Use the Pinecone MCP server - Pinecone Docs (original) (raw)
The Pinecone MCP server enables AI agents to interact directly with Pinecone’s functionality and documentation via the standardized Model Context Protocol (MCP). Using the MCP server, agents can search Pinecone documentation, manage indexes, upsert data, and query indexes for relevant information.
This page shows you how to configure Cursor and Claude Desktop to connect with the Pinecone MCP server.
The Pinecone MCP server provides the following tools:
search-docs: Search the official Pinecone documentation.list-indexes: Lists all Pinecone indexes.describe-index: Describes the configuration of an index.describe-index-stats: Provides statistics about the data in the index, including the number of records and available namespaces.create-index-for-model: Creates a new index that uses an integrated inference model to embed text as vectors.upsert-records: Inserts or updates records in an index with integrated inference.search-records: Searches for records in an index based on a text query, using integrated inference for embedding. Has options for metadata filtering and reranking.cascading-search: Searches for records across multiple indexes, deduplicating and reranking the results.rerank-documents: Reranks a collection of records or text documents using a specialized reranking model.
Before you begin
Ensure you have the following:
- A Pinecone API key
- Node.js installed, with
nodeandnpxavailable on yourPATH