sirmews/mcp-pinecone

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

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.