What is Pinecone Model Context Protocol for Claude Desktop

The Pinecone Model Context Protocol Server is designed for Claude Desktop to read and write data to a Pinecone index, enabling efficient management and retrieval of structured data. It acts as a bridge between the client application (like Claude Desktop) and the Pinecone service, facilitating interaction with the database through a simple set of tools and APIs.

Use cases

This server can be utilized for various applications including semantic search, document retrieval, and metadata management within datasets stored in Pinecone. It allows users to efficiently interact with large amounts of data, making it effective for developers and businesses needing to perform searches, read documents, or analyze statistics related to their data.

How to use

To use the server, you need to install via Smithery or with the uv package management tool. After the setup, configure your Pinecone index name and API key in the Claude Desktop configuration file. Once configured, the server allows you to perform operations like searching, reading, and listing documents with simple commands, making it user-friendly for developers.

Key features

Key features include tools for semantic search, reading and listing documents, retrieving Pinecone index statistics, and processing documents for upserts. The server leverages Pinecone’s capabilities for generating embeddings and supports chunking of data for optimal storage and retrieval efficiency.

Where to use

The MCP Server can be used in any environment where Claude Desktop is deployed, particularly for applications requiring integration with Pinecone’s vector database capabilities. Suitable use cases include AI-based applications, data analysis platforms, and any project requiring the management of large text or vector datasets.

Pinecone Model Context Protocol Server for Claude Desktop.

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.

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

Published Servers Configuration

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.