Pinecone Model Context Protocol Server for Claude Desktop.

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Read and write to a Pinecone index.

Components

flowchart TB
 subgraph Client["MCP Client (e.g., Claude Desktop)"]
 UI[User Interface]
 end

 subgraph MCPServer["MCP Server (pinecone-mcp)"]
 Server[Server Class]
 
 subgraph Handlers["Request Handlers"]
 ListRes[list_resources]
 ReadRes[read_resource]
 ListTools[list_tools]
 CallTool[call_tool]
 GetPrompt[get_prompt]
 ListPrompts[list_prompts]
 end
 
 subgraph Tools["Implemented Tools"]
 SemSearch[semantic-search]
 ReadDoc[read-document]
 ListDocs[list-documents]
 PineconeStats[pinecone-stats]
 ProcessDoc[process-document]
 end
 end

 subgraph PineconeService["Pinecone Service"]
 PC[Pinecone Client]
 subgraph PineconeFunctions["Pinecone Operations"]
 Search[search_records]
 Upsert[upsert_records]
 Fetch[fetch_records]
 List[list_records]
 Embed[generate_embeddings]
 end
 Index[(Pinecone Index)]
 end

 %% Connections
 UI --> Server
 Server --> Handlers
 
 ListTools --> Tools
 CallTool --> Tools
 
 Tools --> PC
 PC --> PineconeFunctions
 PineconeFunctions --> Index
 
 %% Data flow for semantic search
 SemSearch --> Search
 Search --> Embed
 Embed --> Index
 
 %% Data flow for document operations
 UpsertDoc --> Upsert
 ReadDoc --> Fetch
 ListRes --> List

 classDef primary fill:#2563eb,stroke:#1d4ed8,color:white
 classDef secondary fill:#4b5563,stroke:#374151,color:white
 classDef storage fill:#059669,stroke:#047857,color:white
 
 class Server,PC primary
 class Tools,Handlers secondary
 class Index storage

Resources

The server implements the ability to read and write to a Pinecone index.

Tools

• semantic-search: Search for records in the Pinecone index.

• read-document: Read a document from the Pinecone index.

• list-documents: List all documents in the Pinecone index.

• pinecone-stats: Get stats about the Pinecone index, including the number of records, dimensions, and namespaces.

• process-document: Process a document into chunks and upsert them into the Pinecone index. This performs the overall steps of chunking, embedding, and upserting.

Note: embeddings are generated via Pinecone's inference API and chunking is done with a token-based chunker. Written by copying a lot from langchain and debugging with Claude.

Related MCP server: MCP AI Server

Quickstart

Installing via Smithery

To install Pinecone MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp-pinecone --client claude

Install the server

Recommend using uv to install the server locally for Claude.

uvx install mcp-pinecone

OR

uv pip install mcp-pinecone

Add your config as described below.

Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json On Windows: %APPDATA%/Claude/claude_desktop_config.json

Note: You might need to use the direct path to uv. Use which uv to find the path.

Development/Unpublished Servers Configuration

"mcpServers": {
 "mcp-pinecone": {
 "command": "uv",
 "args": [
 "--directory",
 "{project_dir}",
 "run",
 "mcp-pinecone"
 ]
 }
}

Published Servers Configuration

"mcpServers": {
 "mcp-pinecone": {
 "command": "uvx",
 "args": [
 "--index-name",
 "{your-index-name}",
 "--api-key",
 "{your-secret-api-key}",
 "mcp-pinecone"
 ]
 }
}

Sign up to Pinecone

You can sign up for a Pinecone account here.

Get an API key

Create a new index in Pinecone, replacing {your-index-name} and get an API key from the Pinecone dashboard, replacing {your-secret-api-key} in the config.

Development

Building and Publishing

To prepare the package for distribution:

1. Sync dependencies and update lockfile:

uv sync

2. Build package distributions:

uv build

This will create source and wheel distributions in the dist/ directory.

3. Publish to PyPI:

uv publish

Note: You'll need to set PyPI credentials via environment variables or command flags:

• Token: --token or UV_PUBLISH_TOKEN

• Or username/password: --username/UV_PUBLISH_USERNAME and --password/UV_PUBLISH_PASSWORD

Debugging

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv --directory {project_dir} run mcp-pinecone

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Source Code

The source code is available on GitHub.

Contributing

Send your ideas and feedback to me on Bluesky or by opening an issue.

Maintenance

Resources

• GitHub Repository
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