GWAS Bioinformatics MCP Server
Access 30+ bioinformatics tools from 14 databases.
Open source Open in the app JSON README (API)
About
Access 30+ bioinformatics tools from 14 databases.
Details
- Kind
- MCP servers
- Topic
- Government & public data
- Publisher
- zaeyasa
- Origin
- official
- Category
- ferramentas
- Transport
- local
- Version
- 1.0.2
- Stars
- 1
- Forks
- 2
- Last push
- 2026-02-09T22:51:02Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-29 04:01:43
- Updated
- 2026-08-29 04:01:43
- Origin id
io.github.zaeyasa/gwas-mcp
README
# 🧬 GWAS-MCP: Bioinformatics MCP Server
[](https://badge.fury.io/py/gwas-mcp)
[](https://opensource.org/licenses/MIT)
[](https://modelcontextprotocol.io)
<!-- mcp-name: io.github.zaeyasa/gwas-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.
<p align="center">
<img src="https://img.shields.io/badge/Tools-30+-green" alt="30+ Tools">
<img src="https://img.shields.io/badge/Databases-12+-blue" alt="12+ Databases">
<img src="https://img.shields.io/badge/Python-3.10+-blue" alt="Python 3.10+">
</p>
---
## ✨ 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
```bash
pip install gwas-mcp
```
### Claude Desktop Configuration
Add to your `claude_desktop_config.json`:
```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
| Tool | Description |
|------|-------------|
| `search_uniprot` | Search UniProt by protein name, gene, or ID |
| `get_protein_details` | Get detailed protein info (function, domains, GO terms) |
| `search_ncbi_gene` | Search NCBI Gene database |
| `search_ensembl_gene` | Get gene location and details from Ensembl |
| `get_variant_info` | Get SNP/variant info by rsID |
| `get_interpro_domains` | Get protein domain information |
### Clinical & Variant Tools
| Tool | Description |
|------|-------------|
| `search_clinvar` | Search ClinVar for clinical variants |
| `get_clinvar_variant` | Get clinical interpretation for a variant |
| `annotate_snps` | Annotate SNPs with functional consequences |
| `query_gwas_catalog` | Query GWAS Catalog for associations |
| `get_eqtl_data` | Get eQTL data from GTEx |
### Protein Interaction Tools
| Tool | Description |
|------|-------------|
| `get_protein_interactions` | Find interacting proteins (STRING) |
| `get_interaction_network` | Get network between multiple proteins |
| `get_functional_enrichment` | Pathway/GO enrichment analysis |
### Structure & Pathway Tools
| Tool | Description |
|------|-------------|
| `get_alphafold_structure` | Get AI-predicted structure |
| `search_alphafold` | Search AlphaFold database |
| `search_pdb_structures` | Search PDB for 3D structures |
| `get_pdb_structure` | Get PDB structure details |
| `search_kegg_pathway` | Search KEGG pathways |
| `get_kegg_pathway` | Get pathway genes and details |
| `get_gene_pathways` | Find pathways for a gene |
### Drug Discovery Tools
| Tool | Description |
|------|-------------|
| `get_drug_targets` | Find drugs targeting a gene (Open Targets) |
| `get_disease_associations` | Get disease associations with scores |
| `search_open_targets` | Search genes, diseases, or drugs |
| `search_pharmgkb` | Search PharmGKB database |
| `get_drug_gene_interactions` | Get drug-gene interactions |
### Genetic Disease Tools
| Tool | Description |
|------|-------------|
| `search_omim` | Search OMIM for genetic diseases |
| `get_gene_diseases` | Get 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
```bash
# 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
| Database | Type | Description |
|----------|------|-------------|
| [UniProt](https://www.uniprot.org/) | Protein | Protein sequences and annotations |
| [Ensembl](https://www.ensembl.org/) | Gene/Variant | Genome browser and variant data |
| [NCBI Gene](https://www.ncbi.nlm.nih.gov/gene/) | Gene | Gene information database |
| [ClinVar](https://www.ncbi.nlm.nih.gov/clinvar/) | Clinical | Clinical variant interpretations |
| [GWAS Catalog](https://www.ebi.ac.uk/gwas/) | GWAS | Genome-wide association studies |
| [GTEx](https://gtexportal.org/) | Expression | Expression QTL data |
| [STRING](https://string-db.org/) | Interactions | Protein-protein interactions |
| [InterPro](https://www.ebi.ac.uk/interpro/) | Domains | Protein families and domains |
| [AlphaFold](https://alphafold.ebi.ac.uk/) | Structure | AI-predicted structures |
| [PDB](https://www.rcsb.org/) | Structure | Experimental 3D structures |
| [KEGG](https://www.kegg.jp/) | Pathways | Metabolic and signaling pathways |
| [Open Targets](https://platform.opentargets.org/) | Drug Discovery | Drug targets and disease associations |
| [PharmGKB](https://www.pharmgkb.org/) | Pharmacogenomics | Drug-gene interactions |
| [OMIM](https://omim.org/) | Diseases | Genetic 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](LICENSE) file for details.
---
## 🙏 Acknowledgments
- [Model Context Protocol](https://modelcontextprotocol.io/) - The MCP specification
- [Anthropic](https://www.anthropic.com/) - Claude AI and MCP development
- All the amazing bioinformatics databases that make this possible
---
## 📬 Contact
- GitHub: [@zaeyasa](https://github.com/zaeyasa)
---
<p align="center">Made with ❤️ for the bioinformatics community</p>