sirmews/mcp-pinecone
by Various
Model Context Protocol server to allow for reading and writing from Pinecone. Rudimentary RAG
MCP
sirmews/mcp-pinecone
Added 1 June 2026
Overview
A Model Context Protocol server that connects LLM hosts to Pinecone vector databases for basic retrieval-augmented generation. It provides read and write operations against a Pinecone index via the standard MCP interface.
Best for
Best for
Developers who need a minimal MCP connector to add Pinecone-based memory or knowledge retrieval to an LLM client.
Use cases
- Attach a Pinecone knowledge base to an MCP-compatible LLM client for context retrieval
- Insert documents or embeddings into a Pinecone index from an LLM session
- Query a Pinecone index for similar vectors during a chat or agent workflow
How to use
Install
npx -y @smithery/cli install mcp-pinecone --client claude Tools exposed
semantic-searchread-documentlist-documentspinecone-statsprocess-document
Tested with
Claude Desktop
Notes
A Model Context Protocol server that connects LLM hosts to Pinecone vector databases for basic retrieval-augmented generation. It provides read and write operations against a Pinecone index via the standard MCP interface.
149 stars on GitHub. Last updated 2025-01-31. Licensed MIT.
Use cases
- Attach a Pinecone knowledge base to an MCP-compatible LLM client for context retrieval
- Insert documents or embeddings into a Pinecone index from an LLM session
- Query a Pinecone index for similar vectors during a chat or agent workflow
Pros
- Adheres to the Model Context Protocol for easy integration with MCP-supporting tools
- Lightweight Python server with a focused feature set
- Straightforward read and write operations for basic RAG workflows
Cons
- Limited to rudimentary RAG with no built-in chunking or embedding management
- Relies on the user to manage Pinecone index configuration and API keys externally
- Small community (149 stars) and single maintainer may affect long-term support
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Adheres to the Model Context Protocol for easy integration with MCP-supporting tools
- Lightweight Python server with a focused feature set
- Straightforward read and write operations for basic RAG workflows
Cons
- Limited to rudimentary RAG with no built-in chunking or embedding management
- Relies on the user to manage Pinecone index configuration and API keys externally
- Small community (149 stars) and single maintainer may affect long-term support
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Milvus
Community
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
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Community
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Chroma
Community
Search infrastructure for AI
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