MCP Server Proto-OKN

MCP Server Proto-OKN

A Model Context Protocol server that provides tools for querying SPARQL endpoints, with specialized support for Proto-OKN knowledge graphs hosted on the FRINK platform.

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MCP Server Proto-OKN

A Model Context Protocol (MCP) server that provides tools for querying SPARQL endpoints, with specialized support for Proto-OKN (Prototype Open Knowledge Network) knowledge graphs hosted on the FRINK platform.

Features

  • FRINK Integration: Automatic detection and documentation linking for FRINK-hosted knowledge graphs
  • Proto-OKN Support: Optimized for querying knowledge graphs in the Proto-OKN ecosystem including:
    • SPOKE (Scalable Precision Medicine Open Knowledge Engine)
    • BioBricks ICE (Chemical safety and cheminformatics)
    • DREAM-KG (Addressing homelessness with explainable AI)
    • SAWGraph (Safe Agricultural Products and Water monitoring)
    • And many other Proto-OKN knowledge graphs
  • Flexible Configuration: Support for both FRINK and custom SPARQL endpoints
  • Automatic Documentation: Registry links for supported knowledge graphs

Installation

Prerequisites

  1. Install VS Code Insiders (required for MCP support)

    Download and install VS Code Insiders from https://code.visualstudio.com/insiders/

    VS Code Insiders is needed because it includes the latest MCP (Model Context Protocol) features.

  2. Install GitHub Copilot extension (required for MCP integration)

    • Open VS Code Insiders
    • Install the GitHub Copilot extension from the marketplace
    • Sign in with your GitHub account that has Copilot access
    • Note: You need an active GitHub Copilot subscription to use MCP features

    MCP servers integrate with VS Code through the Copilot Chat interface.

  3. Install uv (Python package manager)

    # macOS/Linux
    curl -LsSf https://astral.sh/uv/install.sh | sh
    
    # Windows
    powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
    
    # Or via pip
    pip install uv
    

Setup Instructions

  1. Clone and setup the project

    git clone https://github.com/sbl-sdsc/mcp-proto-okn.git
    cd mcp-proto-okn
    uv sync
    
  2. Configure the MCP servers

    This project includes a pre-configured .vscode/mcp.json file with multiple Proto-OKN knowledge graph endpoints. You need to update the commands to use the new mcp-server-protookn:

    Edit .vscode/mcp.json and update the server configurations:

    {
      "servers": {
        "mcp-spoke-sparql": {
          "command": "uv",
          "args": ["run", "python", "-m", "mcp_server_protookn.server", "--endpoint", "https://frink.apps.renci.org/spoke/sparql"]
        },
        "mcp-dreamkg-sparql": {
          "command": "uv",
          "args": ["run", "python", "-m", "mcp_server_protookn.server", "--endpoint", "https://frink.apps.renci.org/dreamkg/sparql"]
        }
      }
    }
    

    The existing file contains configurations for all major Proto-OKN knowledge graphs. You can enable/disable specific servers by adding or removing them from the configuration.

  3. Start using the MCP server

    • Open VS Code Insiders
    • Open a new chat window
    • The MCP servers should automatically connect and provide access to the knowledge graphs

Quick Start: Query a Knowledge Graph

Once everything is set up, you can start querying knowledge graphs through the VS Code chat interface:

Example prompts to try:

  1. Explore the SPOKE knowledge graph structure:

    What types of entities are available in the SPOKE knowledge graph?
    
  2. Query that combines multiple entity types:

    Antibiotic contamination can contribute to antimicrobial resistance. Find locations with antibiotic contamination.
    
  3. Query across multiple KGs:

    What type of data is available for perfluorooctanoic acid in SPOKE, BioBricks, and SAWGraph?
    

The chat interface will use the MCP server to execute SPARQL queries against the configured endpoints and return structured results.

Alternative Installation Methods

Using uvx (standalone execution)

uvx mcp-server-protookn --endpoint https://frink.apps.renci.org/spoke/sparql

Usage

Command Line Parameters

The MCP server accepts the following command line arguments:

Required:

  • --endpoint: SPARQL endpoint URL (e.g., https://frink.apps.renci.org/spoke/sparql)

Optional:

  • --description: Custom description for the SPARQL endpoint (automatically generated for FRINK endpoints)

Command Line

# FRINK endpoint (automatic documentation linking)
uvx mcp-server-protookn --endpoint https://frink.apps.renci.org/spoke/sparql

# Custom endpoint with description
uvx mcp-server-protookn --endpoint https://example.com/sparql --description "Custom SPARQL endpoint"

Tool: query

Execute a SPARQL query against the configured endpoint.

Parameters:

  • query_string: A valid SPARQL query string
  • description: Custom description for the SPARQL endpoint (automatically generated for FRINK endpoints)

Returns:

  • The query results in JSON format

Links

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