nickzren/opentargets-mcp

Open Targets MCP Server

A Model Context Protocol (MCP) server that exposes the Open Targets Platform GraphQL API as a set of tools for use with Claude Desktop and other MCP-compatible clients.

Features

Core Capabilities

• Target Analysis: Search genes/proteins by Ensembl ID or symbol. Access expression data, genetic constraints, pathways, protein interactions, safety profiles, and mouse phenotypes
• Disease Analysis: Query diseases by EFO ID. Find associated targets, phenotypes (HPO), and research projects
• Drug Discovery: Search drugs by ChEMBL ID. Access safety data, adverse events, indications, and mechanism of action
• Evidence Mining: Explore target-disease associations with scored evidence from multiple sources
• Variant Analysis: Query genetic variants, GWAS credible sets, and pharmacogenomics data
• Study Exploration: Access GWAS studies with L2G predictions and fine-mapped loci
• Smart Search: Entity resolution with synonym handling, autocomplete, and ID mapping

Data Sources

The Open Targets Platform integrates evidence from 22+ primary data sources:

• Genetics: Open Targets Genetics, ClinVar, UK Biobank, FinnGen, Gene2Phenotype, Orphanet, COSMIC
• Functional: CRISPR screens, DepMap, GeneBass
• Drugs: ChEMBL, FDA/EMA approvals, chemical probes
• Expression: GTEx, Human Protein Atlas, Expression Atlas
• Pathways: Reactome, Signor, IntAct
• Literature: Europe PMC text mining
• Safety: FAERS, pharmacogenomics data
• Models: Mouse (MGI, IMPC) phenotypes

Architecture

graph LR
    subgraph "Clients"
        A[Claude Desktop]
        B[Python Scripts]
        C[AI Agents]
    end
    
    subgraph "MCP Server"
        D[Open Targets<br/>MCP Server]
        E[Tool Categories<br/>Target • Disease • Drug<br/>Evidence • Search • Variant • Study]
    end
    
    subgraph "Open Targets"
        F[GraphQL API]
        G[22+ Data Sources]
    end
    
    A <-->|MCP Protocol| D
    B <-->|Direct API| D
    C <-->|Function Calls| D
    D <-->|GraphQL| F
    F <--> G
    
    E --> D
    
    style D fill:#e1f5fe
    style F fill:#fff3e0

The MCP server acts as a bridge between client applications and the Open Targets Platform. It translates tool calls into GraphQL queries and provides structured access to biomedical data from 22+ integrated sources.

Prerequisites

• Python 3.12+ with pip

Quick Start

1. Install UV

UV is a fast Python package and project manager.

pip install uv

2. Install MCPM (MCP Manager)

MCPM is a package manager for MCP servers that simplifies installation and configuration.

pip install mcpm

3. Setup the MCP Server

cd opentargets-mcp
uv sync

4. Add the Server to Claude Desktop

# Make sure you're in the project directory
cd opentargets-mcp

# Set Claude as the target client
mcpm target set @claude-desktop

# Add the OpenTargets MCP server using the Python from uv's environment
mcpm import stdio opentargets \
  --command "$(uv run which python)" \
  --args "-m opentargets_mcp.server"

Then restart Claude Desktop.

Usage

Running the Server Standalone

uv run python -m opentargets_mcp.server

Example Scripts

uv run python examples/target_validation_profile.py EGFR
uv run python examples/disease_to_drug.py "schizophrenia"
uv run python examples/drug_safety_profile.py "osimertinib"
uv run python examples/genetic_target_prioritization.py "inflammatory bowel disease"

AI Agent Example

The ReAct Agent provides an interactive terminal interface for exploring Open Targets data:

# Create .env file with your OpenAI API key
echo "OPENAI_API_KEY=your_key_here" > .env

# Run agent
uv run python examples/react_agent.py

The agent uses a ReAct (Reasoning and Acting) pattern to break down complex biomedical queries into steps, making it easy to explore drug targets, diseases, and their relationships.

Development

# Run tests
uv run pytest tests/ -v