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GWAS Bioinformatics MCP Server

Access 30+ bioinformatics tools from 14 databases.

Updated
Feb 9, 2026

Quick Install

uvx gwas-mcp

🧬 GWAS-MCP: Bioinformatics MCP Server

PyPI version License: MIT MCP

A powerful Model Context Protocol (MCP) server for GWAS and bioinformatics research. Seamlessly integrates with Claude Desktop and other MCP clients to provide AI-powered access to major biological databases.

30+ Tools 12+ Databases Python 3.10+


✨ Features

🔬 Protein & Gene Lookup

  • UniProt - Search proteins by name, gene, or ID
  • Ensembl - Gene information and variant details
  • NCBI Gene - Comprehensive gene database

🧪 Clinical & Variants

  • ClinVar - Clinical variant interpretations (pathogenic/benign)
  • GWAS Catalog - Genome-wide association studies
  • GTEx - Expression quantitative trait loci (eQTL)

🔗 Protein Interactions & Networks

  • STRING - Protein-protein interactions
  • InterPro - Protein domains and families

🏗️ Structures & Pathways

  • AlphaFold - AI-predicted protein structures
  • PDB - Experimental 3D structures
  • KEGG - Metabolic and signaling pathways

💊 Drug Discovery

  • Open Targets - Drug target validation & disease associations
  • PharmGKB - Pharmacogenomics & drug-gene interactions

🏥 Genetic Diseases

  • OMIM - Online Mendelian Inheritance in Man

🚀 Quick Start

Installation

pip install gwas-mcp

Claude Desktop Configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "gwas-bioinformatics": {
      "command": "python",
      "args": ["-m", "gwas_mcp.server"]
    }
  }
}

Config file location:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

Restart Claude Desktop

After adding the configuration, restart Claude Desktop to load the MCP server.


🛠️ Available Tools

Protein & Gene Tools

ToolDescription
search_uniprotSearch UniProt by protein name, gene, or ID
get_protein_detailsGet detailed protein info (function, domains, GO terms)
search_ncbi_geneSearch NCBI Gene database
search_ensembl_geneGet gene location and details from Ensembl
get_variant_infoGet SNP/variant info by rsID
get_interpro_domainsGet protein domain information

Clinical & Variant Tools

ToolDescription
search_clinvarSearch ClinVar for clinical variants
get_clinvar_variantGet clinical interpretation for a variant
annotate_snpsAnnotate SNPs with functional consequences
query_gwas_catalogQuery GWAS Catalog for associations
get_eqtl_dataGet eQTL data from GTEx

Protein Interaction Tools

ToolDescription
get_protein_interactionsFind interacting proteins (STRING)
get_interaction_networkGet network between multiple proteins
get_functional_enrichmentPathway/GO enrichment analysis

Structure & Pathway Tools

ToolDescription
get_alphafold_structureGet AI-predicted structure
search_alphafoldSearch AlphaFold database
search_pdb_structuresSearch PDB for 3D structures
get_pdb_structureGet PDB structure details
search_kegg_pathwaySearch KEGG pathways
get_kegg_pathwayGet pathway genes and details
get_gene_pathwaysFind pathways for a gene

Drug Discovery Tools

ToolDescription
get_drug_targetsFind drugs targeting a gene (Open Targets)
get_disease_associationsGet disease associations with scores
search_open_targetsSearch genes, diseases, or drugs
search_pharmgkbSearch PharmGKB database
get_drug_gene_interactionsGet drug-gene interactions

Genetic Disease Tools

ToolDescription
search_omimSearch OMIM for genetic diseases
get_gene_diseasesGet all diseases for a gene

💬 Example Prompts

Once configured, ask Claude naturally:

Protein & Gene Queries

"Get information about the BRCA1 gene"

"Search UniProt for hemoglobin"

"What protein has UniProt ID P53_HUMAN?"

Clinical Variants

"Is the BRCA1 variant rs80357906 pathogenic?"

"Search ClinVar for TP53 variants"

Protein Interactions

"What proteins interact with TP53?"

"Find functional enrichment for BRCA1, ATM, and CHEK2"

Structures & Pathways

"Get the AlphaFold structure for TP53"

"What pathways is BRCA1 involved in?"

"Search PDB for insulin structures"

Drug Discovery

"What drugs target EGFR?"

"What diseases is BRAF associated with?"

Genetic Diseases

"Search OMIM for cystic fibrosis"

"What diseases are linked to the CFTR gene?"


⚡ Performance Features

  • Smart Caching - API responses cached for 1 hour to improve speed
  • Async Operations - All API calls are non-blocking
  • Error Handling - Graceful handling of API failures

🔧 Development

From Source

# Clone the repository
git clone https://github.com/zaeyasa/gwas-mcp.git
cd gwas-mcp

# Install dependencies
pip install -e .

# Run the server
python -m gwas_mcp.server

Project Structure

gwas-mcp/
├── src/
│   └── gwas_mcp/
│       ├── server.py           # Main MCP server
│       ├── tools/
│       │   ├── protein_tools.py     # UniProt, NCBI, Ensembl
│       │   ├── clinical_tools.py    # ClinVar, STRING
│       │   ├── structure_tools.py   # PDB, KEGG, PharmGKB
│       │   └── advanced_tools.py    # AlphaFold, Open Targets, OMIM
│       └── resources/
│           └── db_resources.py      # Database resources
├── pyproject.toml
├── README.md
└── LICENSE

📊 Supported Databases

DatabaseTypeDescription
UniProtProteinProtein sequences and annotations
EnsemblGene/VariantGenome browser and variant data
NCBI GeneGeneGene information database
ClinVarClinicalClinical variant interpretations
GWAS CatalogGWASGenome-wide association studies
GTExExpressionExpression QTL data
STRINGInteractionsProtein-protein interactions
InterProDomainsProtein families and domains
AlphaFoldStructureAI-predicted structures
PDBStructureExperimental 3D structures
KEGGPathwaysMetabolic and signaling pathways
Open TargetsDrug DiscoveryDrug targets and disease associations
PharmGKBPharmacogenomicsDrug-gene interactions
OMIMDiseasesGenetic disease database

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.


🙏 Acknowledgments

  • Model Context Protocol - The MCP specification
  • Anthropic - Claude AI and MCP development
  • All the amazing bioinformatics databases that make this possible

📬 Contact


Made with ❤️ for the bioinformatics community

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