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Pinecone MCP
Query and manage Pinecone vector indices from AI agents. Upsert embeddings, run similarity search, filter by metadata, and manage namespaces for RAG pipelines.
MCP verified
Integration
| Transport | stdio |
| Auth | api-key |
| Endpoint | npx pinecone-mcp-server |
| Install | npx pinecone-mcp-server |
Use Cases
| 01 | Upsert and query vector embeddings in Pinecone for semantic search |
| 02 | Build RAG pipelines with Pinecone as the long-term knowledge store |
| 03 | Manage vector namespaces and metadata filters from agent workflows |
Tags
pinecone vector-search embeddings rag semantic-search
Machine-readable: /api/servers.json
· JSON-LD schema embedded in <head>