MCP Server Proto-OKN

A Model Context Protocol (MCP) server providing seamless access to SPARQL endpoints with specialized support for the NSF-funded Proto-OKN Project (Prototype Open Knowledge Network). This server enables intelligent querying of biomedical and scientific knowledge graphs hosted on the FRINK platform.

Features

• 🔗 FRINK Integration: Automatic detection and documentation linking for FRINK-hosted knowledge graphs

• 🧬 Proto-OKN Ecosystem: Optimized support for biomedical and scientific knowledge graphs including:

  • SPOKE - Scalable Precision Medicine Open Knowledge Engine

  • BioBricks ICE - Chemical safety and cheminformatics data

  • DREAM-KG - Addressing homelessness with explainable AI

  • SAWGraph - Safe Agricultural Products and Water monitoring

  • Additional Proto-OKN knowledge graphs - Expanding ecosystem of scientific data

• ⚙️ Flexible Configuration: Support for both FRINK and custom SPARQL endpoints

• 📚 Automatic Documentation: Registry links and metadata for supported knowledge graphs

Architecture

The MCP Server Proto-OKN acts as a bridge between AI assistants (like Claude) and SPARQL knowledge graphs, enabling natural language queries to be converted into structured SPARQL queries and executed against scientific databases.

Prerequisites

Before installing the MCP Server Proto-OKN, ensure you have:

• Operating System: macOS, Linux, or Windows

• Client Application: One of the following:

  • Claude Desktop with Pro or Max subscription

  • VS Code Insiders with GitHub Copilot subscription

Installation

Initial Setup

1. Install uv Package Manager

   The uv package manager is required for Python dependency management:

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

   Note: Python installation is not required. uv will automatically install Python and all dependencies.

2. Verify Installation Path (macOS only)

   which uv

   If uv is not installed in /usr/local/bin, create a symbolic link for Claude Desktop compatibility:

   sudo ln -s $(which uv) /usr/local/bin/uv

3. Clone and Setup Project

   git clone https://github.com/sbl-sdsc/mcp-proto-okn.git cd mcp-proto-okn uv sync

4. Create a

   The tool runs in a self-contained environment managed by uv.

   uv tool install $HOME/path_to_git_repo/mcp-proto-okn uv tool list

Claude Desktop Setup

Recommended for most users

1. Download and Install Claude Desktop

   Visit https://claude.ai/download and install Claude Desktop for your operating system.

   Requirements: Claude Pro or Max subscription is required for MCP server functionality.

2. Configure MCP Server

   macOS

   cp claude_desktop_config.json "$HOME/Library/Application Support/Claude/"

   Windows

   copy claude_desktop_config.json %APPDATA%\Claude\claude_desktop_config.json

   Refer to the Claude documentation for details.

   Note: If you have existing MCP server configurations, merge the contents instead of overwriting.

3. Restart Claude Desktop

   After saving the configuration file, quit Claude Desktop and restart it. The application needs to restart to load the new configuration and start the MCP server.

4. Verify Installation

   1. Launch Claude Desktop

   2. Click "Connect your tools to Claude" at the bottom of the interface

   3. Click "Manage connectors"

   4. Verify that mcp-proto-okn tools appear in the connector list

VS Code Setup

For advanced users and developers

1. Install VS Code Insiders

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

   Note: VS Code Insiders is required as it includes the latest MCP (Model Context Protocol) features.

2. Install GitHub Copilot Extension

   • Open VS Code Insiders

   • Sign in with your GitHub account

   • Install the GitHub Copilot extension

   Requirements: GitHub Copilot subscription is required for MCP integration.

3. Configure Workspace

   1. Open VS Code Insiders

   2. File → Open Folder → Select mcp-proto-okn directory

   3. Open a new chat window

   4. Select Agent mode

   5. Choose Claude Sonnet 4 model for optimal performance

   6. The MCP servers will automatically connect and provide knowledge graph access

Configuration

The server comes pre-configured with 10 Proto-OKN SPARQL endpoints. You can customize the configuration by editing the appropriate files:

• Claude Desktop: claude_desktop_config.json

• VS Code: .vscode/mcp.json

Adding Custom Endpoints

To add additional Proto-OKN endpoints or third-party SPARQL endpoints, modify the configuration file. The snippet below shows how to specify FRINK and third-party endpoints.

Note: For VS Code configuration (.vscode/mcp.json), replace mcpServers with servers.

Quick Start

Once configured, you can immediately start querying knowledge graphs through natural language prompts in Claude Desktop or VS Code chat interface.

Example Queries

1. Knowledge Graph Overview

   Provide a concise overview of the SPOKE knowledge graph, including its main purpose, data sources, and key features.

2. Multi-Entity Analysis

   Antibiotic contamination can contribute to antimicrobial resistance. Find locations with antibiotic contamination.

3. Cross-Knowledge Graph Comparison

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

The AI assistant will automatically convert your natural language queries into appropriate SPARQL queries, execute them against the configured endpoints, and return structured, interpretable results.

Usage

Command Line Interface

The MCP server can be invoked directly with the following parameters:

Required Parameters:

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

Optional Parameters:

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

Example Usage

API Reference

Available Tools

query

Executes SPARQL queries against the configured endpoint.

Parameters:

• query_string (string, required): A valid SPARQL query

Returns:

• JSON object containing query results

get_description

Retrieves endpoint metadata and documentation.

Parameters:

• None

Returns:

• String containing endpoint description, PI information, funding details, and related documentation links

License

This project is licensed under the BSD 3-Clause License. See the LICENSE file for details.

Citation

If you use MCP Server Proto-OKN in your research, please cite the following works:

Related Publications

• Nelson, C.A., Rose, P.W., Soman, K., Sanders, L.M., Gebre, S.G., Costes, S.V., Baranzini, S.E. (2025). "Nasa Genelab-Knowledge Graph Fabric Enables Deep Biomedical Analysis of Multi-Omics Datasets." NASA Technical Reports, 20250000723. Link

• Sanders, L., Costes, S., Soman, K., Rose, P., Nelson, C., Sawyer, A., Gebre, S., Baranzini, S. (2024). "Biomedical Knowledge Graph Capability for Space Biology Knowledge Gain." 45th COSPAR Scientific Assembly, July 13-21, 2024. Link

Acknowledgments

Funding

This work is supported by:

• National Science Foundation Award #2333819: "Proto-OKN Theme 1: Connecting Biomedical information on Earth and in Space via the SPOKE knowledge graph"

Related Projects

• Proto-OKN Project - Prototype Open Knowledge Network initiative

• FRINK Platform - Knowledge graph hosting infrastructure

• Knowledge Graph Registry - Catalog of available knowledge graphs

• Model Context Protocol - AI assistant integration standard

• Original MCP Server SPARQL - Base implementation reference

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