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Built with ❤️ by Krishna Goyal

    Mcp Pinecone

    Model Context Protocol server to allow for reading and writing from Pinecone. Rudimentary RAG Python-based implementation.

    148 stars
    Python
    Updated Oct 31, 2025
    claude
    mcp
    mcp-server
    model-context-protocol
    pinecone
    rag

    Table of Contents

    • Components
    • Resources
    • Tools
    • Quickstart
    • Installing via Smithery
    • Install the server
    • Claude Desktop
    • Sign up to Pinecone
    • Get an API key
    • Development
    • Building and Publishing
    • Debugging
    • License
    • Source Code
    • Contributing

    Table of Contents

    • Components
    • Resources
    • Tools
    • Quickstart
    • Installing via Smithery
    • Install the server
    • Claude Desktop
    • Sign up to Pinecone
    • Get an API key
    • Development
    • Building and Publishing
    • Debugging
    • License
    • Source Code
    • Contributing

    Documentation

    Pinecone Model Context Protocol Server for Claude Desktop.

    smithery badge

    PyPI - Downloads

    Read and write to a Pinecone index.

    Components

    mermaid
    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:

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

    Install the server

    Recommend using uv to install the server locally for Claude.

    code
    uvx install mcp-pinecone

    OR

    code
    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__

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

    __Published Servers Configuration__

    json
    "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:

    bash
    uv sync

    2. Build package distributions:

    bash
    uv build

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

    3. Publish to PyPI:

    bash
    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](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) with this command:

    bash
    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.

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