README.md•6.95 kB
# AlphaGenome MCP Server
[](https://www.npmjs.com/package/@jolab/alphagenome-mcp)
[](https://opensource.org/licenses/MIT)
An MCP server that provides natural language access to Google DeepMind's AlphaGenome for regulatory genomics analysis and variant effect prediction.
## Features
- **Variant Effect Prediction**: Analyze regulatory impacts of genetic variants across 11 molecular modalities (RNA-seq, ChIP-seq, ATAC-seq, splicing, etc.)
- **Regulatory Element Discovery**: Identify promoters, enhancers, and transcription factor binding sites in genomic regions
- **Batch Variant Scoring**: Prioritize multiple variants by regulatory impact for GWAS and sequencing studies
- **Natural Language Interface**: Query variants using rsIDs or genomic coordinates without coding
- **Multi-Modal Analysis**: Unified predictions for gene expression, chromatin accessibility, TF binding, and 3D chromatin structure
## Tools
### predict_variant_effect
Predicts the regulatory impact of a single genetic variant.
**Inputs:**
- `chromosome` (string): Chromosome name (chr1-chr22, chrX, chrY)
- `position` (number): Genomic position (1-based)
- `ref` (string): Reference allele (A/T/G/C)
- `alt` (string): Alternate allele (A/T/G/C)
- `tissue_type` (string, optional): Tissue context (UBERON term, e.g., "UBERON:0000955" for brain)
- `output_types` (array, optional): Specific modalities to analyze
**Example:**
```
"Analyze the regulatory impact of chr19:44908684T>C in brain tissue"
```
### analyze_region
Identifies regulatory elements in a genomic region.
**Inputs:**
- `chromosome` (string): Chromosome name
- `start` (number): Start position (1-based)
- `end` (number): End position
- `analysis_types` (array, optional): Element types to find (promoter, enhancer, etc.)
- `resolution` (string, optional): "base" (1bp) or "window" (128bp)
**Example:**
```
"Find enhancers in chr11:5225464-5227071"
```
### batch_score_variants
Scores and ranks multiple variants by regulatory impact.
**Inputs:**
- `variants` (array): List of variants with chr, pos, ref, alt
- `scoring_metric` (string): Metric for ranking (rna_seq, splice, regulatory_impact, combined)
- `top_n` (number, optional): Number of top variants to return
- `include_interpretation` (boolean, optional): Include clinical interpretation
**Example:**
```
"Score these variants by splicing impact: chr7:117199563C>T, chr2:127892810G>A"
```
## Installation
### Requirements
- Node.js ≥18.0.0
- Python ≥3.8 with `alphagenome` and `numpy`
- AlphaGenome API key ([request here](https://deepmind.google/discover/blog/alphagenome/))
### Quick Start
```bash
# Install Python dependencies
pip install alphagenome numpy
# Add to Claude Desktop
claude mcp add alphagenome -- npx -y @jolab/alphagenome-mcp@latest --api-key YOUR_API_KEY
```
## Configuration
### Usage with Claude Desktop
Add to your `claude_desktop_config.json`:
```json
{
"mcpServers": {
"alphagenome": {
"command": "npx",
"args": ["-y", "@jolab/alphagenome-mcp@latest"],
"env": {
"ALPHAGENOME_API_KEY": "your-api-key-here"
}
}
}
}
```
Or use command-line argument:
```json
{
"mcpServers": {
"alphagenome": {
"command": "npx",
"args": [
"-y",
"@jolab/alphagenome-mcp@latest",
"--api-key",
"your-api-key-here"
]
}
}
}
```
### Verification
Test the installation:
```
"Analyze chr19:44908684T>C with AlphaGenome"
```
Expected: Detailed regulatory impact report within 30-60 seconds.
## Usage Examples
### Basic Analysis
**Single Variant:**
```
"What is the regulatory impact of rs429358?"
```
**Specific Tissue:**
```
"Analyze chr6:41129252C>T in brain tissue"
```
**Custom Modalities:**
```
"Show only RNA-seq and splicing effects for chr2:127892810G>A"
```
### Advanced Queries
**Region Exploration:**
```
"Find all regulatory elements in the APOE gene region"
```
**Variant Prioritization:**
```
"Rank these 10 variants by their impact on gene expression"
```
**Cross-Tissue Comparison:**
```
"Compare the effect of this variant in brain vs liver"
```
**Mechanistic Investigation:**
```
"Which transcription factors are affected by rs744373?"
```
## Use Cases
- **Post-GWAS Analysis**: Prioritize GWAS hits by functional impact
- **Clinical Interpretation**: Assess pathogenicity of VUS (variants of uncertain significance)
- **Drug Target Discovery**: Identify regulatory variants affecting target genes
- **Synthetic Biology**: Design tissue-specific regulatory elements
- **Evolutionary Genomics**: Analyze regulatory changes across species
## Development
### Build from Source
```bash
git clone https://github.com/taehojo/alphagenome-mcp.git
cd alphagenome-mcp
npm install
pip install -r requirements.txt
npm run build
```
### Project Structure
```
src/
├── index.ts # MCP server
├── alphagenome-client.ts # API client
├── tools.ts # Tool definitions
└── utils/ # Validation & formatting
scripts/
└── alphagenome_bridge.py # Python bridge
```
### Testing
```bash
npm run lint
npm run typecheck
npm run build
```
## Architecture
```
Claude Desktop → MCP Server (TypeScript) → Python Bridge → AlphaGenome API
```
The server uses a Python subprocess bridge to interface with AlphaGenome's Python-only SDK.
## Performance
- **First call**: 30-60 seconds (initialization)
- **Subsequent calls**: 5-15 seconds
- **Recommended**: <1000 variants per session
- **Modalities**: 11 (RNA-seq, CAGE, PRO-cap, splice sites, DNase, ATAC, histone mods, TF binding, contact maps)
- **Resolution**: Single base-pair for most modalities
## Limitations
- Requires active internet and API access
- InDels and structural variants not fully supported
- Accuracy decreases for regulatory elements >100kb from TSS
- Human and mouse genomes only
- Research use only (not validated for clinical diagnostics)
## Citation
```bibtex
@software{jo2025alphagenome_mcp,
author = {Jo, Taeho},
title = {AlphaGenome MCP Server},
year = {2025},
url = {https://github.com/taehojo/alphagenome-mcp},
version = {0.1.5}
}
```
AlphaGenome:
```bibtex
@article{avsec2025alphagenome,
title = {AlphaGenome: Unified prediction of variant effects},
author = {Avsec, Žiga and Latysheva, Natasha and Cheng, Jun and others},
journal = {bioRxiv},
year = {2025},
doi = {10.1101/2025.06.27.600757}
}
```
## License
MIT License - Copyright (c) 2025 Taeho Jo
## Links
- **npm**: https://www.npmjs.com/package/@jolab/alphagenome-mcp
- **GitHub**: https://github.com/taehojo/alphagenome-mcp
- **Issues**: https://github.com/taehojo/alphagenome-mcp/issues
- **AlphaGenome**: https://deepmind.google/discover/blog/alphagenome/
- **Model Context Protocol**: https://modelcontextprotocol.io/