medical-mcps

Biological APIs MCP Server

MCP server that integrates multiple biological and medical databases for research purposes.

Quick Start

Connect to Production Server

The easiest way to use this MCP server is to connect to the production deployment. All APIs are available through a unified endpoint that gives you access to all tools in one place.

Production URL: https://mcp.cloud.curiloo.com/tools/unified/mcp

Configure in Cursor (or other MCP client)

Add this to your .cursor/mcp.json (or equivalent MCP client configuration):

{
    "mcpServers": {
        "medical-apis": {
            "url": "https://mcp.cloud.curiloo.com/tools/unified/mcp"
        }
    }
}

What You Get

Once connected, you'll have access to 100+ tools across 14 biological and medical APIs:

• Pathways: Reactome, KEGG, Pathway Commons
• Genes & Proteins: UniProt, MyGene.info, Node Normalization
• Targets & Associations: OpenTargets Platform
• Variants: MyVariant.info, GWAS Catalog
• Diseases: OMIM, MyDisease.info
• Drugs: ChEMBL, MyChem.info, OpenFDA
• Literature: PubMed/PubTator3
• Trials: ClinicalTrials.gov, NCI Clinical Trials
• Knowledge Graphs: Every Cure Matrix Knowledge Graph

Example: Search for a Gene

{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
        "name": "mygene_get_gene",
        "arguments": {
            "gene_id_or_symbol": "TP53"
        }
    }
}

Individual API Endpoints

If you prefer to use individual APIs separately, each API has its own endpoint:

• /tools/reactome/mcp - Reactome only
• /tools/pubmed/mcp - PubMed only
• /tools/chembl/mcp - ChEMBL only
• ... (see Available Endpoints for full list)

Local Development

To run your own instance locally, you can either:

• Use Docker Compose (recommended for quick setup) - see Docker Compose Setup
• Run directly with Python/uv - see Running the Server below

APIs Integrated

✅ Implemented APIs

• Reactome API - Pathway information, gene/protein queries, disease associations
• KEGG API - Pathway maps, gene annotations, disease and drug information
• UniProt API - Protein sequences, functional annotations, disease associations
• OMIM API - Genetic disease information, gene-disease associations (requires API key)
• GWAS Catalog API - Genetic associations, variant information, study metadata
• Pathway Commons API - Integrated pathway data, pathway interactions, gene/protein networks
• Node Normalization API - CURIE normalization, identifier mapping across databases
• ChEMBL API - Drug-target interactions, bioactivity data, mechanisms of action, drug indications
• ClinicalTrials.gov API - Clinical trial search, study metadata, trial status
• PubMed/PubTator3 API - Biomedical literature search, article retrieval, preprint search
• OpenFDA API - FDA adverse event reports, drug labels, device events, drug approvals
• OpenTargets Platform API - Target/disease search, associations, evidence
• MyVariant.info API - Genetic variant annotations, population frequencies, clinical significance
• BioThings Suite APIs - MyGene.info (gene annotations), MyDisease.info (disease information), MyChem.info (drug/chemical data)
• NCI Clinical Trials API - Cancer clinical trial search and metadata (requires API key)

Installation

Option 1: Install from PyPI

Install the package from PyPI:

pip install medical-mcps

Then run the server:

medical-mcps

The server will be available at http://localhost:8000.

Option 2: Run with Docker

Pull and run the pre-built Docker image:

# Pull latest image
docker pull pascalwhoop/medical-mcps:latest

# Run server
docker run -p 8000:8000 pascalwhoop/medical-mcps:latest

The server will be available at http://localhost:8000.

For specific versions:

docker pull pascalwhoop/medical-mcps:v0.1.0

Option 3: Docker Compose (Recommended for Development)

The easiest way to run the MCP backend:

# Start all services with auto-rebuild
make docker-watch

# Or start in background
make docker-up

# View logs
make docker-logs

# Stop services
make docker-down

Services will be available at:

• MCP Backend: http://localhost:8000