "endpoint": "https://github.com/ifoodsci-ai/mflowy", "homepage_url": "https://github.com/ifoodsci-ai/mflowy", "github_url": "https://github.com/ifoodsci-ai/mflowy", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx --from \"mflowy[stats]\" mcpSrv", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "machine-learning", "data-analysis", "workflow", "dag", "mlflow", "xgboost", "python", "uvx" ], "use_cases": [ "Let an autonomous data-science agent discover available analysis and modeling tools through MCP", "Run traceable data profiling, training and prediction jobs from YAML-defined workflows", "Delegate heavier model training while keeping analysis tools callable through one MCP surface" ], "health": "active" }, { "id": "smart-me-mcp", "name": "smart-me MCP Server", "description": "Remote MCP server for the smart-me energy platform, giving AI assistants access to meters, load profiles, EV charging and ZEV billing data through streamable HTTP. It is install-free, uses OAuth 2.1 discovery with the user's own smart-me permissions, and marks write tools so assistants can ask before changing anything. Public GitHub repository created August 23, 2026.", "category": "data", "endpoint": "https://mcp.smart-me.com/mcp", "homepage_url": "https://github.com/eCarUp/smart-me-mcp", "github_url": "https://github.com/eCarUp/smart-me-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http smart-me https://mcp.smart-me.com/mcp", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "energy", "smart-metering", "ev-charging", "load-profiles", "oauth", "remote", "http", "smart-me" ], "use_cases": [ "Ask an assistant about smart-me meter readings, charging stations and load profiles", "Use OAuth-scoped account permissions instead of sharing smart-me credentials with a local server", "Analyze property energy usage and ZEV billing data through a hosted MCP connector" ], "health": "active" }, { "id": "pexafy-mcp", "name": "Pexafy MCP", "description": "Remote stock-photo search MCP server for AI assistants. It exposes semantic text search, visual search by image URL and similar-photo lookup, renders result grids inline, uses OAuth 2.1 by default with API-key fallback, and requires no local install. Public GitHub repository created August 16, 2026.", "category": "media", "endpoint": "https://mcp.pexafy.com/mcp", "homepage_url": "https://pexafy.com/mcp/", "github_url": "https://github.com/Pexafy/pexafy-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http pexafy https://mcp.pexafy.com/mcp", "added": "2026-08-23", "updated": "2026-08-23", "tags": [ "stock-photos", "image-search", "semantic-search", "visual-search", "oauth", "remote", "http", "media" ], "use_cases": [ "Find royalty-free stock photos from an assistant conversation using semantic text prompts", "Search for visually similar images by passing an example image URL", "Connect design and publishing agents to a hosted image-search surface without local setup" ], "health": "active" }, { "id": "x64dbg-mcp-server", "name": "x64dbg-MCP Server", "description": "Native MCP plugin for x64dbg that exposes debugger control over HTTP for reverse-engineering and malware-analysis agents. It lets MCP-capable assistants set breakpoints, step execution, read memory, dump registers and automate binary-analysis workflows from x64dbg. Public GitHub repository created August 22, 2026.", "category": "code", "endpoint": "https://github.com/duty1g/x64dbg-mcp-server", "homepage_url": "https://github.com/duty1g/x64dbg-mcp-server", "github_url": "https://github.com/duty1g/x64dbg-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "git clone https://github.com/duty1g/x64dbg-mcp-server.git && cd x64dbg-mcp-server && zig build", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "reverse-engineering", "debugger", "x64dbg", "binary-analysis", "malware-analysis", "breakpoints", "memory", "zig" ], "use_cases": [ "Let an AI assistant drive x64dbg while analyzing a binary or suspected malware sample", "Automate breakpoint, register, memory and stepping workflows through a model-visible tool surface", "Give reverse-engineering agents debugger receipts instead of relying on screenshots or manual notes" ], "health": "active" }, { "id": "cove-book-forge-mcp", "name": "cove-book-forge-mcp", "description": "Local-first MCP server that turns PDF and EPUB books into cached AI analysis, Obsidian notes and installable Codex or Claude Agent Skills. It fingerprints chapters, reuses analysis across outputs, supports resumable whole-book jobs and exposes the book, chapter, output and job lifecycle through MCP. Public GitHub repository created August 21, 2026.", "category": "productivity", "endpoint": "https://github.com/moonlin1213/cove-book-forge-mcp", "homepage_url": "https://github.com/moonlin1213/cove-book-forge-mcp", "github_url": "https://github.com/moonlin1213/cove-book-forge-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/moonlin1213/cove-book-forge-mcp.git && cd cove-book-forge-mcp && pip install -e .", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "books", "pdf", "epub", "obsidian", "agent-skills", "knowledge-base", "reading", "python" ], "use_cases": [ "Forge a long PDF or EPUB into reusable agent skills instead of one-off chat summaries", "Cache chapter analysis so multiple outputs can reuse validated reading work without repeated model calls", "Publish book-derived notes to Obsidian or installable skill directories from one MCP workflow" ], "health": "active" }, { "id": "overleaf-mcp", "name": "Overleaf MCP", "description": "TypeScript MCP server for reading, searching, editing, committing and pushing Overleaf Git projects from MCP clients. It keeps Overleaf Git tokens in local configuration, scopes access to configured projects and gives assistants file-structure, line-range and targeted-edit tools for LaTeX collaboration. Public GitHub repository created August 22, 2026.", "category": "productivity", "endpoint": "https://github.com/fly233338/overleaf-mcp", "homepage_url": "https://github.com/fly233338/overleaf-mcp", "github_url": "https://github.com/fly233338/overleaf-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @fly233338/overleaf-mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "overleaf", "latex", "git", "academic-writing", "editing", "typescript", "stdio", "documents" ], "use_cases": [ "Let an AI coding assistant inspect and edit LaTeX files inside an Overleaf Git project", "Search project text, read line ranges and make targeted document edits from Claude or another MCP client", "Commit and push reviewed LaTeX changes back to Overleaf without exposing Git tokens in model-visible arguments" ], "health": "active" }, { "id": "delphi-ide-remote-mcp", "name": "Delphi IDE Remote MCP Server", "description": "Beta MCP server that remote-controls a Windows RAD Studio and Delphi environment from any MCP client. It combines official DelphiLSP semantic navigation, safe editing, MSBuild builds, git, scaffolding, remote file transfer and sandboxed run/deploy workflows over streamable HTTP or stdio. Public GitHub repository created August 19, 2026.", "category": "code", "endpoint": "https://github.com/soporte-defontsoft/delphi-ide-remote-mcp", "homepage_url": "https://github.com/soporte-defontsoft/delphi-ide-remote-mcp", "github_url": "https://github.com/soporte-defontsoft/delphi-ide-remote-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/soporte-defontsoft/delphi-ide-remote-mcp.git", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "delphi", "rad-studio", "object-pascal", "lsp", "msbuild", "remote-development", "windows", "http" ], "use_cases": [ "Let agents on macOS, Linux or cloud hosts work against a Delphi project held on a Windows RAD Studio machine", "Use DelphiLSP-backed semantic navigation plus safe file edits, builds and packaging from one MCP surface", "Keep Delphi tooling warm as a service while multiple AI clients perform read, edit and build workflows" ], "health": "active" }, { "id": "mcp-scribe", "name": "MCP Scribe", "description": "OpenAPI-to-MCP runtime that turns an API schema into a production-oriented MCP server at startup. It maps operations into model-callable tools with argument schemas, credentials, retries, rate limiting and response shaping while keeping the OpenAPI spec as the source of truth. Public GitHub repository created August 21, 2026.", "category": "code", "endpoint": "https://github.com/The-Swarm-Corporation/mcp-scribe", "homepage_url": "https://swarms.ai", "github_url": "https://github.com/The-Swarm-Corporation/mcp-scribe", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install mcp-scribe", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "openapi", "api-tools", "schema", "tool-generation", "rate-limiting", "credentials", "python", "mcp-gateway" ], "use_cases": [ "Expose a real API to agents by pointing MCP Scribe at its OpenAPI schema", "Avoid maintaining generated adapter code while still giving models typed tool schemas", "Add credential handling, retries, rate limits and response shaping around API operations" ], "health": "active" }, { "id": "game-asset-mcp", "name": "game-asset-mcp", "description": "MCP server for agentic game-asset generation, taking prompts or reference images through image, 3D model, PBR texture and provenance workflows. It supports new asset generation plus retexturing existing owned meshes, records provider task IDs and SHA-256 hashes, and can normalize meshes with optional Blender support. Public GitHub repository created August 24, 2026.", "category": "media", "endpoint": "https://github.com/theisegoria/game-asset-mcp", "homepage_url": "https://github.com/theisegoria/game-asset-mcp", "github_url": "https://github.com/theisegoria/game-asset-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/theisegoria/game-asset-mcp.git && cd game-asset-mcp && npm install && npm run build", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "game-assets", "3d", "gltf", "pbr", "image-to-3d", "text-to-3d", "tripo", "leonardo-ai" ], "use_cases": [ "Let a game-development agent generate reference images, meshes and textures as one traceable workflow", "Retexture an existing approved mesh with new PBR materials instead of regenerating geometry", "Keep provenance records for generated assets, including provider task IDs, seeds and downloaded-byte hashes" ], "health": "active" }, { "id": "typeship-mcp", "name": "Typeship MCP", "description": "Official MCP server for the Typeship API, generated from the Typeship OpenAPI spec with a compact discovery surface. It exposes search_docs, read_docs and execute tools, validates arguments from schema, supports field selection and can run in read-only mode for safer agent use. Public GitHub repository created August 23, 2026.", "category": "code", "endpoint": "https://github.com/typeship-ax/mcp", "homepage_url": "https://github.com/typeship-ax/mcp", "github_url": "https://github.com/typeship-ax/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y --package @typeship-ax/mcp typeship-mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "typeship", "openapi", "api-client", "schema-validation", "read-only", "typescript", "stdio", "developer-tools" ], "use_cases": [ "Let agents discover and call the Typeship API through generated schema-derived tools", "Use read_docs before execute so a model can inspect complete operation schemas and examples", "Run an API-backed MCP connector in read-only mode when exploration is safer than mutation" ], "health": "active" }, { "id": "polyrama-mcp", "name": "Polyrama MCP Server", "description": "Official MCP server for Polyrama, a prediction-market research terminal covering Polymarket and Kalshi. It gives MCP clients typed tools for market research, public Polymarket wallet analysis, signals and paper-only workflows through a local stdio package. Public GitHub repository created August 18, 2026.", "category": "data", "endpoint": "https://github.com/Polyrama/mcp", "homepage_url": "https://polyrama.io", "github_url": "https://github.com/Polyrama/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @polyrama/mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "prediction-markets", "polymarket", "kalshi", "wallet-analysis", "market-research", "signals", "typescript", "stdio" ], "use_cases": [ "Research Polymarket and Kalshi markets from an MCP-compatible assistant", "Analyze public Polymarket wallets and market signals without giving the agent trading authority", "Run paper-only prediction-market workflows from Claude, Codex, Cursor or similar clients" ], "health": "active" }, { "id": "unrealugc-mcp", "name": "UnrealUGC MCP Server", "description": "Official MCP server for UnrealUGC that lets MCP assistants browse creators and models, estimate credit costs and generate AI UGC video ads. It supports local stdio via npm and a hosted streamable HTTP endpoint for clients that can connect remotely. Public GitHub repository created August 18, 2026.", "category": "media", "endpoint": "https://github.com/UnrealUGC/mcp", "homepage_url": "https://unrealugc.com", "github_url": "https://github.com/UnrealUGC/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @unrealugc/mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "ai-video", "ugc", "video-generation", "creators", "credit-estimates", "ads", "typescript", "http" ], "use_cases": [ "Let a marketing or creative agent browse available UGC creators and models", "Estimate video-generation credit cost before launching an UnrealUGC job", "Generate AI UGC video ads from an MCP client through local stdio or hosted HTTP" ], "health": "active" }, { "id": "lakebrasil-mcp", "name": "lakebrasil-mcp", "description": "Live Brazilian government-data MCP server exposing federal and state sources including BACEN, IBGE, Câmara, Senado, Portal da Transparência, courts, elections, wildfire hotspots and postal-code datasets. Most tools read directly from original APIs or files without an account, with optional keys only for specific sources. Public GitHub repository created August 21, 2026.", "category": "data", "endpoint": "https://github.com/lakebrasil/mcp", "homepage_url": "https://github.com/lakebrasil/mcp", "github_url": "https://github.com/lakebrasil/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx lakebrasil-mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "brazil", "government-data", "bacen", "ibge", "transparency", "courts", "elections", "python" ], "use_cases": [ "Ask an agent for live Brazilian public data without bulk-downloading a full data lake", "Query economic, legislative, court, postal-code, election or wildfire sources from one MCP server", "Use original government APIs and files for fresh slices of Brazilian public records" ], "health": "active" }, { "id": "jira-alerts-mcp", "name": "Jira Alerts MCP", "description": "MCP server for Jira Service Management Operations, focused on the alerts and on-call surface that replaced Opsgenie. It can search alerts, read notes and activity timelines, acknowledge or close alerts, add responders and inspect current or upcoming on-call schedules. Public GitHub repository created August 21, 2026.", "category": "infrastructure", "endpoint": "https://github.com/rrvrs/jira-alerts-mcp", "homepage_url": "https://www.npmjs.com/package/jira-alerts-mcp", "github_url": "https://github.com/rrvrs/jira-alerts-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y jira-alerts-mcp", "added": "2026-08-24", "updated": "2026-08-24", "tags": [ "jira", "jsm", "alerts", "on-call", "opsgenie", "incident-response", "atlassian", "typescript" ], "use_cases": [ "Let an incident-response agent find active JSM Operations alerts and summarize what is paging the team", "Look up current and next on-call responders from an MCP client", "Acknowledge, annotate or close alerts when the workflow permits explicit write actions" ], "health": "active" }, { "id": "zameen-mcp", "name": "zameen-mcp", "description": "Read-only MCP server for researching Zameen.com property listings with AI. It supports verified and titanium listing filters, property watchlists and listing-detail lookups so real-estate agents can query Pakistani property inventory through a local stdio server. Public GitHub repository created August 25, 2026.", "category": "data", "endpoint": "https://github.com/lonewolfmasanaga/zameen.com-mcp", "homepage_url": "https://github.com/lonewolfmasanaga/zameen.com-mcp", "github_url": "https://github.com/lonewolfmasanaga/zameen.com-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx zameen-mcp", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "real-estate", "zameen", "property-search", "pakistan", "watchlists", "read-only", "python", "uvx" ], "use_cases": [ "Let an assistant search Zameen.com listings by natural-language real-estate criteria", "Track property watchlists and inspect verified or titanium listings from an MCP client", "Research Pakistani property inventory without giving the agent mutation authority" ], "health": "active" }, { "id": "lilypond-mcp", "name": "lilypond-mcp", "description": "MCP server that engraves GNU LilyPond source into cropped, placeable PDF, EPS, SVG and PNG music assets. It exposes tools for engraving files or inline code and returns LilyPond diagnostics with line numbers so agents can iterate on notation and produce assets for InDesign or other layout software. Public GitHub repository created August 24, 2026.", "category": "media", "endpoint": "https://github.com/wspringer/lilypond-mcp", "homepage_url": "https://github.com/wspringer/lilypond-mcp", "github_url": "https://github.com/wspringer/lilypond-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/wspringer/lilypond-mcp.git && cd lilypond-mcp && npm install && npm run build", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "music-notation", "lilypond", "engraving", "pdf", "svg", "eps", "png", "layout" ], "use_cases": [ "Have an agent generate printable music fragments from LilyPond code", "Produce cropped notation assets for publishing or page-layout workflows", "Use compiler diagnostics to revise broken LilyPond snippets through an MCP loop" ], "health": "active" }, { "id": "brightdata-mcp-studio", "name": "Bright Data MCP Studio", "description": "Fork of Bright Data's MCP server that adds a Scraper Studio lifecycle for public-site scraper creation, breakage detection, repair and verification. It keeps Bright Data API access behind a local stdio package and exposes the expanded scraper workflow to Claude Code, Claude Desktop, Cursor and other MCP clients. Public GitHub repository created August 19, 2026.", "category": "web", "endpoint": "https://github.com/Dinesh210805/brightdata-mcp-studio", "homepage_url": "https://www.npmjs.com/package/brightdata-mcp-studio", "github_url": "https://github.com/Dinesh210805/brightdata-mcp-studio", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y brightdata-mcp-studio", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "bright-data", "web-scraping", "scraper-studio", "crawler", "repair", "verification", "typescript", "npx" ], "use_cases": [ "Let an agent build and verify a scraper for a public website through Bright Data", "Detect and repair broken extraction flows instead of manually rewriting scraper code", "Expose Bright Data web access to MCP clients with API-token based local configuration" ], "health": "active" }, { "id": "amazing-marvin-complete-mcp", "name": "Amazing Marvin Complete MCP", "description": "Python MCP server for Amazing Marvin with broad public-API coverage across tasks, projects, labels, planning and productivity workflows. It packages live-verified API findings into a local stdio connector so assistants can inspect and manage an Amazing Marvin account through typed tools. Public GitHub repository created August 19, 2026.", "category": "productivity", "endpoint": "https://github.com/andreasd083/amazing-marvin-complete-mcp", "homepage_url": "https://github.com/andreasd083/amazing-marvin-complete-mcp", "github_url": "https://github.com/andreasd083/amazing-marvin-complete-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/andreasd083/amazing-marvin-complete-mcp.git && cd amazing-marvin-complete-mcp && python3 -m venv .venv && .venv/bin/pip install .", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "amazing-marvin", "tasks", "productivity", "planning", "projects", "labels", "python", "stdio" ], "use_cases": [ "Ask an assistant to inspect tasks, projects and planning data in Amazing Marvin", "Automate personal-productivity maintenance through typed MCP tools", "Use a local server with the user account API key instead of pasting task data into chat" ], "health": "active" }, { "id": "unraid-mcp", "name": "Unraid MCP", "description": "Security-conscious MCP server for managing Unraid through its official GraphQL API. It emphasizes pinned dependencies, lockfile-frozen installs and least-privilege configuration while exposing server, Docker, VM and storage-management workflows to MCP clients. Public GitHub repository created August 19, 2026.", "category": "infrastructure", "endpoint": "https://github.com/lemanjo/unraid-mcp", "homepage_url": "https://github.com/lemanjo/unraid-mcp", "github_url": "https://github.com/lemanjo/unraid-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/lemanjo/unraid-mcp.git && cd unraid-mcp && pnpm install --frozen-lockfile && pnpm build", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "unraid", "nas", "graphql", "docker", "virtual-machines", "storage", "security", "typescript" ], "use_cases": [ "Let an infrastructure agent inspect and manage an Unraid host through its official API", "Expose NAS, Docker and VM operations to MCP without scraping the Unraid web UI", "Run a security-hardened local connector with pinned dependencies and explicit credentials" ], "health": "active" }, { "id": "goalslot-mcp", "name": "goalslot-mcp", "description": "MCP server for GoalSlot that exposes goals, tasks, weekly schedule templates, time tracking, shared timer data, reports, notes and journal entries as agent tools. It runs over stdio and reads credentials from the companion GoalSlot CLI rather than prompting inside the MCP session. Public GitHub repository created August 25, 2026.", "category": "productivity", "endpoint": "https://github.com/ZeeshanAdilButt/goalslot-mcp", "homepage_url": "https://goalslot.io", "github_url": "https://github.com/ZeeshanAdilButt/goalslot-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/ZeeshanAdilButt/goalslot-mcp.git && cd goalslot-mcp && npm install && npm run build", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "goals", "tasks", "time-tracking", "journal", "weekly-planning", "reports", "typescript", "stdio" ], "use_cases": [ "Ask an assistant to review goals, weekly plans and current task status in GoalSlot", "Log time, inspect reports or summarize journal entries from an MCP client", "Use an existing CLI login so the MCP server never handles an interactive auth flow" ], "health": "active" }, { "id": "mcp-server-healthcare", "name": "MCP Server Healthcare", "description": "Healthcare MCP server for NHS-oriented clinical coding and information-governance workflows. It can suggest ICD-10-CM, OPCS-4 and HCC codes, track SAR and FOI requests, classify DSAR mapping requests, batch-code notes and connect to a Cerner FHIR R4 sandbox when credentials are configured. Public GitHub repository created August 25, 2026.", "category": "data", "endpoint": "https://github.com/bobbynoble/MCP_Server_Healthcare", "homepage_url": "https://github.com/bobbynoble/MCP_Server_Healthcare", "github_url": "https://github.com/bobbynoble/MCP_Server_Healthcare", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/bobbynoble/MCP_Server_Healthcare.git && cd MCP_Server_Healthcare && pip install -r requirements.txt", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "healthcare", "clinical-coding", "nhs", "fhir", "cerner", "dsar", "foi", "python" ], "use_cases": [ "Suggest clinical codes from a note while keeping the coding workflow inside an MCP client", "Track SAR, FOI and DSAR information-governance requests with agent-readable tools", "Query or write Cerner FHIR sandbox data when the matching credentials are configured" ], "health": "active" }, { "id": "superoffice-mcp-server", "name": "SuperOffice CRM Onsite MCP Server", "description": "TypeScript MCP server for SuperOffice CRM Onsite installations using the SuperOffice REST WebAPI. It lets MCP clients query contacts, persons, appointments, support tickets, custom extra tables and audit logs through native stdio transport. Public GitHub repository created August 25, 2026.", "category": "productivity", "endpoint": "https://github.com/alihaider663/superoffice-mcp-server", "homepage_url": "https://github.com/alihaider663/superoffice-mcp-server", "github_url": "https://github.com/alihaider663/superoffice-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/alihaider663/superoffice-mcp-server.git && cd superoffice-mcp-server && npm install && npm run build", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "superoffice", "crm", "contacts", "appointments", "support-tickets", "audit-logs", "typescript", "stdio" ], "use_cases": [ "Let a sales or support assistant search SuperOffice CRM records from an MCP client", "Inspect contacts, appointments, support tickets and custom extra tables through typed tools", "Use a local stdio bridge against an onsite SuperOffice REST WebAPI deployment" ], "health": "active" }, { "id": "odoo-mcp", "name": "odoo-mcp", "description": "Early MCP server for Odoo ERP that exposes partners, sales orders, stock levels and invoices as task-oriented tools over a Docker-backed local setup. It narrows Odoo's broad XML-RPC API into named workflows an LLM agent can call without knowing model names or domain syntax. Public GitHub repository created August 25, 2026.", "category": "productivity", "endpoint": "https://github.com/SaintsFlow/odoo-mcp", "homepage_url": "https://github.com/SaintsFlow/odoo-mcp", "github_url": "https://github.com/SaintsFlow/odoo-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/SaintsFlow/odoo-mcp.git && cd odoo-mcp && docker compose up mcp", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "odoo", "erp", "sales-orders", "inventory", "invoices", "xml-rpc", "docker", "business-ops" ], "use_cases": [ "Ask an agent to find Odoo customers, suppliers, sales orders or invoices", "Expose stock and order status through named tools instead of raw XML-RPC calls", "Test ERP workflows against an Odoo Community demo stack before connecting real data" ], "health": "active" }, { "id": "obsidian-vault-search-mcp", "name": "Obsidian Vault Search MCP", "description": "Local-first Obsidian search MCP server using Python standard-library code, SQLite indexing, BM25 retrieval and optional OpenAI-compatible semantic reranking or aggregation. It keeps vault indexes on disk, supports Chinese bigram tokenization and works without an API key for basic retrieval. Public GitHub repository created August 25, 2026.", "category": "productivity", "endpoint": "https://github.com/johnadams-bot/obsidian-vault-search-mcp", "homepage_url": "https://github.com/johnadams-bot/obsidian-vault-search-mcp", "github_url": "https://github.com/johnadams-bot/obsidian-vault-search-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/johnadams-bot/obsidian-vault-search-mcp.git", "added": "2026-08-25", "updated": "2026-08-25", "tags": [ "obsidian", "notes", "local-search", "bm25", "sqlite", "chinese", "knowledge-base", "python" ], "use_cases": [ "Find Obsidian notes by meaning or fuzzy remembered content from an MCP client", "Build a local SQLite index of a vault without sending notes to a hosted service", "Optionally rerank or summarize matching notes with any OpenAI-compatible LLM endpoint" ], "health": "active" }, { "id": "doop-mcp", "name": "Doop MCP", "description": "Built-in MCP server for Doop, an open-source multiplayer design canvas where humans and AI agents design together live. Agents connect over HTTP with OAuth, create and edit frames, stream design work into shared canvases, set status, and inherit the same access boundaries as the human who authorized them. Public GitHub repository created August 22, 2026.", "category": "media", "endpoint": "https://doop.design/mcp", "homepage_url": "https://doop.design", "github_url": "https://github.com/kgoedecke/doop", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "git clone https://github.com/kgoedecke/doop.git && cd doop && npm install && npm run dev", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "design", "canvas", "multiplayer", "ai-agents", "oauth", "frames", "collaboration", "typescript" ], "use_cases": [ "Let Claude Code or another MCP client create and revise design frames inside a live multiplayer canvas", "Watch an agent stream UI or brand explorations while human collaborators see presence and activity in real time", "Self-host an agent-readable design workspace with embedded Postgres and optional hosted deployment" ], "health": "active" }, { "id": "swissdevjobs-cli-mcp", "name": "swissdevjobs-cli MCP", "description": "Zero-dependency Python CLI and MCP server for salary-transparent developer job search across SwissDevJobs and sister boards covering Switzerland, Germany, the UK, US, Canada, Netherlands, France, plus jobs.ch, jobup.ch and Singapore IT listings. It gives agents JSON-first job search, salary filters and applied-job memory. Public GitHub repository created August 24, 2026.", "category": "productivity", "endpoint": "https://github.com/Stupidoodle/swissdevjobs-cli", "homepage_url": "https://github.com/Stupidoodle/swissdevjobs-cli", "github_url": "https://github.com/Stupidoodle/swissdevjobs-cli", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx --from git+https://github.com/Stupidoodle/swissdevjobs-cli sdj mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "jobs", "salary-transparency", "developer-jobs", "job-search", "python", "uvx", "sqlite", "claude-code" ], "use_cases": [ "Ask an agent to find developer roles by technology, region, remote status and minimum salary", "Track already-applied jobs locally so repeated searches hide duplicates", "Use salary-published job boards as structured JSON context for career and recruiting workflows" ], "health": "active" }, { "id": "hasdata-google-search-mcp", "name": "HasData Google Search MCP", "description": "Hosted Google Search and SERP MCP server from HasData. It exposes read-only tools for live organic results, AI Overview, People Also Ask, AI Mode, news, shopping, product detail and short-video result data without needing a Google Cloud project. Public GitHub repository created August 21, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=google_serp", "homepage_url": "https://hasdata.com/apis/google-serp-api", "github_url": "https://github.com/HasData/google-search-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/google-search-mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "google-search", "serp", "ai-overview", "people-also-ask", "news", "shopping", "hasdata", "http" ], "use_cases": [ "Give an assistant live Google SERP context as structured JSON from a hosted MCP endpoint", "Retrieve AI Overview, People Also Ask and news or shopping results without a Google Cloud project", "Connect Claude, Cursor, Windsurf or another HTTP MCP client with a HasData API key" ], "health": "active" }, { "id": "quantified-self-mcp", "name": "Quantified Self MCP Server", "description": "Local FastMCP server that lets assistants query personal health and finance data stored in local SQLite databases. It includes tools for health metrics such as steps, sleep and resting heart rate, plus categorized expense ledgers with summaries, while keeping generated data folders and database files out of version control. Public GitHub repository created August 25, 2026.", "category": "data", "endpoint": "https://github.com/Thecimal/quantified-self-mcp", "homepage_url": "https://github.com/Thecimal/quantified-self-mcp", "github_url": "https://github.com/Thecimal/quantified-self-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Thecimal/quantified-self-mcp.git && cd quantified-self-mcp && python3 -m venv .venv && . .venv/bin/activate && pip install -r requirements.txt", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "quantified-self", "health", "finance", "sqlite", "local-first", "fastmcp", "python", "personal-data" ], "use_cases": [ "Ask an assistant to summarize recent sleep, steps and resting-heart-rate trends from local data", "Query categorized spending and totals from a personal SQLite finance ledger", "Keep sensitive self-tracking data local while still exposing bounded read tools to an MCP client" ], "health": "active" }, { "id": "your-mail-mcp", "name": "your-mail-mcp", "description": "Self-hosted read-only mail MCP server that mirrors IMAP accounts into local maildir, indexes them with notmuch, and serves question-oriented mail search over authenticated Streamable HTTP. It is designed for always-on agents and scheduled digests where sending, deleting and moving mail are intentionally unavailable. Public GitHub repository created August 20, 2026.", "category": "communication", "endpoint": "https://github.com/wildsurfer/your-mail-mcp", "homepage_url": "https://github.com/wildsurfer/your-mail-mcp", "github_url": "https://github.com/wildsurfer/your-mail-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "git clone https://github.com/wildsurfer/your-mail-mcp.git && cd your-mail-mcp && docker compose up -d", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "email", "imap", "notmuch", "maildir", "read-only", "oauth", "self-hosted", "http" ], "use_cases": [ "Find booking references, invoices, access codes or promises buried in old email threads", "Generate read-only morning triage across multiple IMAP accounts from a local index", "Use email as context for writing or coding work without granting an agent mailbox mutation tools" ], "health": "active" }, { "id": "licenseguard-mcp", "name": "LicenseGuard MCP", "description": "MCP server and web tool for dependency-license obligations by distribution model. It checks whether a package, manifest or lockfile creates obligations for SaaS, internal use, distributed binaries, on-prem deployments or devDependency-only use, citing clauses instead of returning generic scanner warnings. Public GitHub repository created August 20, 2026.", "category": "code", "endpoint": "https://license-guard.rcc-aoki.workers.dev/mcp", "homepage_url": "https://licenseguard.tenchorooms.com", "github_url": "https://github.com/rccaoki-wq/license-guard", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "docker run -i --rm ghcr.io/rccaoki-wq/license-guard:1.1.0", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "licenses", "compliance", "spdx", "copyleft", "agpl", "dependencies", "supply-chain", "cloudflare-workers" ], "use_cases": [ "Check a dependency license before adding it to a project with a specific shipping model", "Audit package manifests or lockfiles for obligations that generic scanners over-warn about", "Explain GPL, AGPL, LGPL, MPL, EPL and CDDL obligations with distribution-specific context" ], "health": "active" }, { "id": "geo-tool-check-mcp", "name": "geo-tool-check MCP", "description": "CLI, stdio MCP server and hosted Streamable HTTP MCP endpoint for generative-engine-optimization checks. It scores crawler access, structure and citability for ChatGPT, Perplexity, Claude and Google AI, including robots.txt checks for AI crawlers and content quotability analysis. Public GitHub repository created August 25, 2026.", "category": "web", "endpoint": "https://www.geo-tool.com/mcp", "homepage_url": "https://www.geo-tool.com/en/developers", "github_url": "https://github.com/geo-tool-com/geo-tool-check", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "npx -y geo-tool-check --mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "geo", "ai-search", "seo", "robots-txt", "citability", "llms-txt", "crawler-access", "http" ], "use_cases": [ "Ask an assistant whether a page is readable and quotable by AI search systems", "Check robots.txt exposure for GPTBot, OAI-SearchBot, ClaudeBot and other AI crawlers", "Run local or hosted readiness checks before publishing pages meant to be cited by LLM search" ], "health": "active" }, { "id": "base-tx-explain-mcp", "name": "base-tx-explain MCP", "description": "Paid MCP server that deterministically decodes Base mainnet transactions into strict JSON and plain-English summaries. The explain_transaction tool reports action type, assets moved, counterparties, risk flags, contract-verification checks, gas in USD, timestamps and block data with no LLM in the response path. Public GitHub repository created August 20, 2026.", "category": "payments", "endpoint": "https://base-tx-explain.fly.dev/mcp", "homepage_url": "https://0200project.com/docs/", "github_url": "https://github.com/0200project/base-tx-explain", "x402": true, "x402_price": "$0.02/call", "verified": false, "protocols": [ "MCP", "x402" ], "transport": "http", "auth": "x402", "install_cmd": "https://base-tx-explain.fly.dev/mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "base", "ethereum", "transactions", "decoder", "x402", "crypto-payments", "risk-flags", "onchain" ], "use_cases": [ "Explain a Base transaction hash with deterministic structured output rather than model guesses", "Inspect token movements, counterparties, gas cost and contract verification for agent payment workflows", "Use an x402-paid MCP endpoint for low-cost transaction decoding in autonomous agent pipelines" ], "health": "active" }, { "id": "bestprice-mcp", "name": "BestPrice MCP", "description": "Official BestPrice.gr Streamable HTTP MCP endpoint for live product search, offer comparison and price-history lookups. The read-only public service exposes search_products, compare_offers and get_price_history without requiring a BestPrice account or API key. Public GitHub repository created August 26, 2026.", "category": "web", "endpoint": "https://mcp.bestprice.gr/mcp", "homepage_url": "https://www.bestprice.gr/mcp", "github_url": "https://github.com/TheBestCo/bestprice-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "qwen mcp add --scope user --transport http bestprice-shopping https://mcp.bestprice.gr/mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "shopping", "price-comparison", "products", "offers", "price-history", "bestprice", "streamable-http", "read-only" ], "use_cases": [ "Search products and compare live offers from BestPrice.gr through an MCP-compatible assistant", "Retrieve 180-day price history before recommending a purchase or price target", "Connect Gemini CLI, Qwen Code, DeepSeek Harness or another HTTP MCP client to a read-only shopping endpoint" ], "health": "active" }, { "id": "saripati-mcp", "name": "SARIPATI MCP", "description": "Local-first provider-agnostic MCP knowledge vault for AI hosts. SARIPATI stores structured findings, reusable notes and session digests in SQLite, supports hybrid semantic plus FTS5 recall with local MiniLM embeddings, and includes a read-only dashboard for browsing the accumulated corpus. Public GitHub repository created August 26, 2026.", "category": "productivity", "endpoint": "https://github.com/kyouscireul/saripati", "homepage_url": "https://github.com/kyouscireul/saripati", "github_url": "https://github.com/kyouscireul/saripati", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y saripati mcp", "added": "2026-08-26", "updated": "2026-08-26", "tags": [ "memory", "knowledge-base", "sqlite", "local-first", "semantic-search", "fts5", "embeddings", "npx" ], "use_cases": [ "Give Claude Code, Cursor, Windsurf or another AI host a local cross-session research memory", "Save structured findings, decisions and reusable patterns without depending on a cloud account", "Recall accumulated work by hybrid semantic and keyword search from a single SQLite vault" ], "health": "active" }, { "id": "agentseed", "name": "AgentSeed", "description": "Anti-hallucination gate for AI coding agents packaged as an Agent Plugins skill plus MCP server, hook and CI gate. It verifies code across 16 languages, scans for fabricated completion claims and requires runtime evidence before work is marked done. Public GitHub repository created August 25, 2026.", "category": "code", "endpoint": "https://github.com/Morningstar202604/AgentSeed", "homepage_url": "https://github.com/Morningstar202604/AgentSeed", "github_url": "https://github.com/Morningstar202604/AgentSeed", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Morningstar202604/AgentSeed.git && cd AgentSeed && bash install.sh --client auto --hooks", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "anti-hallucination", "code-verification", "ci", "agent-plugins", "hooks", "static-analysis", "guardrails", "evidence" ], "use_cases": [ "Gate coding-agent completion on observed checks instead of model self-report", "Catch invented APIs, undefined identifiers and fake all-tests-pass claims before review", "Add the same verification policy to local agent workflows and CI" ], "health": "active" }, { "id": "booking-mcp", "name": "Booking.com MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for read-only Booking.com search and property-detail retrieval. Agents can search stays by destination, dates and filters, then fetch full public property data as structured JSON without a Booking.com account or local scraper. Public GitHub repository created August 24, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=booking", "homepage_url": "https://github.com/HasData/booking-mcp", "github_url": "https://github.com/HasData/booking-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/booking-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "booking", "travel", "hotels", "stays", "property-search", "hasdata", "streamable-http", "json" ], "use_cases": [ "Search hotel and stay options by destination, dates and travel filters", "Retrieve full public Booking.com property details for itinerary planning", "Give travel agents structured lodging context without running browser automation" ], "health": "active" }, { "id": "zillow-mcp", "name": "Zillow MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for Zillow listing search and property details. It exposes read-only tools for for-sale, for-rent and sold listings with rich filters, returning public listing data as structured JSON without a Zillow account. Public GitHub repository created August 24, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=zillow", "homepage_url": "https://github.com/HasData/zillow-mcp", "github_url": "https://github.com/HasData/zillow-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/zillow-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "zillow", "real-estate", "property-search", "rentals", "sold-listings", "hasdata", "streamable-http", "housing" ], "use_cases": [ "Let an assistant compare for-sale, rental and sold listings in a target market", "Fetch structured property details for real-estate research or relocation planning", "Use public Zillow data in agent workflows without a partner API integration" ], "health": "active" }, { "id": "google-flights-mcp", "name": "Google Flights MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for Google Flights-style itinerary search. It returns one-way, round-trip and multi-city flight options with fares, legs, carbon emissions and price-history signals as structured JSON. Public GitHub repository created August 24, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=google_travel_flights", "homepage_url": "https://github.com/HasData/google-flights-mcp", "github_url": "https://github.com/HasData/google-flights-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/google-flights-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "flights", "travel", "fares", "itineraries", "price-history", "carbon-emissions", "hasdata", "streamable-http" ], "use_cases": [ "Search one-way, round-trip and multi-city itineraries from an MCP client", "Compare flight fares, legs and emissions before making travel recommendations", "Use structured flight search where a retired or unavailable travel API would otherwise be needed" ], "health": "active" }, { "id": "airbnb-mcp", "name": "Airbnb MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for read-only Airbnb stay search and listing details. It searches public listings by location and dates, then returns full listing data as structured JSON without an Airbnb developer account or partner approval. Public GitHub repository created August 24, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=airbnb", "homepage_url": "https://github.com/HasData/airbnb-mcp", "github_url": "https://github.com/HasData/airbnb-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/airbnb-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "airbnb", "travel", "stays", "short-term-rentals", "listing-search", "hasdata", "streamable-http", "json" ], "use_cases": [ "Search Airbnb stays by location and travel dates from Claude, Cursor or another MCP client", "Read detailed public listing data for lodging comparisons", "Build travel-planning workflows without maintaining an Airbnb scraper" ], "health": "active" }, { "id": "indeed-mcp", "name": "Indeed MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for read-only Indeed job search and job-post detail retrieval. Agents can search public postings by keyword and location, then retrieve full structured posting data without an Indeed developer account. Public GitHub repository created August 24, 2026.", "category": "productivity", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=indeed", "homepage_url": "https://github.com/HasData/indeed-mcp", "github_url": "https://github.com/HasData/indeed-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/indeed-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "indeed", "jobs", "recruiting", "job-search", "career", "hasdata", "streamable-http", "json" ], "use_cases": [ "Search job listings by role, keyword and location as structured MCP output", "Retrieve full public job postings for candidate matching or career research", "Feed recruiting agents current job-market data without browser automation" ], "health": "active" }, { "id": "google-trends-mcp", "name": "Google Trends MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for Google Trends data. It exposes a read-only trends tool returning interest over time, interest by region, and rising or top related queries and topics for arbitrary search terms as structured JSON. Public GitHub repository created August 24, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=google_trends", "homepage_url": "https://github.com/HasData/google-trends-mcp", "github_url": "https://github.com/HasData/google-trends-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/google-trends-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "google-trends", "trend-analysis", "search-interest", "market-research", "related-queries", "hasdata", "streamable-http", "json" ], "use_cases": [ "Ask an assistant to compare search interest for products, topics or brands", "Pull regional trend data and related queries for market research", "Monitor rising topics without maintaining a Trends scraping stack" ], "health": "active" }, { "id": "duckduckgo-mcp", "name": "DuckDuckGo MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for DuckDuckGo search results. It returns ranked organic results, ads in a separate array, DuckDuckGo AI answers and region-targeted search output as structured JSON for MCP clients. Public GitHub repository created August 20, 2026.", "category": "web", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=duckduckgo", "homepage_url": "https://github.com/HasData/duckduckgo-mcp", "github_url": "https://github.com/HasData/duckduckgo-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/duckduckgo-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "duckduckgo", "search", "serp", "ai-answer", "regional-search", "hasdata", "streamable-http", "json" ], "use_cases": [ "Give agents privacy-oriented web search results through a hosted MCP endpoint", "Retrieve organic results and ad blocks separately for SERP analysis", "Target DuckDuckGo searches by region without running a local browser" ], "health": "active" }, { "id": "instagram-mcp", "name": "Instagram MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for read-only public Instagram data. It lets agents look up public profiles by handle and walk public post feeds as structured JSON without signing in, posting, or acting as an Instagram account. Public GitHub repository created August 21, 2026.", "category": "media", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=instagram", "homepage_url": "https://github.com/HasData/instagram-mcp", "github_url": "https://github.com/HasData/instagram-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/instagram-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "instagram", "social-media", "public-profiles", "post-feeds", "creator-research", "hasdata", "streamable-http", "read-only" ], "use_cases": [ "Research public Instagram profiles and feeds from an MCP-compatible assistant", "Collect structured public social context for creator, brand or campaign analysis", "Avoid account-bound social actions by using read-only public-data tools" ], "health": "active" }, { "id": "tiktok-mcp", "name": "TikTok MCP by HasData", "description": "Hosted Streamable HTTP MCP server from HasData for read-only public TikTok data. It exposes tools for public profile lookup, account video feeds, video comments and TikTok keyword search, returning structured JSON without OAuth or a TikTok developer account. Public GitHub repository created August 24, 2026.", "category": "media", "endpoint": "https://mcp.hasdata.com/api/mcp?apis=tiktok", "homepage_url": "https://github.com/HasData/tiktok-mcp", "github_url": "https://github.com/HasData/tiktok-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "npx -y @hasdata/tiktok-mcp", "added": "2026-08-27", "updated": "2026-08-27", "tags": [ "tiktok", "social-video", "public-profiles", "comments", "keyword-search", "hasdata", "streamable-http", "read-only" ], "use_cases": [ "Search TikTok videos or creators from an MCP client", "Fetch public profile, video-feed and comment data for trend analysis", "Give research agents TikTok context without signing into or acting through an account" ], "health": "active" }, { "id": "exoscale-mcp", "name": "Exoscale MCP Server", "description": "MCP server for managing Exoscale cloud infrastructure from AI assistants. It exposes composite tools across Compute, SKS Kubernetes, DNS, DBaaS, block storage and object storage, supports stdio and Streamable HTTP transports, and runs read-only by default unless writes are explicitly enabled. Public GitHub repository created August 27, 2026.", "category": "infrastructure", "endpoint": "https://github.com/samisouabni/exoscale-mcp", "homepage_url": "https://github.com/samisouabni/exoscale-mcp", "github_url": "https://github.com/samisouabni/exoscale-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @samisouabni/exoscale-mcp", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "exoscale", "cloud", "infrastructure", "kubernetes", "dns", "dbaas", "object-storage", "read-only" ], "use_cases": [ "Let an assistant inventory Exoscale compute, DNS, Kubernetes and storage resources through bounded tools", "Run cloud-ops triage with read-only defaults before allowing mutating actions", "Expose Exoscale infrastructure context over local stdio or shared Streamable HTTP deployments" ], "health": "active" }, { "id": "pairbook-mcp", "name": "PairBook MCP", "description": "MCP server and CLI for PairBook financial market data covering 4,700+ US stocks and ETFs. It gives agents no-key access to correlations, ETF holdings overlap, beta and volatility through a free static JSON API refreshed after the US market close. Public GitHub repository created August 28, 2026.", "category": "data", "endpoint": "npx -y pairbook-mcp", "homepage_url": "https://www.pairbook.io", "github_url": "https://github.com/vj88-coder/pairbook-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y pairbook-mcp", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "stocks", "etfs", "finance", "correlation", "volatility", "holdings-overlap", "market-data", "no-key" ], "use_cases": [ "Compare two stocks or ETFs for return correlation, beta and volatility", "Check ETF portfolio overlap before an assistant suggests diversification ideas", "Use refreshed static financial data in research workflows without managing an API key" ], "health": "active" }, { "id": "brainferno-mcp-bridge", "name": "Brainferno MCP Bridge", "description": "MCP bridge that lets AI assistants drive Adobe Photoshop, After Effects, Premiere Pro, Illustrator, Audition and Media Encoder. It advertises more than 120 creative-production tools plus an ffmpeg lane, with per-application panels and live-run documentation. Public GitHub repository created August 26, 2026.", "category": "media", "endpoint": "https://github.com/Brainferno/brainferno-mcp-bridge", "homepage_url": "https://github.com/Brainferno/brainferno-mcp-bridge", "github_url": "https://github.com/Brainferno/brainferno-mcp-bridge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Brainferno/brainferno-mcp-bridge.git && cd brainferno-mcp-bridge && npm install", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "adobe", "photoshop", "after-effects", "premiere-pro", "illustrator", "audition", "media-encoder", "creative-automation" ], "use_cases": [ "Let a creative assistant manipulate Adobe project files and timelines through typed MCP tools", "Automate repetitive Photoshop, Premiere Pro or After Effects production steps", "Coordinate media editing workflows with ffmpeg and Adobe app-specific bridges" ], "health": "active" }, { "id": "attest-capture-mcp", "name": "Attest Capture MCP", "description": "Stdio MCP server for evidence-grade capture of public URLs through the Attest Capture API. Its capture_url tool returns screenshot, PDF or HTML artifacts with a SHA-256 digest, timestamp and optional public evidence page for audit trails. Public GitHub repository created August 25, 2026.", "category": "web", "endpoint": "npx -y attest-capture-mcp", "homepage_url": "https://getattest.com.au/capture", "github_url": "https://github.com/xthemarketmaker-cmyk/attest-capture-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y attest-capture-mcp", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "screenshots", "pdf", "html-capture", "evidence", "sha256", "timestamp", "audit", "web-archives" ], "use_cases": [ "Capture a public webpage as a screenshot, PDF or HTML artifact with verifiable metadata", "Attach timestamped evidence pages to compliance, QA or research reports", "Give agents a deterministic capture trail instead of relying on transient browser state" ], "health": "active" }, { "id": "adb-automation-mcp", "name": "ADB Automation MCP", "description": "MCP server exposing Android Debug Bridge capabilities as typed, documented tools and resources. It is packaged for uvx and PyPI, includes AI-assisted installation docs, and lets agents inspect or automate connected Android devices through ADB. Public GitHub repository created August 25, 2026.", "category": "code", "endpoint": "uvx adb-automation-mcp", "homepage_url": "https://allaudin.github.io/adb-automation-mcp/", "github_url": "https://github.com/allaudin/adb-automation-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx adb-automation-mcp", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "android", "adb", "mobile-testing", "device-automation", "python", "uvx", "qa", "developer-tools" ], "use_cases": [ "Let a coding assistant inspect connected Android devices through ADB", "Automate mobile QA steps from an MCP-compatible desktop or coding client", "Expose documented Android device resources without hand-writing shell wrappers" ], "health": "active" }, { "id": "mcp-toolhub", "name": "MCP ToolHub", "description": "Security-focused local stdio MCP server for coding agents. ToolHub exposes hardened filesystem and Git tools with workspace isolation, audit logs, approval-gated execution, and a separate trusted administrator CLI so the MCP client cannot self-approve risky actions. Public GitHub repository created August 26, 2026.", "category": "code", "endpoint": "https://github.com/asxvgxkep/mcp-toolhub", "homepage_url": "https://github.com/asxvgxkep/mcp-toolhub", "github_url": "https://github.com/asxvgxkep/mcp-toolhub", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uv tool install git+https://github.com/asxvgxkep/mcp-toolhub.git", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "security", "coding-agents", "filesystem", "git", "approval-gates", "audit-logs", "workspace-isolation", "stdio" ], "use_cases": [ "Give coding agents local file and Git tools with human approval gates", "Audit every tool call and risky execution request during agent development work", "Keep an MCP server stdio-only with no network listener for local workspace safety" ], "health": "active" }, { "id": "imslp-mcp", "name": "IMSLP MCP Server", "description": "MCP server for IMSLP, the Petrucci Music Library. It provides no-key read access to works, scores and recordings through the public IMSLP API, making classical-music metadata and score references available to assistants. Public GitHub repository created August 27, 2026.", "category": "media", "endpoint": "https://github.com/smeet666/mcp-imslp", "homepage_url": "https://github.com/smeet666/mcp-imslp", "github_url": "https://github.com/smeet666/mcp-imslp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/smeet666/mcp-imslp.git && cd mcp-imslp && npm install", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "imslp", "classical-music", "scores", "recordings", "metadata", "petrucci", "music-library", "no-key" ], "use_cases": [ "Search classical works, scores and recordings from an assistant", "Gather source links and metadata for musicology, education or repertoire planning", "Use public IMSLP catalog data without maintaining a custom scraper" ], "health": "active" }, { "id": "kitchensink4word", "name": "KitchenSink4Word", "description": "Large Microsoft Word .docx MCP server focused on avoiding document corruption. It advertises 170 tools for equations, Zotero citations, tables, footnotes, TOCs, tracked changes, live Word editing, comparison, protection, redaction, accessibility and compliance workflows. Public GitHub repository created August 27, 2026.", "category": "productivity", "endpoint": "https://github.com/nometalalchemist/KitchenSink4Word", "homepage_url": "https://nometalalchemist.github.io/KitchenSink4Word/", "github_url": "https://github.com/nometalalchemist/KitchenSink4Word", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx kitchensink4word", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "word", "docx", "documents", "citations", "tracked-changes", "tables", "redaction", "accessibility" ], "use_cases": [ "Let an assistant edit complex Word documents while preserving formatting and revision semantics", "Automate citations, tables, footnotes, front matter and accessibility checks in .docx files", "Run compliance, redaction and review-cycle workflows over long formatted documents" ], "health": "active" }, { "id": "canva-mcp-gemini-cli", "name": "Canva MCP Server for Gemini CLI", "description": "Production-oriented MCP server for the Canva Connect API, packaged for npx and aimed at Gemini CLI, Antigravity, Cursor and Claude-style clients. It lets agents design, manage and export Canva assets through typed tools with OAuth-backed Canva access. Public GitHub repository created August 27, 2026.", "category": "media", "endpoint": "npx -y --package @elisbanpaco/mcp-canva-gemini-cli mcp-canva", "homepage_url": "https://www.npmjs.com/package/@elisbanpaco/mcp-canva-gemini-cli", "github_url": "https://github.com/elisbanpaco/mcp-canva-gemini-cli", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y --package @elisbanpaco/mcp-canva-gemini-cli mcp-canva", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "canva", "design", "assets", "export", "gemini-cli", "antigravity", "oauth", "typescript" ], "use_cases": [ "Let design agents create, manage and export Canva assets through the Canva Connect API", "Connect Gemini CLI, Antigravity, Cursor or other MCP clients to Canva workflows", "Automate lightweight brand and campaign asset production from an assistant" ], "health": "active" }, { "id": "diag2md-mcp", "name": "diag2md MCP", "description": "MCP server that turns Draw.io C4 and UML diagrams into AI-readable Mermaid Markdown and architectural guardrails. It is intended for coding agents that must verify proposed changes against diagram source of truth before modifying code. Public GitHub repository created August 27, 2026.", "category": "code", "endpoint": "npx -y diag2md-mcp", "homepage_url": "https://github.com/diag2md/diag2md-mcp", "github_url": "https://github.com/diag2md/diag2md-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y diag2md-mcp", "added": "2026-08-28", "updated": "2026-08-28", "tags": [ "drawio", "c4", "uml", "mermaid", "architecture", "guardrails", "diagrams", "coding-agents" ], "use_cases": [ "Convert Draw.io architecture diagrams into Mermaid Markdown for agent context", "Force coding agents to check visual architecture source files before implementation", "Keep project changes aligned with C4 and UML diagrams during AI-assisted development" ], "health": "active" }, { "id": "assurance-mcp", "name": "Assurance MCP", "description": "Read-only MCP server for assurance checks over local folders and documents. It helps agents ask what they missed, whether a document still matches its source, and where coverage or staleness risks remain, while explicitly avoiding writes, deletes and network access. Public GitHub repository created August 29, 2026.", "category": "code", "endpoint": "python -m assurance_mcp.server", "homepage_url": "https://github.com/i-ops-hq/assurance-mcp", "github_url": "https://github.com/i-ops-hq/assurance-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install assurance-mcp", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "assurance", "coverage", "staleness", "documents", "read-only", "local-files", "python", "audit" ], "use_cases": [ "Ask an assistant to check whether a folder or document has coverage gaps before delivery", "Compare written outputs against source material for stale or missing claims", "Run local assurance checks with a read-only MCP server that opens no network access" ], "health": "active" }, { "id": "distil-mcp", "name": "Distil MCP", "description": "Rust crate, benchmark harness and MCP server for measuring what context compression costs an LLM agent. It analyzes where session tokens go, whether rewrites pay for invalidated prompt cache, and exposes context-compression measurement workflows through MCP. Public GitHub repository created August 28, 2026.", "category": "ai", "endpoint": "npx -y @munhq/distil", "homepage_url": "https://github.com/munhq/distil", "github_url": "https://github.com/munhq/distil", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @munhq/distil", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "context-compression", "token-analysis", "benchmark", "rust", "prompt-cache", "llm-evaluation", "no-key", "agent-sessions" ], "use_cases": [ "Measure token distribution and cache tradeoffs across real agent transcripts", "Benchmark context compression strategies before adding them to an agent stack", "Expose context cost diagnostics to MCP-compatible development clients" ], "health": "active" }, { "id": "termmirror", "name": "TermMirror", "description": "MCP server that gives agents real interactive terminal sessions with PTY support, TUI handling, REPLs, SSH flows and a live web view a human can watch or type into. It is designed for terminal work that normal command wrappers cannot reach. Public GitHub repository created August 27, 2026.", "category": "code", "endpoint": "node /absolute/path/to/termmirror/dist/src/index.js", "homepage_url": "https://github.com/Ar9av/termmirror", "github_url": "https://github.com/Ar9av/termmirror", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm install termmirror", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "terminal", "pty", "tui", "repl", "ssh", "human-in-loop", "recording", "developer-tools" ], "use_cases": [ "Let an agent drive installers, REPLs or TUI applications that need a real terminal", "Watch and intervene in an agent terminal session through a live browser view", "Record interactive terminal sessions as asciicast, GIF or video artifacts" ], "health": "active" }, { "id": "proton-safe-mcp", "name": "Proton Safe MCP", "description": "Draft-only Proton Mail MCP server built on Proton Mail Bridge. It can read and search mail, create drafts with attachments, and requires out-of-band human approval in a local terminal before draft creation; it deliberately cannot send email. Public GitHub repository created August 29, 2026.", "category": "communication", "endpoint": "uv run proton-safe-mcp", "homepage_url": "https://fbossiere.github.io/proton-safe-mcp/", "github_url": "https://github.com/fbossiere/proton-safe-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/fbossiere/proton-safe-mcp.git && cd proton-safe-mcp && uv run proton-safe-mcp setup", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "proton-mail", "email", "draft-only", "attachments", "human-approval", "imap", "proton-bridge", "security" ], "use_cases": [ "Let an assistant search Proton Mail while keeping SMTP send capability out of scope", "Create Proton Mail drafts with attachments for human review before sending", "Reduce email prompt-injection blast radius with draft-only and local-approval boundaries" ], "health": "active" }, { "id": "tfnsw-trip-planner-mcp", "name": "TfNSW Trip Planner MCP Server", "description": "MCP server exposing Transport for NSW Trip Planner APIs through Streamable HTTP and legacy SSE endpoints. It provides tools for stop search, journey planning, live departure boards and service data using a TfNSW Open Data API key. Public GitHub repository created August 29, 2026.", "category": "data", "endpoint": "https://your-host/mcp", "homepage_url": "https://github.com/maxim75/tfnsw_trip_planner_mcp", "github_url": "https://github.com/maxim75/tfnsw_trip_planner_mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/maxim75/tfnsw_trip_planner_mcp.git", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "transport", "nsw", "transit", "journey-planning", "departures", "streamable-http", "sse", "api-key" ], "use_cases": [ "Plan public transport journeys in New South Wales from an MCP-compatible assistant", "Query live departure boards, stops and service details through the TfNSW APIs", "Bridge header-authenticated transit APIs into clients that support HTTP or SSE MCP transports" ], "health": "active" }, { "id": "fast-mcp-jobvite", "name": "FastMCP Jobvite", "description": "FastMCP server that exposes Jobvite applicant-tracking data as bounded MCP tools. It supports candidate and job-feed workflows with configurable tool allow-lists, stdio or HTTP transport, and pinned uv dependencies. Public GitHub repository created August 27, 2026.", "category": "productivity", "endpoint": "uv run --frozen fastmcp inspect src/fast_mcp_jobvite/server.py:create_server", "homepage_url": "https://github.com/evolvconsulting/fast-mcp-jobvite", "github_url": "https://github.com/evolvconsulting/fast-mcp-jobvite", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/evolvconsulting/fast-mcp-jobvite.git && cd fast-mcp-jobvite && uv run --frozen fastmcp inspect src/fast_mcp_jobvite/server.py:create_server", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "jobvite", "recruiting", "ats", "candidates", "job-feed", "fastmcp", "python", "http" ], "use_cases": [ "Let recruiting assistants search jobs and candidate records from Jobvite", "Expose only selected ATS tools through an allow-list for safer agent workflows", "Run Jobvite MCP locally over stdio or bind an authenticated HTTP transport on loopback" ], "health": "active" }, { "id": "sheetcraft-mcp", "name": "SheetCraft MCP", "description": "Google Sheets MCP server and CLI with 34 tools across six opt-in toolsets. It supports token-efficient reads, teaching errors, OAuth or service-account authentication, and shared commands for both agent tools and terminal workflows. Public GitHub repository created August 28, 2026.", "category": "productivity", "endpoint": "npx -y sheetcraft-mcp@latest", "homepage_url": "https://github.com/P4rthPat3l/sheetcraft-mcp", "github_url": "https://github.com/P4rthPat3l/sheetcraft-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y sheetcraft-mcp@latest auth login", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "google-sheets", "spreadsheets", "oauth", "service-account", "cli", "token-efficient", "npx", "productivity" ], "use_cases": [ "Let an assistant read, update and manage Google Sheets through opt-in toolsets", "Use OAuth for personal spreadsheet access or service accounts for shared files", "Keep Sheets automation setup teachable with errors that tell agents exactly what to run" ], "health": "active" }, { "id": "webscout-mcp", "name": "WebScout MCP", "description": "Web search and fetch MCP server with built-in caching, rate limiting and content extraction. The current MCP surface exposes core search, fetch, crawl, extract and cache tools with zero API keys required, plus CLI and Python interfaces. Public GitHub repository created August 26, 2026.", "category": "web", "endpoint": "webscout-mcp", "homepage_url": "https://wxs-lang.github.io/webscout-mcp/", "github_url": "https://github.com/wxs-lang/webscout-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install webscout-mcp", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "web-search", "fetch", "crawl", "extract", "cache", "rate-limiting", "python", "no-key" ], "use_cases": [ "Give agents a no-key web search and fetch surface with caching and rate limits", "Extract readable content from web pages for research or monitoring workflows", "Use the same package as an MCP server, CLI or Python library" ], "health": "active" }, { "id": "bankglass", "name": "BankGlass", "description": "Self-hosted read-only banking API and MCP server for accounts connected through an Akahu Personal App. It runs on Cloudflare Workers, exposes four read-only MCP tools, and protects access with Cloudflare Access plus separate bearer-token controls for REST routes. Public GitHub repository created August 26, 2026.", "category": "data", "endpoint": "https://your-worker-domain/mcp", "homepage_url": "https://github.com/mynameistito/BankGlass", "github_url": "https://github.com/mynameistito/BankGlass", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "git clone https://github.com/mynameistito/BankGlass.git && cd BankGlass && bun install", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "banking", "akahu", "personal-finance", "cloudflare-workers", "read-only", "oauth", "rest-api", "bun" ], "use_cases": [ "Expose personal banking account and transaction data to an assistant through read-only MCP tools", "Self-host a finance data gateway on Cloudflare Workers with identity-aware access controls", "Build personal-finance automations around Akahu data without giving agents write permissions" ], "health": "active" }, { "id": "melaya-mcp", "name": "Melaya MCP Server", "description": "Remote MCP server for operating an Android phone through the accessibility tree. It reads the screen, taps, types and navigates inside allow-listed apps, uses OAuth 2.1 with PKCE, and exposes a hosted HTTP endpoint for Claude, ChatGPT, Cursor, Codex and other MCP clients. Public GitHub repository created August 28, 2026.", "category": "productivity", "endpoint": "https://api.melaya.org/mcp", "homepage_url": "https://melaya.org", "github_url": "https://github.com/melaya-labs/melaya-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http melaya https://api.melaya.org/mcp", "added": "2026-08-29", "updated": "2026-08-29", "tags": [ "android", "device-control", "accessibility", "remote-mcp", "oauth", "pkce", "phone-automation", "http" ], "use_cases": [ "Let an assistant operate an Android phone by reading the screen and using accessibility actions", "Automate app workflows without a per-app vendor API by using the same UI a person uses", "Connect remote device-control tools to MCP clients through an OAuth-protected hosted endpoint" ], "health": "active" }, { "id": "google-calender-mcp-server", "name": "Google Calender MCP Server", "description": "Production-ready Google Calendar MCP server with OAuth 2.0 refresh-token authentication and seven tools for listing calendars, listing/searching/creating/updating/deleting events, and free/busy queries. Public GitHub repository created August 30, 2026.", "category": "productivity", "endpoint": "node /absolute/path/to/google-calender-mcp-server/dist/index.js", "homepage_url": "https://github.com/H5SH/google-calender-mcp-server", "github_url": "https://github.com/H5SH/google-calender-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/H5SH/google-calender-mcp-server.git && cd google-calender-mcp-server && npm install && npm run build", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "google-calendar", "calendar", "oauth", "events", "free-busy", "typescript", "stdio", "productivity" ], "use_cases": [ "Let an assistant list calendars, search upcoming events, and query free/busy windows through Google Calendar", "Create or update calendar events from an MCP client using the local user's OAuth credentials", "Run a local single-user Calendar MCP server for Claude Desktop, Cursor, VS Code, or other stdio clients" ], "health": "active" }, { "id": "ask-oracle-mcp", "name": "Ask Oracle MCP", "description": "Oracle Database MCP server for schema introspection and SQL execution over stdio. It exposes compact table discovery, single-table description, and SQL execution tools, with writes disabled unless both server and tool-call flags opt in. Public GitHub repository created August 30, 2026.", "category": "data", "endpoint": "npx -y ask-oracle-mcp", "homepage_url": "https://www.npmjs.com/package/ask-oracle-mcp", "github_url": "https://github.com/doberkofler/ask-oracle-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pnpm install && pnpm run build && pnpm start", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "oracle", "database", "sql", "schema-introspection", "read-only", "node", "stdio", "enterprise-data" ], "use_cases": [ "Let an assistant inspect Oracle schemas without dumping the whole database into context", "Run bounded SQL queries against Oracle through a local stdio MCP server", "Keep database writes explicitly gated behind both server configuration and tool-call approval" ], "health": "active" }, { "id": "fushiguro-mcp", "name": "Fushiguro MCP", "description": "MCP server that routes tasks to specialist agents and assembles briefs from layered catalogs of agents, skills, runbooks, connectors, preferences, and cited local knowledge. It runs without its own model key and returns subagent-ready system prompts. Public GitHub repository created August 30, 2026.", "category": "ai", "endpoint": "npx -y fushiguro-mcp", "homepage_url": "https://github.com/omgcarlo/fushiguro-mcp", "github_url": "https://github.com/omgcarlo/fushiguro-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/omgcarlo/fushiguro-mcp.git && cd fushiguro-mcp && npm install && npm run build", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "agent-routing", "subagents", "skills", "runbooks", "rag", "catalog", "preferences", "node-sqlite" ], "use_cases": [ "Route business tasks to the right specialist agent with a reusable catalog of roles and procedures", "Assemble subagent prompts from cited internal knowledge, runbooks, connectors, and house preferences", "Layer a company-specific agent catalog over a packaged baseline without forking the server" ], "health": "active" }, { "id": "ewm-ops-mcp", "name": "EWM Ops MCP", "description": "Warehouse operations MCP server with typed tools, shadow mode, segregation-of-duties policy, and human approval controls. It exposes warehouse task, delivery, stock, and KPI workflows while denying unsafe writes by code rather than prompt. Public GitHub repository created August 30, 2026.", "category": "infrastructure", "endpoint": "npm run mcp", "homepage_url": "https://github.com/popuripk/ewm-ops-mcp", "github_url": "https://github.com/popuripk/ewm-ops-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/popuripk/ewm-ops-mcp.git && cd ewm-ops-mcp && npm install && npm run mcp", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "warehouse", "sap-ewm", "shadow-mode", "human-approval", "segregation-of-duties", "inventory", "deliveries", "operations" ], "use_cases": [ "Let an assistant list overdue warehouse tasks and at-risk deliveries from an MCP client", "Preview warehouse write operations in shadow mode before connecting real enterprise handlers", "Demonstrate policy-enforced denial paths for goods issue and other segregation-of-duties-sensitive actions" ], "health": "active" }, { "id": "regdocs-mcp", "name": "RegDocs MCP", "description": "Regulatory-document MCP server scaffold for MAS notices and SGX rulebooks over stdio and Streamable HTTP. It defines tools for searching notices, retrieving document sections, listing obligations, and diffing versions. Public GitHub repository created August 30, 2026.", "category": "data", "endpoint": "https://your-host/mcp", "homepage_url": "https://github.com/msubash26/regdocs-mcp", "github_url": "https://github.com/msubash26/regdocs-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "git clone https://github.com/msubash26/regdocs-mcp.git", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "regulatory", "mas", "sgx", "notices", "rulebooks", "obligations", "streamable-http", "compliance" ], "use_cases": [ "Search regulatory notices and rulebooks from an MCP-compatible compliance assistant", "Retrieve stable sections of MAS or SGX documents for cited regulatory analysis", "Compare rulebook or notice versions to surface changed clauses and obligations" ], "health": "unknown" }, { "id": "openwrt-luci-mcp", "name": "OpenWrt LuCI MCP", "description": "Read-only MCP server for OpenWrt LuCI HTTP /ubus/ access. It exposes router status, interfaces, DHCP leases, Wi-Fi, services, routes, firewall summaries, logs, packages, diagnostics, and security-audit tools without SSH or arbitrary shell execution. Public GitHub repository created August 30, 2026.", "category": "infrastructure", "endpoint": "node /absolute/path/to/openwrt-luci-mcp/src/index.mjs", "homepage_url": "https://github.com/JeffersonYoung/openwrt-luci-mcp", "github_url": "https://github.com/JeffersonYoung/openwrt-luci-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/JeffersonYoung/openwrt-luci-mcp.git && cd openwrt-luci-mcp && npm install && npm start", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "openwrt", "luci", "router", "ubus", "network-diagnostics", "read-only", "wifi", "security-audit" ], "use_cases": [ "Let an assistant inspect OpenWrt router state over LuCI HTTP without enabling SSH access", "Summarize interfaces, DHCP leases, routes, firewall state, Wi-Fi clients, logs, and installed packages", "Run passive network diagnostics and router security checks through a read-only MCP surface" ], "health": "active" }, { "id": "aipod", "name": "aipod", "description": "Single-binary reference MCP server and pydantic-ai agent. In server mode it exercises broad MCP features including tools, structured output, resources, prompts, content blocks, sampling, subscriptions, service contracts, and optional OAuth 2.1 protected-resource auth. Public GitHub repository created August 30, 2026.", "category": "ai", "endpoint": "aipod server", "homepage_url": "https://github.com/bigg01/aipod", "github_url": "https://github.com/bigg01/aipod", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "git clone https://github.com/bigg01/aipod.git && cd aipod && aipod server", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "reference-server", "pydantic-ai", "fastmcp", "structured-output", "resources", "prompts", "oauth", "test-fixture" ], "use_cases": [ "Test MCP clients, gateways, and runtimes against a broad reference feature surface", "Exercise structured output, resources, prompts, content blocks, and sampling in one local server", "Publish a service contract for MCP compatibility testing and agent integration work" ], "health": "active" }, { "id": "twofold-mcp", "name": "Twofold MCP", "description": "MCP server that gives agents a local wallet and fourteen tools for the Twofold dual-yield liquidity protocol on Robinhood Chain. It supports pool discovery, quotes, swaps, deposits, withdrawals, staking, rewards, wallet info, and token sends over stdio. Public GitHub repository created August 30, 2026.", "category": "payments", "endpoint": "npx -y twofold-mcp", "homepage_url": "https://twofold.fi", "github_url": "https://github.com/twofoldfi/twofold-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y twofold-mcp", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "wallet", "defi", "liquidity", "staking", "swaps", "robinhood-chain", "tokenized-equities", "onchain" ], "use_cases": [ "Give an agent a bounded wallet for Twofold pool, swap, staking, and rewards workflows", "Quote and execute token swaps with slippage controls through an MCP-compatible client", "Inspect Twofold pool reserves, staking APY, TVL, wallet balances, and positions from an assistant" ], "health": "active" }, { "id": "nodeloc-mcp", "name": "NodeLoc MCP", "description": "TypeScript MCP server for the NodeLoc community with 42 stdio tools covering forum browsing, topics, replies, private messages, likes, bookmarks, polls, nodes, chat, energy rewards, payment APIs, knowledge-base lookup, and miniprogram CLI operations. Public GitHub repository created August 30, 2026.", "category": "communication", "endpoint": "node /absolute/path/to/nodeloc-mcp/dist/index.js", "homepage_url": "https://github.com/Patrick130306/nodeloc-mcp", "github_url": "https://github.com/Patrick130306/nodeloc-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/Patrick130306/nodeloc-mcp.git && cd nodeloc-mcp && npm install && npm run build", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "nodeloc", "forum", "community", "private-messages", "chat", "payments", "knowledge-base", "typescript" ], "use_cases": [ "Let an assistant browse NodeLoc topics, read posts, and search community knowledge", "Operate NodeLoc private messages, chat, polls, likes, bookmarks, and node membership through MCP tools", "Use NodeLoc energy, rewards, payment, documentation, and miniprogram workflows from a local stdio server" ], "health": "active" }, { "id": "smailr-mcp", "name": "Smailr MCP", "description": "Local-first MCP server for Smailr mail with 23 tools across mailboxes, messages, attachments, contacts, folders, labels, rules, signatures, quotas, and stats. It supports reading, searching, managing, and sending mail through the Smailr API while keeping the API key local. Public GitHub repository created August 30, 2026.", "category": "communication", "endpoint": "npx -y smailr-mcp", "homepage_url": "https://smailr.com", "github_url": "https://github.com/Patrick130306/smailr-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y smailr-mcp", "added": "2026-08-30", "updated": "2026-08-30", "tags": [ "smailr", "email", "mailboxes", "contacts", "attachments", "folders", "labels", "local-first" ], "use_cases": [ "Let an assistant list, read, search, and update Smailr email from a local MCP server", "Manage Smailr mailboxes, folders, labels, contacts, quotas, and stats through typed tools", "Send or prepare email workflows through the Smailr API while keeping the API key in local environment variables" ], "health": "active" }, { "id": "govconapi-mcp", "name": "GovCon API MCP", "description": "MCP server for GovCon API with 53 tools over US federal procurement data, including SAM.gov opportunities, FPDS awards, SAM entities, FFATA subawards, exclusions, protests, and full-text search across solicitation attachments. Public GitHub repository created August 31, 2026.", "category": "data", "endpoint": "govconapi-mcp", "homepage_url": "https://govconapi.com/mcp", "github_url": "https://github.com/govconapi/govconapi-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pipx install govconapi-mcp", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "govcon", "federal-contracts", "sam-gov", "fpds", "procurement", "rfp", "public-data", "python" ], "use_cases": [ "Search active US federal solicitations and attached RFP documents from an MCP client", "Analyze incumbents, awards, exclusions, and contractor profiles across joined federal procurement datasets", "Give capture and business-development assistants structured access to GovCon API data with source provenance" ], "health": "active" }, { "id": "planvortex-mcp", "name": "PlanVortex MCP", "description": "Official PlanVortex MCP server for social publishing, comment inbox, private messages, analytics, media uploads, organization context, and account capabilities across Facebook, Instagram, LinkedIn, TikTok, X, WhatsApp, YouTube, Google Business, Bluesky, Discord, and Telegram. Public GitHub repository created August 31, 2026.", "category": "communication", "endpoint": "npx -y planvortex-mcp", "homepage_url": "https://planvortex.com", "github_url": "https://github.com/taliasoftworks/PlanVortexMCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y planvortex-mcp", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "social-media", "publishing", "comments", "messages", "analytics", "multi-network", "read-only-mode", "typescript" ], "use_cases": [ "Let an assistant review scheduled social posts, unread comments, and message inboxes across multiple networks", "Create or retry PlanVortex publications while preserving MCP client-side human confirmation controls", "Run a read-only social inbox triage server by setting PLANVORTEX_MCP_READ_ONLY" ], "health": "active" }, { "id": "motif", "name": "Motif", "description": "Self-hosted MCP-backed team memory layer for Claude Code, Codex, and Cursor sessions. It collects agent sessions on a local or team server, recalls prior decisions through MCP, and supports cross-tool handoffs without sending data to a hosted cloud service. Public GitHub repository created August 29, 2026.", "category": "ai", "endpoint": "motif mcp install", "homepage_url": "https://www.getmotif.dev/", "github_url": "https://github.com/motif-Labs/motif", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm i -g getmotif && motif up && motif mcp install", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "agent-memory", "team-context", "claude-code", "codex", "cursor", "self-hosted", "sqlite", "typescript" ], "use_cases": [ "Surface prior team agent sessions and decisions automatically inside MCP-compatible coding agents", "Collect Claude Code, Codex, and Cursor work into one self-hosted session memory server", "Hand off or query sessions across different coding-agent tools with cited source sessions" ], "health": "active" }, { "id": "mcphound", "name": "mcphound", "description": "Independent security scanner and reputation layer for MCP servers and agent skills. The v0.1 release discovers configured MCP servers across agent clients, performs static supply-chain checks, emits SARIF, supports policy enforcement, and never executes scanned servers during static analysis. Public GitHub repository created August 28, 2026.", "category": "infrastructure", "endpoint": "uvx mcphound scan", "homepage_url": "https://github.com/markdoyle4312-hash/mcphound", "github_url": "https://github.com/markdoyle4312-hash/mcphound", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx mcphound scan", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "security", "mcp-security", "supply-chain", "sarif", "policy", "scanner", "reputation", "python" ], "use_cases": [ "Scan local MCP configurations for hardcoded secrets, risky launch commands, and over-broad filesystem access", "Enforce mcp-policy.yaml in CI and emit SARIF for pull-request security review", "Build a reputation database from scanned MCP registry entries and per-server risk history" ], "health": "active" }, { "id": "legalize-mcp", "name": "Legalize MCP", "description": "Remote Streamable HTTP MCP connector for Legalize, providing authenticated read access to consolidated legislation with historical versions, citations, URLs, source metadata, and git commit SHAs. It also includes account-scoped webhook subscription tools for law-change notifications. Public GitHub repository created August 26, 2026.", "category": "data", "endpoint": "https://legalize.dev/mcp", "homepage_url": "https://legalize.dev/mcp", "github_url": "https://github.com/legalize-dev/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http legalize https://legalize.dev/mcp", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "legal", "legislation", "legal-research", "citations", "git-provenance", "streamable-http", "oauth", "read-only-corpus" ], "use_cases": [ "Ask legal-research assistants what a law said on a named historical date with citation and git SHA provenance", "Search consolidated legislation through a remote MCP endpoint rather than relying on model memory", "Subscribe an account-owned webhook endpoint to law-change notifications when supported by the plan" ], "health": "active" }, { "id": "minusone-mcp", "name": "minusOne MCP", "description": "Reverse-engineering MCP server exposing semantic operations for static triage, unpacking, decompilation, dynamic instrumentation, emulation, symbolic execution, time-travel debugging, and evidence handling. Static backends run in pinned Docker containers, with dynamic analysis armed explicitly by the owner. Public GitHub repository created August 28, 2026.", "category": "code", "endpoint": "node dist/mcp/server.js", "homepage_url": "https://github.com/Ashibalt/minusOne-mcp", "github_url": "https://github.com/Ashibalt/minusOne-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/Ashibalt/minusOne-mcp.git && cd minusOne-mcp && npm install && npm run setup && npm run build", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "reverse-engineering", "binary-analysis", "ghidra", "ida", "frida", "angr", "unicorn", "malware-analysis" ], "use_cases": [ "Give an MCP-compatible analyst agent bounded tools for binary triage, decompilation, emulation, and evidence capture", "Run static reverse-engineering backends in isolated Docker containers without network access", "Expose advanced dynamic-analysis workflows only after the owner explicitly arms them" ], "health": "active" }, { "id": "saydo", "name": "SayDo", "description": "Conformance harness for MCP servers that checks whether tools do what publishers claim. It runs declared behaviors in sandboxed or local modes, records evidence, produces signed hash-chained receipts, and includes an optional MCP server for reporting what it found. Public GitHub repository created August 29, 2026.", "category": "infrastructure", "endpoint": "saydo-mcp", "homepage_url": "https://github.com/vince-gonzalez/saydo", "github_url": "https://github.com/vince-gonzalez/saydo", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install saydo[mcp]", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "conformance", "mcp-security", "sandbox", "signed-receipts", "supply-chain", "github-actions", "python", "testing" ], "use_cases": [ "Verify MCP server tool declarations against observed behavior in a controlled harness", "Generate signed receipts that summarize what a server did during a conformance run", "Continuously detect drift between a publisher declaration and current MCP server behavior" ], "health": "active" }, { "id": "insitu", "name": "Insitu", "description": "Portable MCP server for situated identity and reusable agent guidance. A vault stores stanzas, roles, projects, skills, and capability packs, then materializes project-specific protocol and adapter files for agent hosts such as Claude, Cursor, and Grok. Public GitHub repository created August 27, 2026.", "category": "ai", "endpoint": "uv run insitu", "homepage_url": "https://github.com/srmackey/insitu", "github_url": "https://github.com/srmackey/insitu", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/srmackey/insitu.git && cd insitu && uv run insitu", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "agent-instructions", "agent-skills", "agent-identity", "project-context", "claude", "cursor", "grok", "python" ], "use_cases": [ "Compose project-specific agent instructions from reusable stanzas, roles, and capability packs", "Materialize host adapter files and skills for Claude, Cursor, and Grok from one portable vault", "Keep reusable agent guidance from drifting across multiple repositories and tools" ], "health": "active" }, { "id": "db-fahrplan-mcp", "name": "DB Fahrplan MCP", "description": "MCP server for live Deutsche Bahn timetables, journeys, fares, departure and arrival boards, delays, platform changes, trip details, train formation, disruptions, and nearby station search. It talks directly to bahn.de JSON endpoints and requires no API key. Public GitHub repository created August 30, 2026.", "category": "data", "endpoint": "uvx db-fahrplan-mcp", "homepage_url": "https://github.com/capraCoder/db-fahrplan-mcp", "github_url": "https://github.com/capraCoder/db-fahrplan-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx db-fahrplan-mcp", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "deutsche-bahn", "railway", "timetable", "journeys", "fares", "delays", "platforms", "python" ], "use_cases": [ "Ask travel assistants for live Deutsche Bahn journeys, departure boards, platform changes, and disruptions", "Compare fare options and cheapest travel times using the same JSON endpoints behind bahn.de", "Run local or Streamable HTTP MCP access to DB timetable data without registering for an API key" ], "health": "active" }, { "id": "i18n-keeper", "name": "i18n-keeper", "description": "Deterministic i18n linter exposed as both CLI and MCP server for JSON, Laravel PHP, gettext, and YAML locale files. It checks missing keys, placeholder drift, structure mismatches, stale translations, ICU syntax, plural rules, glossary violations, and translation-memory state without requiring an LLM or network. Public GitHub repository created August 31, 2026.", "category": "code", "endpoint": "node /absolute/path/to/i18n-keeper/dist/mcp.js", "homepage_url": "https://github.com/katerynaKhar/i18n-keeper", "github_url": "https://github.com/katerynaKhar/i18n-keeper", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/katerynaKhar/i18n-keeper.git && cd i18n-keeper && npm install && npm run build", "added": "2026-08-31", "updated": "2026-08-31", "tags": [ "i18n", "localization", "linting", "translation-memory", "placeholders", "icu", "laravel", "typescript" ], "use_cases": [ "Let coding agents audit locale files for missing keys, stale translations, placeholder drift, and ICU errors", "Make translation state reviewable in git through a committed translation memory file", "Run deterministic localization checks through MCP without relying on a model reading every language" ], "health": "active" }, { "id": "lemmalog", "name": "Lemmalog", "description": "Datalog-based memory and reasoning engine for LLM agents, with a Rust engine, REPL, skill package, and MCP server exposing 12 stdio JSON-RPC tools. It models agent memory as provenance-tracked facts and stratified rules for temporal queries, contradiction candidates, relevance diffusion, and incremental derived views. Public GitHub repository created August 27, 2026.", "category": "ai", "endpoint": "lemmalog-mcp", "homepage_url": "https://github.com/JordyZomer/lemmalog", "github_url": "https://github.com/JordyZomer/lemmalog", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/JordyZomer/lemmalog.git && cd lemmalog && cargo build --release --features mcp", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "agent-memory", "datalog", "provenance", "deductive-database", "temporal-reasoning", "rust", "claude-code", "kimi" ], "use_cases": [ "Give MCP-compatible agents a shared deductive memory instead of relying only on vector retrieval", "Query current and historical facts with provenance back to source episodes", "Install versioned rule batches and update derived memory views incrementally across sessions" ], "health": "active" }, { "id": "knx-ets-mcp", "name": "KNX ETS MCP", "description": "MCP server plus ETS 5/6 AddIn that lets assistants inspect, create, edit, and maintain KNX ETS building-automation projects through ETS own engine. The AddIn exposes a fixed local named-pipe or optional TCP surface, while the MCP server provides client-facing stdio or Streamable HTTP. Public GitHub repository created August 29, 2026.", "category": "productivity", "endpoint": "knx-ets-mcp.exe", "homepage_url": "https://github.com/knx-ai/knx-ets-mcp", "github_url": "https://github.com/knx-ai/knx-ets-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "Download the release, extract it, run install.bat for the ETS AddIn, then register knx-ets-mcp.exe with an MCP client", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "knx", "ets", "building-automation", "smart-building", "addin", "windows", "csharp", "streamable-http" ], "use_cases": [ "Let an assistant inspect devices, group addresses, links, parameters, and catalogs in an open ETS project", "Generate or tidy KNX building-automation projects from structured project data", "Program or maintain ETS projects through a bounded AddIn rather than direct file manipulation" ], "health": "active" }, { "id": "wq-brain-mcp-server", "name": "WQ BRAIN MCP Server", "description": "Local dependency-light MCP server for WorldQuant BRAIN research, exposing 8 stdio JSON-RPC tools for account status, settings, dataset, field and operator discovery, recent alphas, candidate writing, and guarded multi-simulation runs. Submission is deliberately excluded from the MCP layer and moved behind a separate gated CLI. Public GitHub repository created August 30, 2026.", "category": "data", "endpoint": "python tools/wq_mcp_server.py", "homepage_url": "https://github.com/drephantom/wq-brain-mcp-server", "github_url": "https://github.com/drephantom/wq-brain-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/drephantom/wq-brain-mcp-server.git && cd wq-brain-mcp-server && pip install -r requirements.txt && cp .env.local.example .env.local", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "worldquant", "brain", "quant-research", "alpha", "simulation", "safety-gates", "python", "stdio" ], "use_cases": [ "Let a research agent discover BRAIN datasets, fields, operators, and platform settings", "Write and preflight alpha candidates while keeping real submissions outside the MCP server", "Run quota-aware multi-simulation research loops with explicit safety boundaries" ], "health": "active" }, { "id": "scrapy-mcp-official", "name": "Scrapy MCP Server", "description": "Official Scrapy MCP server that connects MCP-capable agents to live Scrapy crawls for inspection, debugging, and steering. It talks over stdio to the agent and over HTTP with bearer auth to Scrapy RemoteControl job files, letting agents inspect crawl progress, settings, errors, active downloads, and candidate selectors. Public GitHub repository created August 27, 2026.", "category": "web", "endpoint": "uvx --from /absolute/path/to/scrapy-mcp-official scrapy-mcp", "homepage_url": "https://github.com/scrapy/scrapy-mcp-official", "github_url": "https://github.com/scrapy/scrapy-mcp-official", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/scrapy/scrapy-mcp-official && claude mcp add --scope user scrapy-mcp -- uvx --from /absolute/path/to/scrapy-mcp-official scrapy-mcp", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "scrapy", "web-scraping", "crawler", "debugging", "remote-control", "python", "selectors", "stdio" ], "use_cases": [ "Ask an agent whether a running Scrapy crawl is making progress or stuck and why", "Inspect live crawl settings, middlewares, pipelines, request errors, and active downloads", "Try candidate selectors against in-memory responses before patching a spider" ], "health": "active" }, { "id": "octowatch-mcp", "name": "OctoWatch DLP MCP", "description": "Read-only local MCP server for OctoWatch DLP Cloud, exposing risk, anomaly, user, activity, productivity, report, employee-monitoring, search, and API-coverage tools to Cursor, Claude, VS Code, and other MCP clients. Tool failures return MCP is_error and tools advertise read-only hints. Public GitHub repository created August 27, 2026.", "category": "data", "endpoint": "octowatch-mcp", "homepage_url": "https://octowatchdlp.com/", "github_url": "https://github.com/extralabs/octowatch-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "pip install octowatch-mcp", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "dlp", "employee-monitoring", "risk", "anomalies", "activity", "read-only", "python", "security" ], "use_cases": [ "Let a security or operations assistant review OctoWatch DLP Cloud risks, anomalies, users, and activity", "Search monitoring data and reports through a read-only local MCP process", "Audit API coverage and console data without giving the model write tools" ], "health": "active" }, { "id": "goanyapi-mcp", "name": "GoAnyAPI MCP", "description": "Official remote HTTP MCP server for GoAnyAPI, connecting agents to web data, Google Search, SEO, backlinks, Google Ads Transparency, traffic, domain intelligence, and related APIs. It uses OAuth 2.1 with PKCE so users authorize in the browser instead of copying API keys into local configs. Public GitHub repository created August 26, 2026.", "category": "web", "endpoint": "https://mcp.goanyapi.com/mcp", "homepage_url": "https://goanyapi.com/", "github_url": "https://github.com/GoAnyAPI/goanyapi-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http goanyapi https://mcp.goanyapi.com/mcp", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "goanyapi", "google-search", "seo", "backlinks", "domain-intelligence", "google-ads", "oauth", "remote-mcp" ], "use_cases": [ "Give research agents account-authorized access to search, SEO, backlinks, and domain intelligence APIs", "Use browser-based OAuth and GoAnyAPI account credits instead of local API-key copying", "Connect Codex, Claude Code, Cursor, WorkBuddy, and OpenCode to a hosted Streamable HTTP MCP endpoint" ], "health": "active" }, { "id": "parsebounce-mcp-server", "name": "ParseBounce MCP Server", "description": "MCP server for email deliverability data across AWS SES, SendGrid, Mailgun, SparkPost, Postmark, and Mandrill, covering bounces, complaints, suppression lists, delivery stats, campaigns, and provider comparisons. It supports npx stdio configuration and a remote MCP endpoint with OAuth. Public GitHub repository created August 29, 2026.", "category": "communication", "endpoint": "npx -y @parsebounce/mcp-server", "homepage_url": "https://parsebounce.com/", "github_url": "https://github.com/ParseBounce/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @parsebounce/mcp-server", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "email-deliverability", "bounces", "complaints", "suppression-lists", "ses", "sendgrid", "mailgun", "typescript" ], "use_cases": [ "Ask an assistant why a campaign bounced or whether an address appears on a suppression list", "Compare delivery, bounce, complaint, and provider performance across email platforms", "Expose deliverability diagnostics through local stdio MCP or a remote OAuth MCP endpoint" ], "health": "active" }, { "id": "defectdojo-mcp-server", "name": "DefectDojo Intelligence MCP Server", "description": "Permission-preserving MCP server for DefectDojo OSS REST API v2 with parity to DefectDojo Pro read tools plus deterministic analytics and reporting. It uses the caller own API token, keeps tokens out of logs and model output, and gates write and database-history tool groups off by default. Public GitHub repository created August 25, 2026.", "category": "infrastructure", "endpoint": "python -m defectdojo_mcp.server", "homepage_url": "https://github.com/ZeeshanSultan/DefectDojo-MCP-Server", "github_url": "https://github.com/ZeeshanSultan/DefectDojo-MCP-Server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/ZeeshanSultan/DefectDojo-MCP-Server.git && cd DefectDojo-MCP-Server && pip install -e .", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "defectdojo", "appsec", "vulnerability-management", "analytics", "reporting", "permission-preserving", "python", "security" ], "use_cases": [ "Let an AppSec assistant query DefectDojo findings, products, engagements, and tests under the caller own permissions", "Generate deterministic vulnerability analytics and reporting without asking the model to invent calculations", "Deploy an external MCP adapter for DefectDojo OSS environments that do not have built-in Pro MCP" ], "health": "active" }, { "id": "mcpify", "name": "mcpify", "description": "CLI-first OpenAPI-to-MCP server generator that turns any OpenAPI 3.x REST API into MCP tools with stdio, HTTP, and SSE transports. It includes lazy context budgeting, secret masking, read-only controls, per-token RBAC, OAuth2 support, audit trails, health probes, hot reload, mocking, diffing, and zero runtime dependencies. Public GitHub repository created August 28, 2026.", "category": "code", "endpoint": "mcpify serve openapi.json", "homepage_url": "https://github.com/furkan708/mcpify", "github_url": "https://github.com/furkan708/mcpify", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx --from mcpify-openapi mcpify serve openapi.json", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "openapi", "rest-api", "codegen", "mcp-generator", "oauth2", "rbac", "audit-trail", "python" ], "use_cases": [ "Turn an internal OpenAPI specification into agent-callable MCP tools in under a minute", "Expose API operations with read-only controls, secret redaction, audit logs, and per-token authorization", "Diff API spec versions from the MCP tool view and fail CI on breaking changes" ], "health": "active" }, { "id": "ax-platform-mcp", "name": "aX Platform MCP Server", "description": "Remote Streamable HTTP MCP server for aX, an agent-native collaboration network for long-running agents, shared context, tasks, search, messaging, and MCP App widgets. Agents connect on named routes and authenticate through browser-based GitHub OAuth or the documented device-code presence flow. Public GitHub repository created August 25, 2026.", "category": "ai", "endpoint": "https://paxai.app/mcp/agents/{agent_name}", "homepage_url": "https://paxai.app/", "github_url": "https://github.com/pokemon225/ax-platform-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http ax-platform https://paxai.app/mcp/agents/{agent_name}", "added": "2026-09-01", "updated": "2026-09-01", "tags": [ "agent-collaboration", "long-running-agents", "tasks", "messaging", "shared-context", "mcp-apps", "oauth", "remote-mcp" ], "use_cases": [ "Connect named autonomous agents to a shared collaboration network through remote MCP routes", "Coordinate tasks, messages, search, shared context, and presence across long-running agents", "Use hosted aX presence workers for agents that should listen and respond without an open desktop MCP client" ], "health": "active" }, { "id": "tcl-mcp", "name": "TCL MCP", "description": "Open-source MCP server for TCL and Grand Lyon public-transit data, covering real-time next departures, GTFS scheduled timetables, line metadata, active line alerts, and SIRI Lite disruptions. It is read-only, keeps route preferences out of the code, and supports Streamable HTTP deployment behind HTTPS. Public GitHub repository created September 2, 2026.", "category": "data", "endpoint": "npm start", "homepage_url": "https://github.com/jducerf/tcl-mcp", "github_url": "https://github.com/jducerf/tcl-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/jducerf/tcl-mcp.git && cd tcl-mcp && npm install && npm start", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "transit", "grand-lyon", "tcl", "gtfs", "siri-lite", "real-time", "alerts", "typescript" ], "use_cases": [ "Ask travel agents for real-time TCL departures by line, stop, direction, and result limit", "Check scheduled GTFS timetables and route metadata when real-time feeds are incomplete", "Surface active line alerts and disruptions while preserving source-failure caveats" ], "health": "active" }, { "id": "asyntai-mcp-bridge", "name": "Asyntai MCP Bridge", "description": "Local stdio bridge for the hosted Asyntai MCP server, connecting stdio-only MCP clients to Asyntai account tools for website support agents, knowledge management, visitor conversations, leads, and manual live replies. It handles OAuth 2.1 with PKCE and proxies JSON-RPC to the hosted endpoint. Public GitHub repository created September 2, 2026.", "category": "communication", "endpoint": "npx -y @asyntai/mcp", "homepage_url": "https://asyntai.com/documentation/mcp/", "github_url": "https://github.com/asyntai/mcp-bridge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y @asyntai/mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "asyntai", "customer-support", "website-chat", "leads", "oauth", "proxy", "remote-mcp", "javascript" ], "use_cases": [ "Connect Claude Desktop, Cursor, VS Code, or other stdio-only hosts to an Asyntai account", "Let assistants read support conversations, visitor leads, and website knowledge from Asyntai", "Use browser-based OAuth instead of copying API keys into local MCP configuration" ], "health": "active" }, { "id": "imessage-mcp", "name": "iMessage MCP", "description": "Local macOS MCP server for Apple Messages and Contacts, with read-only SQLite access to chat history, local FTS5 indexing, thread and chat inspection, contact-handle resolution, and guarded AppleScript sending that requires an explicit confirmation flag and audit log. Public GitHub repository created September 2, 2026.", "category": "communication", "endpoint": "python server.py", "homepage_url": "https://github.com/ryan-grey/imessage-mcp", "github_url": "https://github.com/ryan-grey/imessage-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/ryan-grey/imessage-mcp.git && cd imessage-mcp && python3 server.py", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "imessage", "apple-messages", "contacts", "macos", "local-first", "fts5", "applescript", "python" ], "use_cases": [ "Search Apple Messages history locally without sending chat content to a hosted MCP service", "List recent chats, read message threads, and resolve names to phone or email handles", "Send iMessages through Messages.app only after explicit confirmation and audit logging" ], "health": "active" }, { "id": "freebazi-mcp", "name": "FreeBazi MCP", "description": "Local MCP server for computing full Chinese Bazi Four Pillars charts from birth date, time, and place. It uses the same offline engine behind freebazi.com, correcting for True Solar Time and historical daylight saving while returning pillars, Ten Gods, hidden stems, Five Elements, luck pillars, and chart links. Public GitHub repository created September 2, 2026.", "category": "ai", "endpoint": "npx -y freebazi-mcp", "homepage_url": "https://freebazi.com", "github_url": "https://github.com/alexsu1212/freebazi-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y freebazi-mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "bazi", "four-pillars", "chinese-astrology", "true-solar-time", "ten-gods", "five-elements", "typescript", "local-first" ], "use_cases": [ "Compute a full Bazi chart from a birth moment and city inside an MCP-compatible client", "Return True Solar Time corrected pillars, Ten Gods, hidden stems, Na Yin, and luck pillars", "Use local chart calculation without an API key or network calls" ], "health": "active" }, { "id": "toolquest-mcp", "name": "ToolQuest MCP", "description": "Deterministic escape-room benchmark server for tool-using agents, exposed through local stdio MCP. It provides puzzle rooms with strict machine-readable tool results, isolated runs, state versions, idempotency keys, replay verification, JSONL traces, Markdown reports, and no LLM judge or external service requirement. Public GitHub repository created September 2, 2026.", "category": "ai", "endpoint": "npx -y toolquest-mcp", "homepage_url": "https://github.com/sysu19351015/toolquest", "github_url": "https://github.com/sysu19351015/toolquest", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y toolquest-mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "agent-evaluation", "benchmark", "tool-use", "escape-room", "deterministic", "traces", "replay", "typescript" ], "use_cases": [ "Evaluate how tool-using agents explore deterministic puzzle rooms through MCP tools", "Record reproducible JSONL traces and export Markdown reports for benchmark runs", "Test retry safety, state-version handling, and long-horizon tool planning without an LLM judge" ], "health": "active" }, { "id": "gemm-basalt-mcp", "name": "Gemm / Basalt MCP", "description": "Local Apple Silicon LLM inference server with MCP stdio, REST, and WebSocket transports sharing one Swift actor over MLX on Metal. It runs Gemma, Qwen, and other MLX-compatible models fully on-device for IDE integration and local agent workflows, with no cloud calls or authentication. Public GitHub repository created September 2, 2026.", "category": "ai", "endpoint": "gemm mcp", "homepage_url": "https://github.com/goodmai/basalt", "github_url": "https://github.com/goodmai/basalt", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/goodmai/basalt.git && cd basalt && swift build", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "local-llm", "apple-silicon", "mlx", "metal", "gemma", "qwen", "swift", "on-device" ], "use_cases": [ "Run local on-device LLM inference from MCP-compatible IDEs on Apple Silicon", "Share one model actor between MCP stdio, REST, and WebSocket clients", "Prototype private agent workflows without sending prompts or model calls to a hosted service" ], "health": "active" }, { "id": "rack-mcp", "name": "Rack MCP", "description": "Safety-first local MCP integration for VCV Rack 2.6.6 that discovers running Rack instances, inspects patches, explains and validates signal flow, previews and atomically applies structured patch changes, manages checkpoints, and reads Probe telemetry through an authenticated loopback bridge. Public GitHub repository created September 2, 2026.", "category": "media", "endpoint": "node packages/server/dist/index.js", "homepage_url": "https://github.com/ColonelKernel/vcv-rack-mcp", "github_url": "https://github.com/ColonelKernel/vcv-rack-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/ColonelKernel/vcv-rack-mcp.git && cd vcv-rack-mcp && pnpm install && pnpm run build", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "vcv-rack", "modular-synthesis", "audio", "music-production", "patches", "telemetry", "loopback", "typescript" ], "use_cases": [ "Let music agents inspect and validate VCV Rack patches through an authenticated local bridge", "Preview, confirm, rollback, and checkpoint structured patch changes before touching a live rack", "Read Probe telemetry and explain modular signal flow from MCP-compatible hosts" ], "health": "active" }, { "id": "saferico-cli-mcp", "name": "Saferico CLI MCP", "description": "Local MCP server and CLI for Solidity security scanning, with 201 detectors executed on the developer machine rather than uploading contracts. It supports path and source scans, SARIF output, engine version pinning, skill and MCP config review, and optional hosted MCP tools for lightweight on-chain reads. Public GitHub repository created September 1, 2026.", "category": "code", "endpoint": "npx -y saferico mcp", "homepage_url": "https://saferico.com", "github_url": "https://github.com/Saferico/saferico-cli", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y saferico mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "solidity", "smart-contracts", "security", "static-analysis", "sarif", "mcp-security", "local-first", "javascript" ], "use_cases": [ "Scan Solidity contracts locally from an AI coding agent without uploading source code", "Generate SARIF for GitHub code scanning and CI security gates", "Review agent skills and MCP configuration files for risky instructions or permissions" ], "health": "active" }, { "id": "todo-mcp-shared", "name": "todo-mcp", "description": "Shared local todo and backlog MCP server for Claude Code, Claude Desktop, Cursor, Windsurf, Warp, Codex, and other clients. It centralizes tasks in encrypted local storage, adds claim tracking and full history, serves a real-time SSE web dashboard, and supports CLI backup, import, export, and optional multi-device sync. Public GitHub repository created September 1, 2026.", "category": "productivity", "endpoint": "npx -y @pasichdev/todo-mcp", "homepage_url": "https://www.npmjs.com/package/@pasichdev/todo-mcp", "github_url": "https://github.com/pasichDev/todo-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @pasichdev/todo-mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "todo", "task-manager", "backlog", "claim-tracking", "encrypted-storage", "web-ui", "sse", "typescript" ], "use_cases": [ "Share one encrypted local task list across multiple MCP-compatible agent clients", "Claim tasks before starting work so parallel agent sessions avoid duplicated effort", "Inspect, backup, import, and export tasks through the terminal or live web dashboard" ], "health": "active" }, { "id": "keihyo-cases-mcp", "name": "Keihyo Cases MCP", "description": "Machine-readable dataset and local MCP server for Japanese advertising-law enforcement actions published by the Consumer Affairs Agency. It packages 151 source-linked orders and surcharge-payment orders from 2021 through 2026, exposing search, get-case, recent-list, and stats tools without network calls. Public GitHub repository created September 2, 2026.", "category": "data", "endpoint": "npx -y github:eoylab/keihyo-cases keihyo-mcp", "homepage_url": "https://eoylab.github.io/keihyo-cases/", "github_url": "https://github.com/eoylab/keihyo-cases", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y github:eoylab/keihyo-cases keihyo-mcp", "added": "2026-09-02", "updated": "2026-09-02", "tags": [ "legal", "advertising-law", "japan", "compliance", "consumer-affairs", "open-data", "citations", "javascript" ], "use_cases": [ "Search Japanese advertising-law enforcement cases by company, product, provision, date, or order type", "Give compliance assistants real source-linked cases instead of relying on model recall", "Run local legal-data lookups from bundled JSON without external network calls" ], "health": "active" }, { "id": "linkedin-mcp-chrome", "name": "LinkedIn MCP Chrome", "description": "Defensive Python wrapper around the upstream mcp-server-linkedin package, pinning fastmcp below 4.0 after the August 31 FastMCP API break while preserving the same LinkedIn profile, company, search, jobs, messaging, connection, and feed tools. It runs over local stdio, opens a separate bundled Chromium login session, and stores that session under the local LinkedIn MCP profile. Public GitHub repository created September 3, 2026.", "category": "communication", "endpoint": "uvx linkedin-mcp-chrome", "homepage_url": "https://pypi.org/project/linkedin-mcp-chrome/", "github_url": "https://github.com/kugamon/linkedin-mcp-chrome", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "uvx linkedin-mcp-chrome", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "linkedin", "profiles", "jobs", "companies", "messaging", "chromium", "fastmcp", "python" ], "use_cases": [ "Query LinkedIn people, company, job, feed, and conversation data from MCP-compatible desktop clients", "Use a pinned dependency wrapper when the upstream LinkedIn server is broken by FastMCP 4 API changes", "Authenticate once in the server-managed Chromium profile and reuse the saved local session" ], "health": "active" }, { "id": "seohead-seotools", "name": "SEOHEAD Tools", "description": "Local SEO evidence and audit-automation toolkit with CLI, Docker, and stdio MCP surfaces. It analyzes Screaming Frog exports against a 96-check registry, exposes 42 shared SEO tools plus five Screaming Frog workflow tools, preserves skipped or unavailable evidence explicitly, and can generate structured audits, task backlogs, and report artifacts. Public GitHub repository created August 29, 2026.", "category": "web", "endpoint": "seohead mcp", "homepage_url": "https://seohead.tech/seotools", "github_url": "https://github.com/PavloSEO/seohead-seotools", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/PavloSEO/seohead-seotools.git && cd seohead-seotools && python3 -m venv .venv && source .venv/bin/activate && python3 -m pip install -e .", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "seo", "technical-seo", "screaming-frog", "audit", "schema-org", "reports", "local-first", "python" ], "use_cases": [ "Turn Screaming Frog crawl exports into machine-readable findings, summaries, and prioritized SEO task backlogs", "Run bounded live URL, infrastructure, structured-data, robots, sitemap, and content checks through agent tools", "Generate evidence-grounded Markdown, JSON, CSV, XLSX, or DOCX SEO review artifacts while preserving uncertainty" ], "health": "active" }, { "id": "monapay-mcp", "name": "MONA Pay MCP", "description": "Vietnam-focused MONA Pay MCP server for creating VietQR checkouts, looking up transactions, configuring and testing webhooks, verifying HMAC signatures, and returning integration snippets and machine-readable documentation from Claude Code, Cursor, Codex, or any stdio MCP client. Supports client-id/client-secret credentials and legacy username/password auth. Public GitHub repository created August 28, 2026.", "category": "payments", "endpoint": "npx -y monapay-mcp", "homepage_url": "https://monapay.vn/ai-agent", "github_url": "https://github.com/themonagroup/monapay-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y monapay-mcp", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "monapay", "payments", "vietqr", "webhooks", "hmac", "vietnam", "checkout", "javascript" ], "use_cases": [ "Let coding agents integrate MONA Pay checkout and bank-transfer confirmation without leaving the IDE", "Create and test webhooks, verify HMAC signatures, and inspect payment logs through MCP tools", "Generate language-specific webhook receiver snippets and read MONA Pay docs as MCP resources" ], "health": "active" }, { "id": "ratchet-mcp", "name": "Ratchet MCP", "description": "Effect-gate control plane for AI agents that need durable approval and at-most-once semantics before irreversible actions such as charging a card, sending an email, or shipping a deploy. It exposes REST and MCP, stores decisions in Postgres, uses leases and idempotency keys, and never performs vendor effects itself. Public GitHub repository created August 31, 2026.", "category": "infrastructure", "endpoint": "npx -y ratchet-mcp", "homepage_url": "https://ratchetgate.com", "github_url": "https://github.com/thearchitect0x-glitch/ratchet", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/thearchitect0x-glitch/ratchet.git && cd ratchet && npm install && npm run dev:db && npm run migrate && npm run dev", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "agent-safety", "effect-gate", "idempotency", "approval", "leases", "postgres", "rest", "typescript" ], "use_cases": [ "Require durable approval before agents perform irreversible external effects", "Deduplicate retries with stable idempotency keys so an action is attempted at most once", "Record indeterminate, duplicate, approved, and completed effect states for operational audit trails" ], "health": "active" }, { "id": "multi-agent-hub", "name": "Multi-Agent Hub", "description": "MCP-based dispatch hub for parallel coding agents, using a stdio Python server to coordinate worker CLIs such as Claude Code, Antigravity, Codex, and Ollama with isolated git worktrees and optional Docker sandbox tests. The repository also ships a companion multi-agent-dispatch skill and Claude plugin path. Public GitHub repository created September 2, 2026.", "category": "code", "endpoint": "python3 mcp_worker_hub.py", "homepage_url": "https://github.com/zkylek1212-k/multi-agent-hub", "github_url": "https://github.com/zkylek1212-k/multi-agent-hub", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/zkylek1212-k/multi-agent-hub.git && cd multi-agent-hub && python3 -m pip install mcp", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "multi-agent", "claude-code", "codex", "ollama", "git-worktree", "sandbox", "plugin", "python" ], "use_cases": [ "Split coding work across multiple CLI worker agents while keeping file edits isolated in git worktrees", "Coordinate worker availability and task lifecycle through seven MCP tools exposed to a master agent", "Run sandboxed validation before merging parallel worker outputs back into the main repository" ], "health": "active" }, { "id": "reddit-mcp-chrome", "name": "Reddit MCP Chrome", "description": "Local Python MCP server for Reddit search, subreddit browsing, and post details that wraps reddit-no-auth-mcp-server while using Chrome session cookies and curl_cffi Chrome TLS impersonation to avoid Reddit anti-scraping blocks. It requires no Reddit API key or OAuth application and runs as a stdio MCP process. Public GitHub repository created September 3, 2026.", "category": "communication", "endpoint": "uvx reddit-mcp-chrome", "homepage_url": "https://pypi.org/project/reddit-mcp-chrome/", "github_url": "https://github.com/kugamon/reddit-mcp-chrome", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx reddit-mcp-chrome", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "reddit", "subreddits", "search", "chrome-cookies", "tls-impersonation", "local-first", "python", "social" ], "use_cases": [ "Search Reddit and browse subreddit posts from Claude Desktop or other MCP clients without a Reddit API key", "Reuse existing Chrome reddit.com cookies and browser-like TLS fingerprints for more reliable reads", "Inspect post details and community discussion threads through a local stdio MCP tool surface" ], "health": "active" }, { "id": "engram-alpha-mcp", "name": "Engram Alpha MCP", "description": "Sovereign local-first cognitive memory and knowledge-graph MCP server for AI coding agents. It combines on-device embeddings, vector search, bi-temporal graph memory, trigram full-text search, SQLite WAL storage, cognitive decay scoring, Obsidian sync, and zero-cloud operation behind a uvx-installable stdio server. Public GitHub repository created August 31, 2026.", "category": "ai", "endpoint": "uvx engram-alpha-mcp", "homepage_url": "https://lalithbuilds.github.io/engram-alpha-mcp/", "github_url": "https://github.com/lalithbuilds/engram-alpha-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx engram-alpha-mcp", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "memory", "knowledge-graph", "vector-search", "sqlite", "obsidian", "local-first", "apple-silicon", "python" ], "use_cases": [ "Give local coding agents durable on-device memory with hybrid vector, graph, and full-text retrieval", "Replace flat MCP memory JSON with indexed SQLite-backed memory that stays private on the machine", "Sync agent memory workflows with Obsidian while avoiding cloud vector databases or SaaS memory stores" ], "health": "active" }, { "id": "chatgpt-mcp-bridge", "name": "ChatGPT MCP Bridge", "description": "Unofficial local MCP bridge that safely exposes one Git workspace to ChatGPT or other MCP clients. The default mode is read-only for code review and architecture analysis, with explicit optional modes for single-file patching or preconfigured commands, sensitive-file blocking, ignore rules, token requirements for HTTP, and no privilege escalation through MCP calls. Public GitHub repository created September 2, 2026.", "category": "code", "endpoint": "chatgpt-mcp-bridge serve --workspace /path/to/project --transport stdio", "homepage_url": "https://github.com/yiran-ye/chatgpt-mcp-bridge#readme", "github_url": "https://github.com/yiran-ye/chatgpt-mcp-bridge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm install --global chatgpt-mcp-bridge", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "chatgpt", "git", "code-review", "workspace", "read-only", "security", "typescript", "bridge" ], "use_cases": [ "Expose a local Git repository to ChatGPT or MCP Inspector for read-only review and architecture analysis", "Optionally allow constrained single-file patches or configured commands without giving MCP calls broader privileges", "Block sensitive files, ignored paths, public writable binds, and unsafe workspace access by default" ], "health": "active" }, { "id": "mnemos-mcp", "name": "mnemos MCP", "description": "C++23 Redis-compatible in-memory key-value server that also ships a native MCP introspection binary. The mnemos-mcp stdio server connects to a running mnemos or Redis instance over TCP and exposes tools for commands, key reads and writes, key scanning, key description, and server info, with a read-only mode that refuses mutating or administrative commands. Public GitHub repository created August 31, 2026.", "category": "data", "endpoint": "./build/mnemos-mcp --port 6380 --read-only", "homepage_url": "https://github.com/aryaman-boop/mnemos", "github_url": "https://github.com/aryaman-boop/mnemos", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/aryaman-boop/mnemos.git && cd mnemos && cmake -S . -B build -DCMAKE_BUILD_TYPE=RelWithDebInfo && cmake --build build", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "redis", "key-value", "cache", "resp", "introspection", "read-only", "cplusplus", "local-first" ], "use_cases": [ "Let agents inspect local Redis-compatible keyspaces, encodings, and server state through MCP tools", "Use a zero-dependency cache in tests or CI while retaining Redis protocol compatibility", "Run read-only MCP diagnostics against a cache without allowing writes or administrative commands" ], "health": "active" }, { "id": "gemini-mcp-tool", "name": "Gemini MCP Tool", "description": "Stdio MCP server that lets Claude Code, Cursor, Windsurf, and other agents offload large-context analysis, planning, structured output, model inspection, diagnostics, brainstorming, and image generation to Google Gemini and Imagen through the Antigravity CLI or legacy Gemini CLI backend. Public GitHub repository created September 3, 2026.", "category": "ai", "endpoint": "npx -y gemini-mcp-tool", "homepage_url": "https://V-Songbird.github.io/gemini-mcp-tool/", "github_url": "https://github.com/V-Songbird/gemini-mcp-tool", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "npx -y gemini-mcp-tool", "added": "2026-09-03", "updated": "2026-09-03", "tags": [ "gemini", "imagen", "antigravity", "large-context", "code-review", "planning", "image-generation", "javascript" ], "use_cases": [ "Send large files or project contexts to Gemini without consuming the primary agent context window", "Generate non-destructive architecture plans, structured JSON, and creative brainstorming outputs via MCP", "Create images and diagnose local Gemini or Antigravity CLI readiness from an agent runtime" ], "health": "active" }, { "id": "reverify", "name": "Reverify", "description": "Anti-hallucination reverse-engineering toolkit for agents that read binaries. It pairs an LLM with deterministic PE, ELF, Mach-O, disassembly, emulation, pattern scanning, and claim-ledger tools so binary-analysis claims are marked VERIFIED, REFUTED, or INCONCLUSIVE against the actual bytes instead of model guesses. Ships as both a CLI and stdio MCP server. Public GitHub repository created August 31, 2026.", "category": "code", "endpoint": "python reverify/mcp_server.py", "homepage_url": "https://pypi.org/project/reverify/", "github_url": "https://github.com/2akouwu/reverify", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install reverify", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "reverse-engineering", "binary-analysis", "anti-hallucination", "verification", "disassembly", "emulation", "malware-analysis", "python" ], "use_cases": [ "Ground AI reverse-engineering claims against real binary bytes before reporting them as facts", "Parse, disassemble, scan, emulate, and inspect PE, ELF, and Mach-O files from MCP-compatible coding agents", "Persist verified binary-analysis facts in a compact ledger that survives context resets" ], "health": "active" }, { "id": "shim-mcp", "name": "Shim MCP", "description": "Self-contained WordPress MCP server plugin that exposes WordPress through local WP-CLI stdio or remote Streamable HTTP. It maps WordPress Abilities API capabilities into 56 content, media, user, plugin, menu, widget, comment, options, and system abilities, with no cloud relay or companion plugin. Public GitHub repository created August 30, 2026.", "category": "web", "endpoint": "wp shim-mcp serve --user=admin", "homepage_url": "https://github.com/justadityaraj/shim-mcp#readme", "github_url": "https://github.com/justadityaraj/shim-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/justadityaraj/shim-mcp.git wp-content/plugins/shim-mcp", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "wordpress", "wp-cli", "abilities-api", "cms", "content", "media", "php", "streamable-http" ], "use_cases": [ "Connect local WordPress development sites to Claude Code, Cursor, or other MCP clients through WP-CLI stdio", "Expose WordPress content, media, users, plugins, menus, widgets, comments, options, and system abilities to agents", "Use remote Streamable HTTP with application-password authentication for WordPress sites not running locally" ], "health": "active" }, { "id": "proxmox-datacenter-manager-mcp", "name": "Proxmox Datacenter Manager MCP", "description": "Read-only Streamable HTTP MCP server for Proxmox Datacenter Manager. It runs as a Docker service, talks to PDM with a dedicated Auditor token, exposes tools for remotes, resources, guests, containers, nodes, tasks, storage, and summaries, and redacts sensitive values from returned guest data and errors. Public GitHub repository created August 31, 2026.", "category": "infrastructure", "endpoint": "http://localhost:3000/mcp", "homepage_url": "https://github.com/j3r3g1l3s/proxmox-datacenter-manager-mcp-server#readme", "github_url": "https://github.com/j3r3g1l3s/proxmox-datacenter-manager-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "docker pull jer3m/pdm-mcp-server:latest", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "proxmox", "datacenter", "virtualization", "readonly", "docker", "streamable-http", "auditor", "typescript" ], "use_cases": [ "Inspect PDM remotes, resources, VMs, containers, nodes, tasks, and storage from an MCP client", "Ask aggregate capacity or power-state questions using compact summary tools instead of large resource dumps", "Use a dedicated read-only Auditor token so agents can observe infrastructure state without mutating it" ], "health": "active" }, { "id": "ynab-mcp-server", "name": "YNAB MCP Server", "description": "Single-tenant open-source MCP server for the full YNAB v1 API. It provides local stdio mode for desktop and coding clients plus OAuth-gated HTTP mode for hosted connector environments, covering 23 tools across all 30 YNAB endpoint paths with an optional read-only mode that hides mutation tools entirely. Public GitHub repository created August 30, 2026.", "category": "productivity", "endpoint": "npx ynab-mcp-server", "homepage_url": "https://github.com/lukendatigh/ynab-mcp-server#readme", "github_url": "https://github.com/lukendatigh/ynab-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx ynab-mcp-server", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "ynab", "budgeting", "personal-finance", "accounts", "transactions", "oauth", "read-only", "typescript" ], "use_cases": [ "Read YNAB budgets, accounts, categories, payees, payee locations, and transactions from MCP clients", "Allow controlled budget, category, payee, account, transaction, and scheduled-transaction mutations when trusted", "Deploy a private single-tenant HTTP connector while keeping the YNAB access token as a server-side secret" ], "health": "active" }, { "id": "pymol-claude-mcp", "name": "PyMOL Claude MCP", "description": "Small Python stdio MCP bridge between Claude Code and a live PyMOL session over PyMOLs XML-RPC server. It exposes tools to run PyMOL commands, execute Python scripts inside PyMOL, and query XML-RPC methods for structure fetches, selections, representations, coloring, measurements, and atom or chain lookups. Public GitHub repository created September 2, 2026.", "category": "media", "endpoint": "python pymol_server.py", "homepage_url": "https://github.com/stavasol96-arch/Pymol-Claude-MCP#readme", "github_url": "https://github.com/stavasol96-arch/Pymol-Claude-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/stavasol96-arch/Pymol-Claude-MCP.git && cd Pymol-Claude-MCP && python3 -m venv venv && source venv/bin/activate && pip install -r requirements.txt", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "pymol", "molecular-visualization", "proteins", "xml-rpc", "chemistry", "biology", "python", "claude-code" ], "use_cases": [ "Drive an already-running PyMOL session from Claude Code or another MCP-compatible client", "Fetch molecular structures, create selections, adjust representations, color scenes, and measure distances", "Run PyMOL commands or scripts from an agent while keeping PyMOL local on the users machine" ], "health": "active" }, { "id": "better-web-search-mcp", "name": "BetterWebSearch MCP", "description": "Keyless-first TypeScript MCP server for web research, using DuckDuckGo by default and optional Brave or Tavily backends. It combines web search with a three-tier extraction ladder from fast HTTP fetch to hydration and Playwright, plus cache and SSRF protections, so agents get cleaner research payloads without mandatory API keys. Public GitHub repository created August 29, 2026.", "category": "web", "endpoint": "npx -y better-web-search-mcp", "homepage_url": "https://phantompixeldev.github.io/BetterWebSearch-MCP/", "github_url": "https://github.com/PhantomPixelDev/BetterWebSearch-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y better-web-search-mcp", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "web-search", "duckduckgo", "brave", "tavily", "playwright", "extraction", "ssrf-guard", "typescript" ], "use_cases": [ "Give MCP clients working web search immediately without configuring a paid search API key", "Extract pages through fast HTTP, hydrated fetches, or Playwright when simple search snippets are not enough", "Use optional Brave or Tavily credentials for stronger search backends while retaining keyless DuckDuckGo fallback" ], "health": "active" }, { "id": "2captcha-mcp", "name": "2Captcha MCP", "description": "Official 2Captcha MCP server for agents that need web search, web scraping, browser automation, marketplace parsing, structured extraction, batch jobs, and CAPTCHA solving against sites that block ordinary HTTP clients. It offers a hosted Streamable HTTP endpoint plus a local npx stdio server, both authenticated with a 2Captcha API token. Public GitHub repository created August 28, 2026.", "category": "web", "endpoint": "https://mcp.2captcha.com/mcp", "homepage_url": "https://2captcha.com/", "github_url": "https://github.com/2captcha/2captcha-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "API_TOKEN=YOUR_API_TOKEN npx @2captcha/mcp", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "2captcha", "captcha", "web-scraping", "browser-automation", "web-search", "marketplaces", "anti-bot", "javascript" ], "use_cases": [ "Scrape pages or parse marketplace listings through anti-bot tiers when basic HTTP clients fail", "Solve CAPTCHAs and operate managed browser workflows from MCP-compatible agents", "Run batch scraping or parsing jobs through hosted HTTP or a local npx stdio server" ], "health": "active" }, { "id": "papergraph-mcp", "name": "PaperGraph MCP", "description": "Evidence-first MCP server for turning local or arXiv LaTeX papers into theorem dependency graphs. It keeps single-paper graphs and persistent cross-paper SQLite workspaces, validates raw arXiv requests before loading, searches theorem text, follows dependencies, and returns citation evidence without making agents reread every source. Public GitHub repository created September 2, 2026.", "category": "ai", "endpoint": "uvx --from git+https://github.com/lotchuazzz-crypto/papergraph-mcp.git@v0.4.4 papergraph-mcp", "homepage_url": "https://github.com/lotchuazzz-crypto/papergraph-mcp#readme", "github_url": "https://github.com/lotchuazzz-crypto/papergraph-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx --from git+https://github.com/lotchuazzz-crypto/papergraph-mcp.git@v0.4.4 papergraph-mcp --version", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "arxiv", "latex", "mathematics", "theorems", "knowledge-graph", "sqlite", "research", "python" ], "use_cases": [ "Load local LaTeX projects or arXiv sources and expose theorem environments as MCP-queryable graphs", "Maintain a small cross-paper SQLite workspace for theorem search, dependencies, and citation evidence", "Validate ambiguous arXiv IDs, URLs, and prose requests before an agent imports a paper" ], "health": "active" }, { "id": "onebusaway-mcp", "name": "OneBusAway MCP", "description": "Go MCP server for real-time public-transit data backed by the OneBusAway API and GTFS or GTFS-realtime feeds. It ships as a single binary with 29 transit tools over stdio or HTTP, plus an optional SvelteKit web chat UI, so agents can answer live route, stop, arrival, and service-status questions from an OBA-compatible backend. Public GitHub repository created August 31, 2026.", "category": "data", "endpoint": "/absolute/path/to/mcp/oba-mcp", "homepage_url": "https://onebusaway.org", "github_url": "https://github.com/OneBusAway/mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/OneBusAway/mcp-server.git && cd mcp-server/mcp && make build", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "transit", "gtfs", "gtfs-realtime", "onebusaway", "routes", "stops", "arrivals", "go" ], "use_cases": [ "Ask live public-transit questions such as next arrivals, route stops, and service timing from an MCP client", "Use a OneBusAway or Maglev backend as the data layer behind agent-facing transit tools", "Run the server as local stdio for desktop agents or HTTP behind a private gateway for applications" ], "health": "active" }, { "id": "elbi", "name": "Elbi", "description": "Python semantic-layer tool server that lets developers write ordinary derivation functions and serve them to agents over MCP as versioned, cached, verified tools. The CLI can open a local chat UI and MCP endpoint or run an MCP-only HTTP server, making reproducible table and analytics functions available without requiring an API key for basic setup. Public GitHub repository created September 3, 2026.", "category": "data", "endpoint": "http://localhost:7878/mcp", "homepage_url": "https://intelligible.github.io/elbi/", "github_url": "https://github.com/Intelligible/elbi", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "uv tool install elbi", "added": "2026-09-04", "updated": "2026-09-04", "tags": [ "semantic-layer", "analytics", "derivations", "duckdb", "data-science", "reproducibility", "python", "http" ], "use_cases": [ "Expose trusted Python derivation functions as versioned MCP tools for agents", "Serve table and analytics outputs from local datasets through a reproducible semantic layer", "Run a local chat UI or MCP-only HTTP endpoint for inspecting and calling derived tools" ], "health": "active" }, { "id": "codecraft", "name": "CodeCraft", "description": "Read-only validation and data-lookup MCP server for Minecraft Bedrock add-on development. It exposes nine tools that check feasibility, version data, schemas, identifiers, JSON files, commands, scripts, Python automation envelopes, and whole packs against version-pinned Bedrock data and real TypeScript diagnostics so generated content is more likely to load in-game. Public GitHub repository created August 29, 2026.", "category": "code", "endpoint": "npx codecraft-mcp", "homepage_url": "https://codecraft-ashy-seven.vercel.app/", "github_url": "https://github.com/TanerTalas/codecraft", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/TanerTalas/codecraft.git && cd codecraft && npm install", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "minecraft", "bedrock", "validation", "schemas", "typescript", "commands", "read-only", "game-dev" ], "use_cases": [ "Validate Minecraft Bedrock behavior-pack JSON, identifiers, commands, and scripts before loading them in-game", "Check whether requested Bedrock mechanics are feasible and which version-pinned fields or modules are valid", "Review a generated pack with evidence-backed diagnostics instead of relying on LLM memory of Bedrock APIs" ], "health": "active" }, { "id": "frostagent", "name": "frostagent", "description": "Deny-by-default capability linter for AI agent tool setups. It reads MCP servers, hooks, permission rules, skills, and local server source across Claude Code, Claude Desktop, Cursor, VS Code, Codex, Zed, Windsurf, Gemini CLI, OpenCode, and Cline, then probes stdio, HTTP, or SSE tools and fails policies for unapproved capabilities, plaintext secrets, unpinned packages, dangerous permissions, or changed tool schemas. Public GitHub repository created September 5, 2026.", "category": "infrastructure", "endpoint": "frostagent probe --user", "homepage_url": "https://github.com/keithadler/frostagent#readme", "github_url": "https://github.com/keithadler/frostagent", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/keithadler/frostagent.git", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "security", "capability-policy", "mcp-audit", "tool-schemas", "permissions", "secrets", "lockfile", "agent-safety" ], "use_cases": [ "Audit local AI-agent configurations for unapproved MCP capabilities, hooks, skills, and permission rules", "Detect plaintext secrets, unpinned packages, remote HTTP servers, risky containers, and destructive commands in agent tool configs", "Pin tool descriptions and schemas so MCP tool drift fails a build before agents trust changed capabilities" ], "health": "active" }, { "id": "excel-normalizer", "name": "Excel Semantic Normalizer", "description": "Python service and MCP server for normalizing messy procurement or supply-chain spreadsheets. It maps arbitrary Excel headers and column orders into 19 canonical fields using rule matching, hybrid retrieval, optional LLM adjudication, template export, and a human-feedback loop, with an offline fallback when API keys are unavailable. Public GitHub repository created September 5, 2026.", "category": "data", "endpoint": "python mcp_server.py", "homepage_url": "https://github.com/climik/excel-normalizer#readme", "github_url": "https://github.com/climik/excel-normalizer", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/climik/excel-normalizer.git && cd excel-normalizer && pip install -r requirements.txt", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "excel", "spreadsheets", "semantic-normalization", "procurement", "supply-chain", "templates", "python", "offline" ], "use_cases": [ "Normalize vendor spreadsheets with inconsistent headers into typed canonical JSON records", "Map columns by semantic meaning rather than position, with confidence scores and issue metadata", "Export normalized data back into user-provided Excel templates after MCP-assisted review" ], "health": "active" }, { "id": "tokenectomy", "name": "Tokenectomy", "description": "Rust M2M MCP sidecar for coding agents that compresses noisy error logs before they reach the context window. It strips framework stack frames from node_modules, site-packages, Cargo registries, and caches; redacts likely credentials; can search Stack Exchange for relevant fixes; and keeps the agent focused on user code and actionable diagnostics. Public GitHub repository created September 1, 2026.", "category": "code", "endpoint": "tokenectomy mcp", "homepage_url": "https://github.com/daffa2555/Tokenectomy#readme", "github_url": "https://github.com/daffa2555/Tokenectomy", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "cargo install tokenectomy", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "rust", "error-logs", "context-compression", "secret-redaction", "stack-traces", "coding-agents", "m2m", "debugging" ], "use_cases": [ "Reduce large framework-heavy error dumps before passing them to an LLM coding agent", "Redact secrets and high-entropy credentials from logs before cloud-model transmission", "Surface only user-code stack frames and relevant diagnostic context during autonomous debugging loops" ], "health": "active" }, { "id": "agentpay-mcp", "name": "AgentPay MCP Server", "description": "x402 micropayments MCP server for paid API access, initially focused on Xiaohongshu note data and China wholesale-pricing queries. The local server handles 402 Payment Required challenges, signs Base USDC payments with a configured agent wallet, retries the gateway request, and enforces per-call spend limits so agents can buy small data payloads autonomously. Public GitHub repository created September 5, 2026.", "category": "payments", "endpoint": "uvx mcp-server-agentpay", "homepage_url": "https://github.com/yyxqqq777/mcp-server-agentpay#readme", "github_url": "https://github.com/yyxqqq777/mcp-server-agentpay", "x402": true, "x402_price": "0.05 USDC/call", "verified": false, "protocols": [ "MCP", "x402" ], "transport": "stdio", "auth": "x402", "install_cmd": "pip install mcp-server-agentpay", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "x402", "micropayments", "base", "usdc", "xiaohongshu", "paid-api", "agent-wallets", "python" ], "use_cases": [ "Let an agent pay a small x402 fee to retrieve Xiaohongshu note details or user note lists", "Expose paid wholesale-pricing queries through an MCP gateway with server-side upstream credentials", "Cap autonomous spend per call while automatically handling 402 challenge, payment signing, and retry" ], "health": "active" }, { "id": "copilot-studio-mcp", "name": "Copilot Studio MCP", "description": "MCP server for Microsoft Copilot Studio agent development from VS Code, Claude Code, or other MCP clients. It supports Power Platform CLI sync, YAML authoring for topics, knowledge, tools, flows, evaluations, and chat testing, giving coding agents a terminal-driven workflow for building and validating Copilot Studio assets. Public GitHub repository created September 5, 2026.", "category": "code", "endpoint": "npx copilot-studio-mcp", "homepage_url": "https://github.com/jgt87/copilot-studio-mcp#readme", "github_url": "https://github.com/jgt87/copilot-studio-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/jgt87/copilot-studio-mcp.git && cd copilot-studio-mcp && npm install", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "microsoft", "copilot-studio", "power-platform", "pac-cli", "yaml", "evaluations", "agent-development", "typescript" ], "use_cases": [ "Scaffold, edit, and sync Microsoft Copilot Studio agent assets from a coding-agent session", "Author topics, knowledge, tools, flows, and evaluations as YAML with MCP-assisted validation", "Run chat tests and development checks without leaving VS Code, Claude Code, or another MCP host" ], "health": "active" }, { "id": "registry-mcp", "name": "registry-mcp", "description": "Company-registry MCP server and REST API over national business registries. The initial implementation supports Norway through Brønnøysundregistrene and the United Kingdom through Companies House, with tools for organization lookup, name search, VAT or MVA status, annual-accounts deadlines, confirmation-statement deadlines, and source-backed company reports. Public GitHub repository created September 4, 2026.", "category": "data", "endpoint": "https://api.foretak.dev/mcp", "homepage_url": "https://github.com/foretak/registry-mcp#readme", "github_url": "https://github.com/foretak/registry-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "uvx registry-mcp", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "company-registry", "business-data", "norway", "companies-house", "vat", "deadlines", "rest-api", "python" ], "use_cases": [ "Look up Norwegian organizations by orgnr or search companies by name from an MCP client", "Query UK Companies House data and statutory filing deadlines with a configured API key", "Return source-attributed company reports with registration, status, VAT, address, and industry metadata" ], "health": "active" }, { "id": "fmsg-mcp", "name": "fmsg MCP", "description": "MCP server that gives AI agents an fmsg address for federated messaging through a deployed fmsg Web API. It can send messages, read inboxes, follow threads, react, exchange attachments, and wait for replies, running either as a local stdio server for one address or a shared Streamable HTTP server where each user authenticates with their own fmsg API key. Public GitHub repository created September 3, 2026.", "category": "communication", "endpoint": "npx -y @markmnl/fmsg-mcp", "homepage_url": "https://github.com/markmnl/fmsg-mcp#readme", "github_url": "https://github.com/markmnl/fmsg-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npx -y @markmnl/fmsg-mcp", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "messaging", "federated", "inbox", "threads", "attachments", "streamable-http", "npm", "agents" ], "use_cases": [ "Give an AI agent a federated messaging address for sending and receiving fmsg messages", "Wait for replies, follow message threads, react to messages, and exchange attachments through MCP tools", "Run locally for one agent identity or host a shared HTTP endpoint with per-user bearer-token auth" ], "health": "active" }, { "id": "cueprecise", "name": "CuePrecise", "description": "Evidence-grounded YouTube transcription MCP server for finding exact moments in long videos. It uses Gemini transcription alongside captions, stores timestamped passages and matching frames locally, and lets agents answer cross-language video questions with citations to the original timeline instead of unsupported summaries. Public GitHub repository created August 30, 2026.", "category": "media", "endpoint": "cueprecise-mcp", "homepage_url": "https://github.com/Nattentia/cueprecise#readme", "github_url": "https://github.com/Nattentia/cueprecise", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "uvx cueprecise", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "youtube", "transcription", "video-search", "timestamps", "gemini", "captions", "frames", "evidence" ], "use_cases": [ "Ask questions about long YouTube videos and receive answers tied to exact timestamps", "Transcribe foreign-language videos and query them later without rerunning the whole extraction", "Retrieve matching frames when the relevant evidence is visual rather than only spoken" ], "health": "active" }, { "id": "safedatabase-mcp", "name": "SafeDataBaseMCP", "description": "Guardrailed database MCP server for SQLite, Postgres, and AWS RDS. Reads run immediately, but writes must go through a propose-change transaction that computes a real preview, rolls back, returns a single-use change id, and only commits if confirm-change is called; RDS access can use short-lived IAM tokens instead of stored passwords. Public GitHub repository created September 5, 2026.", "category": "data", "endpoint": "python -m safedatabase_mcp.server", "homepage_url": "https://github.com/Hamzah-Muhammad/SafeDataBaseMCP#readme", "github_url": "https://github.com/Hamzah-Muhammad/SafeDataBaseMCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/Hamzah-Muhammad/SafeDataBaseMCP.git && cd SafeDataBaseMCP && pip install -e .", "added": "2026-09-05", "updated": "2026-09-05", "tags": [ "database", "sqlite", "postgres", "aws-rds", "write-guardrails", "preview", "iam-auth", "python" ], "use_cases": [ "Let agents inspect database schemas and run SELECT queries while blocking destructive SQL patterns", "Require a preview-and-confirm flow before INSERT, UPDATE, or DELETE statements reach disk", "Use short-lived AWS RDS IAM authentication instead of storing a database password in agent configuration" ], "health": "active" }, { "id": "aster-dex-mcp", "name": "Aster DEX MCP", "description": "Read-only Python MCP server for Aster DEX market and airdrop research. It exposes Aster DEX volume, points, leaderboard rank, wallet eligibility, and farming-progress checks as structured tools for Claude, Cursor, Cline, or other MCP clients, with no trading tools and no private-key access. Public GitHub repository created September 4, 2026.", "category": "payments", "endpoint": "python main.py --demo", "homepage_url": "https://github.com/trinity1994/MCP-Server-Aster-DEX#readme", "github_url": "https://github.com/trinity1994/MCP-Server-Aster-DEX", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/trinity1994/MCP-Server-Aster-DEX.git && cd MCP-Server-Aster-DEX && pip install -r requirements.txt", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "aster", "dex", "defi", "airdrop", "leaderboard", "wallet", "read-only", "python" ], "use_cases": [ "Ask an MCP client to check Aster DEX wallet volume, points, rank, and airdrop eligibility", "Track DeFi farming progress through typed JSON tool results instead of manually refreshing a dashboard", "Give agents read-only market and eligibility context without exposing trading or private-key capabilities" ], "health": "active" }, { "id": "omarchy-mcp-server", "name": "Omarchy MCP Server", "description": "HTTP MCP server packaged as an Omarchy plugin. It exposes the Omarchy command registry and live shell IPC surfaces through four generic command/search tools, fifteen curated tools, and seven readable resources, all supervised by the plugin daemon with policy checks and bearer-token client auth. Public GitHub repository created August 30, 2026.", "category": "infrastructure", "endpoint": "http://127.0.0.1:8765/mcp", "homepage_url": "https://github.com/bruce-forte/omarchy-mcp-server#readme", "github_url": "https://github.com/bruce-forte/omarchy-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "omarchy plugin add https://github.com/bruce-forte/omarchy-mcp-server.git --enable", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "omarchy", "desktop", "commands", "ipc", "policy", "bearer-token", "http", "python" ], "use_cases": [ "Let Claude Code, Codex, or another MCP client inspect and run approved Omarchy commands", "Expose Omarchy command registry and shell IPC references as MCP resources for human-readable review", "Share one supervised local daemon and one policy surface across multiple agent clients" ], "health": "active" }, { "id": "okf-agent-memory", "name": "OKF Agent Memory", "description": "Git-native persistent memory layer for AI coding agents built around Google OKF v0.2 concepts. The zero-dependency Go CLI stores memory as Markdown and YAML in a repository knowledge folder, validates graph structure, searches concepts with in-memory BM25, and runs a stdio MCP server for Claude Code, Cursor, Codex, and similar clients. Public GitHub repository created September 5, 2026.", "category": "ai", "endpoint": "okf mcp knowledge", "homepage_url": "https://github.com/okf-memory/okf-agent-memory#readme", "github_url": "https://github.com/okf-memory/okf-agent-memory", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/okf-memory/okf-agent-memory.git && cd okf-agent-memory && make build", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "memory", "okf", "bm25", "markdown", "knowledge-graph", "git-native", "go", "agent-memory" ], "use_cases": [ "Add local repository-backed memory search and retrieval to coding agents without a vector database", "Validate and maintain OKF knowledge bundles with deterministic CLI checks before agent use", "Reduce memory-token bloat by exposing progressive concept lookup over MCP" ], "health": "active" }, { "id": "pocketbase-mcp", "name": "PocketBase MCP", "description": "Python MCP server that exposes PocketBase through thirteen intent-first tools instead of a large endpoint wrapper. It supports collection inspection, schema-aware record writes, auth lifecycle operations, server inspection, optional destructive tools gated by an environment flag, stdio mode for desktop clients, and HTTP mode for container deployments. Public GitHub repository created September 1, 2026.", "category": "data", "endpoint": "uv run pocketbase-mcp", "homepage_url": "https://github.com/Touexe/pocketbase-mcp#readme", "github_url": "https://github.com/Touexe/pocketbase-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/Touexe/pocketbase-mcp.git && cd pocketbase-mcp && uv sync", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "pocketbase", "database", "collections", "schema", "auth", "docker", "python", "fastmcp" ], "use_cases": [ "Inspect PocketBase collections, fields, API rules, indexes, and server health from an MCP client", "Create or update records with payload validation against cached PocketBase schemas", "Run a single-identity PocketBase MCP process over stdio locally or HTTP in a container" ], "health": "active" }, { "id": "abapsmith", "name": "ABAPSmith", "description": "TypeScript MCP server for SAP ABAP development over ADT endpoints. It lets agents inspect packages and objects, edit and activate ABAP artifacts, run ABAP Unit and ATC checks, inspect dumps, manage transports with gated release behavior, and operate a debugger against a live SAP system through capped, journaled responses. Public GitHub repository created September 2, 2026.", "category": "code", "endpoint": "node dist/index.js", "homepage_url": "https://github.com/Freight-Art/abapsmith#readme", "github_url": "https://github.com/Freight-Art/abapsmith", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/Freight-Art/abapsmith.git && cd abapsmith && npm install && npm run build", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "sap", "abap", "adt", "debugger", "abap-unit", "atc", "transports", "typescript" ], "use_cases": [ "Let coding agents develop ABAP objects against a live ADT-enabled SAP system", "Run ABAP Unit, ATC static analysis, class runs, and report executions from an MCP workflow", "Inspect ST22 dumps, debugger state, variables, transports, and quick fixes without a full IDE loop" ], "health": "active" }, { "id": "ozon-shopping-mcp", "name": "Ozon Shopping MCP", "description": "Unofficial TypeScript MCP server for personal Ozon shopping research. It uses a headless Chrome session rather than Seller API keys to search products, retrieve prices, inspect product cards, compare listings, and read reviews through a local stdio MCP server intended for interactive use rather than bulk scraping. Public GitHub repository created September 4, 2026.", "category": "web", "endpoint": "npx -y ozon-shopping-mcp@latest serve", "homepage_url": "https://github.com/neosheps/ozon-shopping-mcp#readme", "github_url": "https://github.com/neosheps/ozon-shopping-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y ozon-shopping-mcp@latest setup", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "ozon", "shopping", "ecommerce", "product-search", "reviews", "prices", "playwright", "typescript" ], "use_cases": [ "Search Ozon products and compare prices or product cards from an MCP-compatible assistant", "Summarize reviews and listing details without opening many manual browser tabs", "Run local personal shopping research through a stdio server with no Seller API key" ], "health": "active" }, { "id": "cc-readback", "name": "cc-readback", "description": "Local read-only TypeScript MCP server over Claude Code session files in ~/.claude. It lets Claude Desktop or Claude Code answer questions about recent coding sessions, prompts, touched files, decisions, blocked threads, and project history while denying tool-output bodies, thinking blocks, attachments, settings, and secrets, with redaction applied to every emitted string. Public GitHub repository created September 3, 2026.", "category": "code", "endpoint": "node dist/cli.js install all", "homepage_url": "https://github.com/affirmitv/cc-readback#readme", "github_url": "https://github.com/affirmitv/cc-readback", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/affirmitv/cc-readback.git && cd cc-readback && npm install && npm run build", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "claude-code", "session-history", "read-only", "redaction", "local", "transcripts", "typescript", "privacy" ], "use_cases": [ "Ask a desktop MCP client what local Claude Code sessions did recently without copy-pasting transcripts", "Find prompts, summaries, file paths touched, decisions, and blocked sessions while excluding raw tool outputs", "Expose local session history with deny-by-default parsing and secret redaction before any MCP result is returned" ], "health": "active" }, { "id": "jadx-mcp", "name": "jadx-mcp", "description": "Java MCP server implemented as a jadx-gui plugin for Android reverse engineering. It runs inside jadx-gui over Streamable HTTP and lets agents list and search classes, fetch decompiled Java or smali, inspect methods, manifest components, resources, strings, cross-references, and apply renames for deobfuscation loops against the app currently loaded in the GUI. Public GitHub repository created August 30, 2026.", "category": "code", "endpoint": "http://localhost:8090/mcp", "homepage_url": "https://github.com/0xdad0/jadx-mcp#readme", "github_url": "https://github.com/0xdad0/jadx-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "none", "install_cmd": "git clone https://github.com/0xdad0/jadx-mcp.git && cd jadx-mcp && gradle jar", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "jadx", "android", "reverse-engineering", "decompilation", "smali", "java", "streamable-http", "deobfuscation" ], "use_cases": [ "Let an MCP-compatible agent analyze the Android app currently open in jadx-gui", "Search classes, retrieve decompiled source, inspect methods and cross-references, and review manifest resources", "Drive iterative deobfuscation by applying class, method, field, package, and variable renames" ], "health": "active" }, { "id": "linkedin-mcp-deeplearner", "name": "LinkedIn MCP", "description": "Python MCP server for LinkedIn-oriented workflows, built for Google Antigravity and compatible with Claude Code. It registers globally, exposes diagnostic and LinkedIn automation tools, uses a captured local browser session for search, comments, and connection requests, optionally uses a LinkedIn OAuth token for publishing, and stores job-scraping data in SQLite under ~/.config/linkedin-mcp. Public GitHub repository created September 3, 2026.", "category": "communication", "endpoint": "./install.sh --claude", "homepage_url": "https://github.com/DeepLearner7/linkedin-mcp#readme", "github_url": "https://github.com/DeepLearner7/linkedin-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "git clone https://github.com/DeepLearner7/linkedin-mcp.git && cd linkedin-mcp && ./install.sh --claude", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "linkedin", "jobs", "browser-session", "oauth", "sqlite", "recruiting", "automation", "python" ], "use_cases": [ "Expose LinkedIn search, comment, connection-request, and diagnostic workflows to an MCP client after local login", "Run daily job scraping and recruiter-feed staging into a local SQLite database for agent review", "Optionally publish LinkedIn posts through an OAuth access token while keeping credentials in local config" ], "health": "active" }, { "id": "hubitat-mcp-server", "name": "Hubitat MCP Server", "description": "Python stdio MCP server for Hubitat Elevation home-automation hubs using the Maker API. It lists devices, retrieves device details, searches by name, type, or room, reads attributes such as temperature or battery state, lists available commands, and sends device commands for lights, dimmers, switches, and custom Hubitat devices. Public GitHub repository created September 6, 2026.", "category": "infrastructure", "endpoint": "python3 hubitat-mcp-server.py", "homepage_url": "https://github.com/jgitta/hubitat-mcp-server#readme", "github_url": "https://github.com/jgitta/hubitat-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/jgitta/hubitat-mcp-server.git && cd hubitat-mcp-server && pip install mcp requests python-dotenv", "added": "2026-09-06", "updated": "2026-09-06", "tags": [ "hubitat", "smart-home", "maker-api", "devices", "lights", "sensors", "automation", "python" ], "use_cases": [ "List, search, and inspect Hubitat devices from Claude Desktop or another MCP-compatible client", "Read current smart-home attributes such as switch state, temperature, battery, or device capabilities", "Send commands through Hubitat Maker API to turn devices on or off, toggle them, or set dimmer levels" ], "health": "active" }, { "id": "modwrench", "name": "ModWrench", "description": "Composable TypeScript MCP server for PC game modding research and diagnostics. It bridges Nexus Mods, mod.io, Thunderstore, and a local workbench so agents can search mods, read changelogs, inspect versions, review dependencies, examine load orders, and trace crash logs without giving the assistant a broad browser or shell surface. Public GitHub repository created September 7, 2026.", "category": "web", "endpoint": "npx -y @modwrench/cli mcp", "homepage_url": "https://www.npmjs.com/package/@modwrench/cli", "github_url": "https://github.com/171county/modwrench", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "npm install -g @modwrench/cli", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "modding", "nexus-mods", "modio", "thunderstore", "load-order", "crash-analysis", "typescript", "read-only" ], "use_cases": [ "Search mod platforms and compare mod metadata, versions, dependencies, changelogs, and permissions from an MCP client", "Let a gaming assistant inspect local mod-manager state and crash logs without granting a general-purpose browser-control API", "Compose only the Nexus, mod.io, Thunderstore, or workbench capabilities a user actually configured" ], "health": "active" }, { "id": "audacity4-mcp", "name": "Audacity4MCP", "description": "Early-alpha Python MCP server for AI-driven audio editing in Audacity 4. It connects MCP clients to a locally running Audacity 4 companion fork through a TCP JSON-RPC bridge, exposing local audio editing, effects, VST3, cleanup, and project-control commands without cloud processing or audio API keys. Public GitHub repository created September 5, 2026.", "category": "media", "endpoint": "python -m audacity4_mcp", "homepage_url": "https://github.com/xDarkzx/Audacity4-MCP#readme", "github_url": "https://github.com/xDarkzx/Audacity4-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/xDarkzx/Audacity4-MCP.git && cd Audacity4-MCP && pip install -e .", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "audacity", "audio-editing", "vst3", "local-first", "python", "tcp-bridge", "effects", "early-alpha" ], "use_cases": [ "Let an MCP-compatible assistant control local Audacity 4 editing workflows through a companion fork", "Run audio cleanup, effect, and VST3 operations locally without uploading source audio to a cloud service", "Prototype agent-assisted podcast, mastering, and editing workflows against Audacity 4 internals" ], "health": "active" }, { "id": "rechnungslotse-mcp", "name": "Rechnungslotse MCP Server", "description": "Hosted Streamable HTTP MCP server for German e-invoicing. It creates, validates, and reads XRechnung and ZUGFeRD files against EN 16931 and KoSIT rules, explains rejection codes, checks German statutory invoice fields and mandate timing, and exposes seven tools without an account while reserving account tools for OAuth-authenticated users. Public GitHub repository created September 7, 2026.", "category": "productivity", "endpoint": "https://rechnungslotse.de/api/mcp", "homepage_url": "https://rechnungslotse.de/mcp", "github_url": "https://github.com/XKalleX/rechnungslotse-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http rechnungslotse https://rechnungslotse.de/api/mcp", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "e-invoicing", "germany", "xrechnung", "zugferd", "en16931", "kosit", "peppol", "oauth" ], "use_cases": [ "Validate German XRechnung or ZUGFeRD invoices and return source rule IDs with plain-language explanations", "Create structured German e-invoices and check statutory requirements before sending them to customers or public buyers", "Read invoice PDFs or XML into structured sender, recipient, line-item, total, due-date, and bank-detail fields" ], "health": "active" }, { "id": "google-docs-mcp-mmedum", "name": "google-docs-mcp", "description": "Production-oriented Go MCP server for Google Docs with per-user OAuth. It gives agents scoped read, search, create, export, minimal-diff edit, suggestion, comment, table, tab, layout, revision, named-range, and gdocs resource tools while keeping UTF index math and Docs API request shaping on the server. Public GitHub repository created September 2, 2026.", "category": "productivity", "endpoint": "google-docs-mcp serve", "homepage_url": "https://github.com/mmedum/google-docs-mcp#readme", "github_url": "https://github.com/mmedum/google-docs-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "oauth", "install_cmd": "go install github.com/mmedum/google-docs-mcp/cmd/google-docs-mcp@latest", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "google-docs", "google-workspace", "oauth", "go", "suggestions", "comments", "tables", "document-editing" ], "use_cases": [ "Let an agent read, search, and export Google Docs through a single static local binary", "Apply minimal-diff edits as direct changes, comments, or suggestions without exposing raw UTF index handling to the model", "Review suggestions, comments, revision history, tables, tabs, headers, footers, footnotes, and layout through typed tools" ], "health": "active" }, { "id": "printbridge", "name": "printbridge", "description": "Self-hosted Python MCP print server for local or remote assistants. It exposes print_text, print_url, print_file, list_printers, job-status, cancellation, printer-status, and recent-job tools, renders text or web content to PDF, and sends output to a private CUPS queue over LAN, Tailscale, WireGuard, or a tunneled authenticated HTTP MCP endpoint. Public GitHub repository created September 6, 2026.", "category": "productivity", "endpoint": "python -m printbridge", "homepage_url": "https://github.com/starkshtlm/printbridge#readme", "github_url": "https://github.com/starkshtlm/printbridge", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/starkshtlm/printbridge.git && cd printbridge && pip install -r requirements.txt", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "printing", "cups", "tailscale", "self-hosted", "pdf", "weasyprint", "python", "streamable-http" ], "use_cases": [ "Allow Claude, ChatGPT, or another MCP client to print text, URLs, or files to a user-owned printer", "Keep printers private behind CUPS and a private network route while exposing only an authenticated MCP endpoint", "List printers, check queue state, inspect recent jobs, and cancel print jobs from an assistant conversation" ], "health": "active" }, { "id": "mcp-bitbucket", "name": "MCP Bitbucket", "description": "Python MCP server for Bitbucket Cloud with full REST API coverage. It includes pull-request review tools, per-file diffs, trimmed PR listings, inline comments, approvals, zero-config repository targeting from the current git remote, and a generated endpoint index plus generic request tool for all Bitbucket Cloud 2.0 endpoints. Public GitHub repository created September 7, 2026.", "category": "code", "endpoint": "python -m mcp_bitbucket.server", "homepage_url": "https://github.com/mohitgoel188/mcp-bitbucket#readme", "github_url": "https://github.com/mohitgoel188/mcp-bitbucket", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "git clone https://github.com/mohitgoel188/mcp-bitbucket.git && cd mcp-bitbucket && uv sync", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "bitbucket", "pull-requests", "code-review", "rest-api", "python", "atlassian", "inline-comments", "repository-tools" ], "use_cases": [ "Review Bitbucket Cloud pull requests with diffs, inline comments, approvals, and repository-aware tools", "Use a generated Bitbucket endpoint index and generic request tool when typed wrappers do not cover a workflow", "Launch the same MCP registration inside different Bitbucket checkouts and auto-detect workspace and repository slug" ], "health": "active" }, { "id": "win-rdp-mcp", "name": "win-rdp-mcp", "description": "Go MCP server for controlling a Windows desktop over RDP. It drives screenshots, mouse, keyboard, PowerShell, files, processes, services, registry, scheduled tasks, event logs, OCR, and network checks through a headless RDP session plus an optional pushed in-session agent, requiring only RDP access on the target. Public GitHub repository created September 7, 2026.", "category": "infrastructure", "endpoint": "win-rdp-mcp serve", "homepage_url": "https://github.com/stubbedev/win-rdp-mcp#readme", "github_url": "https://github.com/stubbedev/win-rdp-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "nix run github:stubbedev/win-rdp-mcp", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "windows", "rdp", "remote-desktop", "screenshots", "powershell", "registry", "go", "automation" ], "use_cases": [ "Give an MCP client controlled desktop and system access to a Windows host through an existing RDP endpoint", "Take screenshots, click, type, run PowerShell, inspect services, files, registry, tasks, and event logs from one binary", "Operate a Windows target without enabling SMB, WinRM, or any inbound service beyond RDP" ], "health": "active" }, { "id": "bank-mcp-noskillish", "name": "Bank MCP", "description": "Self-hosted read-only TypeScript MCP server for personal banking through Enable Banking and PSD2. It connects Claude or another MCP client to user-owned European bank accounts through OAuth, stores consents and account ids locally, avoids storing balances or transactions, and exposes account, balance, transaction, subscription, and spending questions without payment initiation. Public GitHub repository created September 6, 2026.", "category": "payments", "endpoint": "bank-mcp serve", "homepage_url": "https://noskillish.github.io/bank/", "github_url": "https://github.com/noskillish/bank", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "git clone https://github.com/noskillish/bank.git && cd bank && docker compose up -d", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "open-banking", "psd2", "enable-banking", "personal-finance", "read-only", "oauth", "typescript", "self-hosted" ], "use_cases": [ "Ask an assistant read-only questions about account balances, transactions, subscriptions, and spending categories", "Self-host a private banking connector where bank credentials stay with the bank and PSD2 provider", "Monitor invoices or low-balance conditions without exposing payment-initiation tools to the model" ], "health": "active" }, { "id": "ravn-mcp-glama", "name": "RAVN MCP Glama", "description": "Local stdio TypeScript MCP server for RAVN cross-chain swap execution. It wraps RAVN public APIs for quotes, execution payloads, normalized swap status, venue health, and native-Bitcoin PSBT preparation, complementing the hosted Streamable HTTP MCP endpoint while keeping signing and custody outside the server. Public GitHub repository created September 7, 2026.", "category": "payments", "endpoint": "node dist/index.js", "homepage_url": "https://github.com/ravndex/ravn-mcp-glama#readme", "github_url": "https://github.com/ravndex/ravn-mcp-glama", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/ravndex/ravn-mcp-glama.git && cd ravn-mcp-glama && npm install && npm run build", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "cross-chain", "swaps", "bitcoin", "psbt", "defi", "typescript", "stdio", "non-custodial" ], "use_cases": [ "Get cross-chain swap quotes across RAVN-supported venues and chains from an MCP client", "Generate signable transaction payloads, typed data, deposit addresses, or Bitcoin PSBTs without exposing private keys", "Check normalized swap status and live venue health during agent-assisted DeFi workflows" ], "health": "active" }, { "id": "savage-mcp", "name": "savage_mcp", "description": "Least-privilege JavaScript browser-reading MCP server for Savage Scraper. It opens explicitly allowlisted URLs in a dedicated tab of the user's existing Chrome profile, performs bounded lazy-load scrolling, and returns simplified page HTML through three stdio tools while intentionally omitting click, type, submit, arbitrary JavaScript, and unrestricted browser-control capabilities. Public GitHub repository created September 6, 2026.", "category": "web", "endpoint": "node savage_mcp.js", "homepage_url": "https://github.com/dominikduda/savage_mcp#readme", "github_url": "https://github.com/dominikduda/savage_mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/dominikduda/savage_mcp.git && cd savage_mcp && npm install", "added": "2026-09-07", "updated": "2026-09-07", "tags": [ "browser-reading", "chrome", "scraping", "allowlist", "least-privilege", "javascript", "authenticated-sites", "stdio" ], "use_cases": [ "Let an MCP client read selected authenticated web pages through the user's existing Chrome session", "Expose page HTML from allowlisted sites without granting click, type, submit, or arbitrary JavaScript tools", "Use one dedicated agent tab for Jira, GitHub, docs, dashboards, or internal sites while leaving other tabs untouched" ], "health": "active" }, { "id": "arcmira-mcp", "name": "Arcmira MCP", "description": "Remote Streamable HTTP MCP server from Arcmira for searching the spoken web. It exposes eight read-only tools over indexed YouTube and podcast transcripts, including full transcript retrieval, show-level search, mention lookup, momentum, sponsor, and coverage analysis, with OAuth for hosts that support MCP authorization or bearer/free-trial keys for other clients. Public GitHub repository created September 8, 2026.", "category": "media", "endpoint": "https://mcp.arcmira.com/mcp", "homepage_url": "https://arcmira.com/docs/mcp", "github_url": "https://github.com/arcmira/mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "oauth", "install_cmd": "claude mcp add --transport http arcmira https://mcp.arcmira.com/mcp", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "youtube", "podcasts", "transcripts", "spoken-web", "oauth", "streamable-http", "read-only", "typescript" ], "use_cases": [ "Search YouTube and podcast transcript indexes from Claude, Cursor, ChatGPT, Codex, or another MCP client", "Retrieve full transcripts, show mentions, sponsor references, coverage windows, and momentum signals through read-only tools", "Connect through MCP OAuth when supported, or use an Arcmira account or trial bearer key for clients without host authorization" ], "health": "active" }, { "id": "trace-mcp", "name": "trace-mcp", "description": "Rust MCP server and CLI that lets coding agents drive Intel Processor Trace captures. It records execution into ring buffers, snapshots traces on triggers, decodes them into searchable timelines and hot paths, and exposes ten stdio MCP tools for starting, querying, exporting, and garbage-collecting traces. Public GitHub repository created September 8, 2026.", "category": "code", "endpoint": "trace-mcp --store /path/to/store serve --stdio", "homepage_url": "https://github.com/OctopusTakopi/trace-mcp#readme", "github_url": "https://github.com/OctopusTakopi/trace-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/OctopusTakopi/trace-mcp.git && cd trace-mcp && cargo build --release", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "intel-pt", "tracing", "debugging", "profiling", "rust", "hotpaths", "timeline", "coding-agents" ], "use_cases": [ "Let an agent capture and inspect low-level execution traces while optimizing or debugging native code", "Query decoded Intel PT snapshots for summaries, hot paths, timelines, functions, calls, and exports", "Attach tracing to a process or command with triggers such as elapsed time, symbol hits, or address filters" ], "health": "active" }, { "id": "finance-mcp-server", "name": "Finance MCP Server", "description": "Python stdio MCP server with nineteen finance tools backed by SQLite. It lets Claude Desktop, Cursor, or another MCP client answer questions about P&L, cash flow, balance sheets, liquidity, contracts, KPIs, NPV, IRR, payment calendars, and contract risk from local demo or user-provided financial data without CSV export steps. Public GitHub repository created September 8, 2026.", "category": "payments", "endpoint": "python server.py", "homepage_url": "https://github.com/kaluginvit/finance-mcp-server#readme", "github_url": "https://github.com/kaluginvit/finance-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/kaluginvit/finance-mcp-server.git && cd finance-mcp-server/product-mcp && pip install -r requirements.txt", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "finance", "sqlite", "pnl", "cash-flow", "kpi", "npv", "irr", "python" ], "use_cases": [ "Ask natural-language questions about P&L, cash flow, balance sheet, liquidity, and KPI data stored in SQLite", "Evaluate investment projects, NPV, IRR, payment calendars, and contract risk through typed MCP tools", "Test finance tool logic independently through the registry dispatch pattern before connecting a full MCP client" ], "health": "active" }, { "id": "agy-mcp-server", "name": "agy-mcp-server", "description": "Zero-third-party-runtime Python stdio MCP bridge for the local agy CLI. It supports synchronous execution and durable background jobs while leaving OAuth and account authentication to agy itself, storing job state under a private local directory with restrictive permissions. Public GitHub repository created September 8, 2026.", "category": "ai", "endpoint": "agy-mcp-server", "homepage_url": "https://github.com/HackerWilson/agy-mcp-server#readme", "github_url": "https://github.com/HackerWilson/agy-mcp-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uv tool install git+https://github.com/HackerWilson/agy-mcp-server.git", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "agy", "cli-bridge", "background-jobs", "python", "stdio", "durable-jobs", "oauth-delegation", "zero-dependency" ], "use_cases": [ "Expose a local agy CLI to MCP clients without giving the bridge direct access to OAuth tokens", "Start long-running agy work as durable background jobs and poll status from an assistant conversation", "Install as a simple stdio command with pipx or uv tool for Claude Desktop, Antigravity, or compatible clients" ], "health": "active" }, { "id": "mcp-developer-server", "name": "MCP Developer Server", "description": "Sandboxed Python MCP server for read-only source-code inspection inside a contained workspace. It implements the 2026-07-28 MCP revision, redacts secrets, marks model-facing results as untrusted, publishes seven tools for reading and searching code, and includes conformance checks plus both stdio and HTTP modes. Public GitHub repository created September 8, 2026.", "category": "code", "endpoint": "uvx --from mcp-devserver mcp-devserver serve --transport stdio", "homepage_url": "https://kogunlowo123.github.io/mcp-developer-server/", "github_url": "https://github.com/kogunlowo123/mcp-developer-server", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "uvx --from mcp-devserver mcp-devserver serve --transport stdio", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "source-code", "sandbox", "read-only", "secret-redaction", "python", "mcp-2026-07-28", "conformance", "developer-tools" ], "use_cases": [ "Give an assistant read-only project overview, tree, file-reading, and code-search tools scoped to one repository", "Reduce accidental exfiltration by redacting secrets and preventing network, shell, write, move, or delete operations", "Run conformance checks against stdio or HTTP MCP servers implementing the 2026-07-28 specification" ], "health": "active" }, { "id": "kinetis-mcp-docs", "name": "kinetis/mcp-docs", "description": "Standalone PHP MCP documentation server for the Kinetis non-blocking PHP framework. It exposes Kinetis documentation as MCP resources over stdio, can be installed through a setup script that registers with Claude Code or Codex, and also runs from a Composer project through vendor/bin/kinetis-mcp-docs. Public GitHub repository created September 8, 2026.", "category": "code", "endpoint": "php vendor/bin/kinetis-mcp-docs", "homepage_url": "https://kinetis.dev/docs/mcp-docs.html", "github_url": "https://github.com/kinetis-dev/mcp-docs", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "composer require kinetis/mcp-docs", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "kinetis", "php", "documentation", "resources", "composer", "claude-code", "codex", "stdio" ], "use_cases": [ "Expose Kinetis framework documentation to a coding agent as local MCP resources", "Register a one-command docs server with Claude Code or Codex for PHP framework assistance", "Run the documentation server from Composer inside an existing PHP project" ], "health": "active" }, { "id": "openvidstudio", "name": "openvidstudio", "description": "Open-source MCP-driven video-generation pipeline for product demo and launch videos. It combines Remotion and Playwright with an npx-installable MCP server so Claude Code, Cursor, ChatGPT, or another MCP client can drive browser capture, keyframing, narration, music-bed, and rendering workflows through sixteen tools. Public GitHub repository created September 2, 2026 and actively updated September 8, 2026.", "category": "media", "endpoint": "npx -y @openvidstudio/mcp-server", "homepage_url": "https://openvidstudio.vercel.app", "github_url": "https://github.com/AnayDhawan/openvidstudio", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y @openvidstudio/mcp-server", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "video-generation", "remotion", "playwright", "product-demos", "launch-videos", "npx", "typescript", "browser-capture" ], "use_cases": [ "Let an AI coding agent generate cinematic launch or demo videos from a real running product", "Drive browser capture, animation timing, narration, cursor motion, and rendering through MCP tools", "Install through npx for immediate use or build the monorepo locally with pnpm for development" ], "health": "active" }, { "id": "niblet-skill-mcp", "name": "Niblet MCP", "description": "MCP server and companion design skill from PyModel for grounding coding-agent UI work in real product screens. The hosted HTTP server or local npx stdio server exposes two tools for Niblet screen references and design-skill retrieval, with token-based access and production origins configurable through environment variables. Public GitHub repository created September 6, 2026 and updated September 8, 2026.", "category": "web", "endpoint": "npx -y @pymodel/niblet", "homepage_url": "https://niblet.com", "github_url": "https://github.com/PyModel/niblet-skill-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "api-key", "install_cmd": "claude mcp add niblet --env NIBLET_TOKEN=$NIBLET_TOKEN -- npx -y @pymodel/niblet", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "ui-design", "screen-references", "agent-skills", "frontend", "niblet", "npx", "api-key", "design-system" ], "use_cases": [ "Ground frontend coding agents in real product-screen references instead of generic UI templates", "Fetch the Niblet design skill and matching reference materials through an MCP-compatible client", "Use the hosted HTTP endpoint or run the same two-tool server locally over stdio with an environment token" ], "health": "active" }, { "id": "cascade-mcp", "name": "Cascade", "description": "JavaScript MCP server and CLI for code-to-column change-impact knowledge graphs. It traces the round trip from frontend screens and HTTP endpoints through Java, MyBatis, SQL statements, database tables, and columns, helping AI coding agents understand downstream effects before editing enterprise applications. Public GitHub repository created September 5, 2026 and updated September 8, 2026.", "category": "code", "endpoint": "cascade mcp", "homepage_url": "https://alexsoft-hq.github.io/Cascade/", "github_url": "https://github.com/alexsoft-hq/Cascade", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npm install -g @alexsoft-hq/cascade", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "impact-analysis", "knowledge-graph", "sql-lineage", "mybatis", "spring-boot", "vue", "static-analysis", "enterprise-code" ], "use_cases": [ "Ask which screens, endpoints, SQL statements, tables, and columns are affected before changing enterprise code", "Map Vue or Java frontend/backend flows through Spring Boot, MyBatis, and SQL lineage into a graph", "Give coding agents context about database-column impact before they refactor or modify an application path" ], "health": "active" }, { "id": "ptc-web", "name": "ptc-web", "description": "Standalone browser-content MCP server for JavaScript-rendered pages. It uses official MCP 2026-07-28 stdio transport and a server-owned Playwright Chromium profile to fetch bounded, inspectable page snapshots, apply extraction recipes, paginate cursor-protected results, and block unsafe URL forms by default. Public GitHub repository created September 8, 2026.", "category": "web", "endpoint": "npx -y ptc-web", "homepage_url": "https://github.com/andreasronge/ptc-web#readme", "github_url": "https://github.com/andreasronge/ptc-web", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "npx -y playwright@1.63.0 install chromium && npx -y ptc-web", "added": "2026-09-08", "updated": "2026-09-08", "tags": [ "browser-content", "playwright", "javascript-rendered", "extraction", "snapshots", "mcp-2026-07-28", "stdio", "typescript" ], "use_cases": [ "Give an MCP client bounded read access to JavaScript-rendered pages through a server-owned Chromium profile", "Extract article, listing, discussion, table, and custom recipe data without broad browser-control tools", "Use cursor-protected snapshots and response-size limits for inspectable web-content workflows" ], "health": "active" }, { "id": "asic-lookup-mcp", "name": "ASIC Lookup MCP", "description": "x402-paid MCP server for searching the Australian ASIC company register by ABN, ACN, or company name. It runs through npx, requires an explicit total spend cap before startup, charges USD 0.01 per successful lookup in USDC on Base, and uses payment as the credential instead of an account or API key. Public GitHub repository created September 9, 2026.", "category": "payments", "endpoint": "npx -y @nightshiftbuilds/asic-lookup-mcp", "homepage_url": "https://github.com/keitaemsden-lab/asic-lookup-mcp#readme", "github_url": "https://github.com/keitaemsden-lab/asic-lookup-mcp", "x402": true, "x402_price": "USD 0.01 per successful lookup", "verified": false, "protocols": [ "MCP", "x402" ], "transport": "stdio", "auth": "x402", "install_cmd": "claude mcp add asic-lookup --env SPEND_CAP_USD=1.00 --env PRIVATE_KEY_FILE=$HOME/.config/asic-lookup/key -- npx -y @nightshiftbuilds/asic-lookup-mcp", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "asic", "australia", "company-register", "abn", "acn", "x402", "usdc", "base" ], "use_cases": [ "Look up Australian registered companies by ABN, ACN, or name from an MCP client", "Experiment with bounded x402 payments where a successful lookup costs USD 0.01 and failed or malformed lookups are free", "Give agent-commerce workflows a concrete paid data retrieval service with spend caps enforced at startup" ], "health": "active" }, { "id": "minecraft-ai-companion", "name": "Minecraft AI Companion MCP", "description": "Early-alpha local Streamable HTTP MCP bridge that gives an AI companion its own Mineflayer-backed player in a Minecraft Java LAN world. It exposes explicit Minecraft action tools through a localhost bearer-token bridge, has been live-tested on Java 1.21.11, and keeps the model subscription outside the server. Public GitHub repository created September 9, 2026.", "category": "media", "endpoint": "node src/server.js", "homepage_url": "https://github.com/ToTRW/minecraft-ai-companion#readme", "github_url": "https://github.com/ToTRW/minecraft-ai-companion", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/ToTRW/minecraft-ai-companion.git && cd minecraft-ai-companion && npm install", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "minecraft", "mineflayer", "game-agents", "streamable-http", "localhost", "bearer-token", "javascript", "early-alpha" ], "use_cases": [ "Let an MCP-capable AI client join a Minecraft Java LAN world as a separate companion player", "Call explicit game actions such as mining, crafting, equipping, smelting, placing blocks, and waiting for events", "Prototype local game-agent workflows without adding camera input or an autonomous decision loop to the server" ], "health": "active" }, { "id": "anymd", "name": "anymd", "description": "Python CLI, library, and MCP server that converts real-world documents into LLM-friendly Markdown. It covers 24 converter families across Office, PDF, email, ebooks, images, archives, data files, and code, with explicit truncation markers, stdout/stderr separation, NDJSON manifests, encoding detection, OCR extras, and zip-bomb or SSRF safeguards. Public GitHub repository created September 9, 2026.", "category": "productivity", "endpoint": "anymd mcp", "homepage_url": "https://github.com/Ljf857/anymd#readme", "github_url": "https://github.com/Ljf857/anymd", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install anymd", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "document-conversion", "markdown", "pdf", "office", "email", "ebooks", "ocr", "python" ], "use_cases": [ "Convert Office files, PDFs, emails, ebooks, images, archives, data files, or source files into structured Markdown for agents", "Use explicit truncation markers, page comments, manifests, and meaningful exit codes in automated document-ingestion pipelines", "Handle Chinese Windows encodings and mislabeled file extensions more safely than ad hoc conversion scripts" ], "health": "active" }, { "id": "mu-ebook-scout", "name": "mu-ebook-scout", "description": "Multi-source ebook search tool delivered as a CLI, MCP server, and Agent Skill shell. It searches public-domain and open-license Chinese and English ebook sources, ranks links, and only downloads files when explicitly requested, using one core engine across all front ends. Public GitHub repository created September 9, 2026.", "category": "web", "endpoint": "mu-ebook-scout mcp", "homepage_url": "https://muippt.github.io/mu-ebook-scout/", "github_url": "https://github.com/muippt/mu-ebook-scout", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "pip install mu-ebook-scout", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "ebooks", "public-domain", "open-license", "chinese", "english", "search", "downloads", "agent-skill" ], "use_cases": [ "Search Chinese and English public-domain or open-license ebook sources from an assistant conversation", "Surface ranked legal links first and defer file downloads until the user explicitly asks", "Use the same book-search engine through CLI, MCP, or an Agent Skill shell" ], "health": "active" }, { "id": "crossingkey-mcp", "name": "CrossingKey MCP", "description": "Hosted MCP server for agent commerce, prepaid credits, bounded paid execution, and machine-readable fulfillment. The public repo documents a production endpoint, offer and checkout discovery, credit-balance checks, fulfillment status, request-service discovery, and authenticated bounded execution with receipt and commit or release semantics. Public GitHub repository created September 9, 2026.", "category": "payments", "endpoint": "https://mcp.crossingkeyintelligence.com/mcp", "homepage_url": "https://github.com/crossingkey-holdings/crossingkey-mcp#readme", "github_url": "https://github.com/crossingkey-holdings/crossingkey-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "claude mcp add --transport http crossingkey https://mcp.crossingkeyintelligence.com/mcp", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "agent-commerce", "prepaid-credits", "paid-execution", "fulfillment", "stripe", "receipts", "streamable-http", "bounded-execution" ], "use_cases": [ "Discover paid agent-commerce offers and checkout paths from an MCP client", "Run bounded paid execution only after authorization, credit reservation, verification, sanitization, and receipt generation", "Check fulfillment readiness against machine-readable manifests and SHA-256 digests" ], "health": "active" }, { "id": "ship24-ai-plugin", "name": "Ship24 AI Plugin", "description": "Official Ship24 plugin for AI coding agents that bundles skills, an integration reviewer, and a hosted Tracking MCP server. It supports Claude Code, Cursor, Codex, Copilot, Gemini CLI, and Agent Skills-compatible tools for integrating Ship24 Tracking API workflows across 2,500-plus carriers with generated endpoint and schema tables. Public GitHub repository created September 9, 2026.", "category": "productivity", "endpoint": "https://docs.ship24.com/integrate-with-ai", "homepage_url": "https://docs.ship24.com/integrate-with-ai", "github_url": "https://github.com/ship24/ship24-ai-plugin", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/ship24/ship24-ai-plugin.git", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "parcel-tracking", "ship24", "shipping", "couriers", "webhooks", "tracking-api", "agent-skills", "integration-review" ], "use_cases": [ "Integrate parcel tracking and webhook flows with Ship24 from an AI coding-agent workflow", "Use generated API schemas and endpoint tables to reduce drift when building shipment tracking features", "Track parcels across thousands of carriers through a hosted MCP-assisted integration path" ], "health": "active" }, { "id": "citydpc-mcp", "name": "CityDPC MCP Server", "description": "Python stdio MCP server for inspecting, analyzing, and editing CityJSON and CityGML building datasets through CityDPC. It includes an 18-tool server guide, dataset lifecycle docs, read-only examples, benchmark evaluation, and paper evidence comparing MCP-assisted workflows with no-tool and code-interpreter baselines. Public GitHub repository created September 9, 2026.", "category": "data", "endpoint": "python mcp-server/cityDPC.py", "homepage_url": "https://github.com/HamerJava/CityDPC-MCP#readme", "github_url": "https://github.com/HamerJava/CityDPC-MCP", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/HamerJava/CityDPC-MCP.git && cd CityDPC-MCP && python3.12 -m venv .venv && . .venv/bin/activate && python -m pip install -r requirements-lock.txt", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "cityjson", "citygml", "geospatial", "buildings", "citydpc", "datasets", "benchmark", "python" ], "use_cases": [ "Inspect and analyze CityJSON or CityGML building datasets through typed MCP tools", "Run local research workflows over sample or user-provided city datasets with explicit dataset-directory configuration", "Evaluate MCP-assisted geospatial workflows against documented benchmark tasks and paper evidence" ], "health": "active" }, { "id": "kingtime", "name": "Kingtime", "description": "Open-source time tracking app for freelancers and small studios with a built-in MCP server. It supports clients, projects, tasks, timers, Harvest import, Moneybird draft invoice preparation, dashboards, passkeys, and two-factor authentication, letting an LLM log time or prepare invoices through personal API-token access. Public GitHub repository created September 9, 2026.", "category": "productivity", "endpoint": "php artisan mcp:serve", "homepage_url": "https://kingtime.nl", "github_url": "https://github.com/sietzekeuning/kingtime", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "http", "auth": "api-key", "install_cmd": "git clone https://github.com/sietzekeuning/kingtime.git && cd kingtime && composer install && npm install", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "time-tracking", "freelancers", "harvest", "moneybird", "invoicing", "laravel", "vue", "api-token" ], "use_cases": [ "Let an assistant log billable time against clients, projects, and tasks through a built-in MCP server", "Import Harvest history and prepare Moneybird draft invoices with hour specifications", "Ask natural-language questions about time totals, billable ratio, dashboards, and top projects" ], "health": "active" }, { "id": "superfast-mcp", "name": "superfast-mcp", "description": "Go MCP server for local filesystem, shell, and Git operations with stdio for local clients and stateless Streamable HTTP for remote clients. Current Phase 0 and 1 tools include rooted read, write, directory listing, bounded command execution, git status, git diff, git log, and health checks, while constraining file and git paths to configured roots. Public GitHub repository created September 8, 2026.", "category": "code", "endpoint": "./superfast-mcp --stdio-only --roots /path/to/code", "homepage_url": "https://github.com/heidi-dang/superfast-mcp#readme", "github_url": "https://github.com/heidi-dang/superfast-mcp", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "git clone https://github.com/heidi-dang/superfast-mcp.git && cd superfast-mcp && go build -trimpath -o superfast-mcp ./cmd/superfast-mcp", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "filesystem", "shell", "git", "go", "streamable-http", "rooted-paths", "coding-agents", "local-tools" ], "use_cases": [ "Give local MCP clients bounded filesystem, shell, and git operations scoped to configured project roots", "Expose the same core tools over stdio locally or stateless Streamable HTTP remotely", "Inspect git status, diffs, recent logs, and file contents from coding-agent workflows" ], "health": "active" }, { "id": "agentic-recall", "name": "agentic-recall", "description": "Node-based long-term memory MCP server for Claude Desktop and Claude Code. It indexes a user-supplied MEMORY_DIR of markdown memories, runs embeddings locally after first download, supports hybrid retrieval, and explicitly reports when the corpus does not contain an answer instead of forcing a weak match. Public GitHub repository created September 8, 2026.", "category": "ai", "endpoint": "npx -y agentic-recall", "homepage_url": "https://www.npmjs.com/package/agentic-recall", "github_url": "https://github.com/dfrancislyondflabc-tech/agentic-recall", "x402": false, "verified": false, "protocols": [ "MCP" ], "transport": "stdio", "auth": "none", "install_cmd": "claude mcp add memory --env MEMORY_DIR=/absolute/path/to/your/memory/folder -- npx -y agentic-recall", "added": "2026-09-09", "updated": "2026-09-09", "tags": [ "memory", "markdown", "retrieval", "embeddings", "local-first", "claude-code", "npx", "absence-verdict" ], "use_cases": [ "Give Claude Desktop or Claude Code persistent memory over a user-selected markdown folder", "Ask whether the corpus contains a fact and receive an explicit absence verdict when it does not", "Use local embeddings and hybrid retrieval without sending private memories to a hosted vector database" ], "health": "active" } ], "total": 1278, "updated": "2026-09-09", "source": "agentndx.ai", "note": "Machine-readable index of all indexed MCP servers. For search: /api/search?q=..." }