Pinecone Model Context Protocol Server for Claude Desktop.

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

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.

Quickstart

Installing via Smithery

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

Install the server

uvx install mcp-pinecone

uv pip install mcp-pinecone

Claude Desktop

~/Library/Application\ Support/Claude/claude_desktop_config.json

%APPDATA%/Claude/claude_desktop_config.json

uv

which uv

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

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

Sign up to Pinecone

Get an API key

{your-index-name}

{your-secret-api-key}

Development

Building and Publishing

1. Sync dependencies and update lockfile:

uv sync

1. Build package distributions:

uv build

dist/

1. Publish to PyPI:

uv publish

• Token:

  --token

  or

  UV_PUBLISH_TOKEN

• Or username/password:

  --username

  /

  UV_PUBLISH_USERNAME

  and

  --password

  /

  UV_PUBLISH_PASSWORD

Debugging

npm

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

License

Source Code

Contributing