Pinecone MCP Server
Pinecone index records accessed through semantic search and document tools.
Data last scanned yesterday · Reviewed last month
Overview
This MCP server enables AI assistants like Claude Desktop to interact directly with Pinecone indices. It facilitates semantic search, document retrieval, and record listing, while also supporting document processing tasks such as chunking and upserting data.
Our verdict
This server carries a high risk level with a security score of 0/100. It is officially archived and no longer maintained, meaning no security patches or bug fixes will be released. It is community-developed and lacks editorial review, making it unsuitable for use in environments where reliability and security are required.
- Supports semantic search and document management
- Contains zero direct software dependencies
- Includes documentation for provided toolset
- Licensed under the MIT license
- Repository is archived and abandoned
- Last code commit occurred over 500 days ago
- Not verified by official Pinecone support
- Security architecture has not been editorially reviewed
Tools
| Tool | Description | Risk |
|---|---|---|
| semantic-search | Search for records in the Pinecone index. | low |
| read-document | Read a document from the Pinecone index. | low |
| list-documents | List all documents in the Pinecone index. | low |
| pinecone-stats | Get stats about the Pinecone index, including the number of records, dimensions, and namespaces. | low |
| process-document | Process a document into chunks and upsert them into the Pinecone index. | medium |
Compatibility
| Client | Local | Docker | Remote | Read-only |
|---|---|---|---|---|
| ChatGPT | ||||
| Claude Desktop | ||||
| Cursor | ||||
| VS Code | ||||
| Windsurf |
Frequently asked questions
›What tools are included for interacting with my Pinecone index?
The server provides tools for semantic searching, listing and reading individual documents, retrieving index statistics, and processing documents into chunks for upserting.
›How does the server handle document embedding and chunking?
The server uses Pinecone's inference API to generate embeddings and performs token-based chunking on your documents during the processing step.
›What information do I need to provide in the configuration to connect to Pinecone?
You must provide your Pinecone index name and a valid Pinecone API key in the server arguments.
›How can I debug issues with the server locally?
Because the server communicates over stdio, it is recommended to use the official MCP Inspector tool to view requests and responses in your browser.
›Is there a recommended way to install this server?
The project recommends using uv for installation, either via uvx for a quick run or by using pip to install the package locally.
Alternatives
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