Pinecone MCP

Local · stdio

Pinecone is a managed vector database for semantic search and RAG, and its official MCP server gives agents the full index lifecycle right from a conversation: creating an index for a specific embedding model, upserting and searching records, reranking results, and searching Pinecone's own documentation. It runs locally via npx with a PINECONE_API_KEY variable and needs no separate cloud endpoint.

Why this server

create-index-for-model provisions an index for the right embedding model in one call
rerank-documents sharpens accuracy by re-sorting results that were already retrieved
search-docs searches Pinecone's own documentation — no need to google the API syntax
cascading-search combines multiple indexes in a single similarity query

Usage examples

Prompt: Create an index for the support knowledge base and upsert these 200 articles

Result: The agent called create-index-for-model with a matching embedding model, then upsert-records loaded all the articles into the new index.

Prompt: Find knowledge-base answers about product returns and pick the most relevant one

Result: search-records returned several similar articles, and rerank-documents re-sorted them, bringing the most accurate one to the top.

Local server

This MCP runs locally on the user's machine (stdio), so availability isn't tracked — rely on reviews and the rating instead.

Reviews

No reviews yet.