gwas-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gwas-mcpGet information about the BRCA1 gene"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
๐งฌ GWAS-MCP: Bioinformatics MCP Server
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.
โจ Features
๐ฌ Protein & Gene Lookup
UniProt - Search proteins by name, gene, or ID
Ensembl - Gene information and variant details
NCBI Gene - Comprehensive gene database
๐งช Clinical & Variants
ClinVar - Clinical variant interpretations (pathogenic/benign)
GWAS Catalog - Genome-wide association studies
GTEx - Expression quantitative trait loci (eQTL)
๐ Protein Interactions & Networks
STRING - Protein-protein interactions
InterPro - Protein domains and families
๐๏ธ Structures & Pathways
AlphaFold - AI-predicted protein structures
PDB - Experimental 3D structures
KEGG - Metabolic and signaling pathways
๐ Drug Discovery
Open Targets - Drug target validation & disease associations
PharmGKB - Pharmacogenomics & drug-gene interactions
๐ฅ Genetic Diseases
OMIM - Online Mendelian Inheritance in Man
๐ Quick Start
Installation
pip install gwas-mcpClaude 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.jsonmacOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.config/Claude/claude_desktop_config.json
Restart Claude Desktop
After adding the configuration, restart Claude Desktop to load the MCP server.
๐ ๏ธ Available Tools
Protein & Gene Tools
Tool | Description |
| Search UniProt by protein name, gene, or ID |
| Get detailed protein info (function, domains, GO terms) |
| Search NCBI Gene database |
| Get gene location and details from Ensembl |
| Get SNP/variant info by rsID |
| Get protein domain information |
Clinical & Variant Tools
Tool | Description |
| Search ClinVar for clinical variants |
| Get clinical interpretation for a variant |
| Annotate SNPs with functional consequences |
| Query GWAS Catalog for associations |
| Get eQTL data from GTEx |
Protein Interaction Tools
Tool | Description |
| Find interacting proteins (STRING) |
| Get network between multiple proteins |
| Pathway/GO enrichment analysis |
Structure & Pathway Tools
Tool | Description |
| Get AI-predicted structure |
| Search AlphaFold database |
| Search PDB for 3D structures |
| Get PDB structure details |
| Search KEGG pathways |
| Get pathway genes and details |
| Find pathways for a gene |
Drug Discovery Tools
Tool | Description |
| Find drugs targeting a gene (Open Targets) |
| Get disease associations with scores |
| Search genes, diseases, or drugs |
| Search PharmGKB database |
| Get drug-gene interactions |
Genetic Disease Tools
Tool | Description |
| Search OMIM for genetic diseases |
| Get all diseases for a gene |
๐ฌ 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?"
โก 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
๐ง 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.serverProject Structure
gwas-mcp/
โโโ src/
โ โโโ gwas_mcp/
โ โโโ server.py # Main MCP server
โ โโโ tools/
โ โ โโโ protein_tools.py # UniProt, NCBI, Ensembl
โ โ โโโ clinical_tools.py # ClinVar, STRING
โ โ โโโ structure_tools.py # PDB, KEGG, PharmGKB
โ โ โโโ advanced_tools.py # AlphaFold, Open Targets, OMIM
โ โโโ resources/
โ โโโ db_resources.py # Database resources
โโโ pyproject.toml
โโโ README.md
โโโ LICENSE๐ Supported Databases
Database | Type | Description |
Protein | Protein sequences and annotations | |
Gene/Variant | Genome browser and variant data | |
Gene | Gene information database | |
Clinical | Clinical variant interpretations | |
GWAS | Genome-wide association studies | |
Expression | Expression QTL data | |
Interactions | Protein-protein interactions | |
Domains | Protein families and domains | |
Structure | AI-predicted structures | |
Structure | Experimental 3D structures | |
Pathways | Metabolic and signaling pathways | |
Drug Discovery | Drug targets and disease associations | |
Pharmacogenomics | Drug-gene interactions | |
Diseases | Genetic disease database |
๐ค Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Fork the repository
Create your feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
Model Context Protocol - The MCP specification
Anthropic - Claude AI and MCP development
All the amazing bioinformatics databases that make this possible
๐ฌ Contact
GitHub: @zaeyasa
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