EMBL-EBI Protein MCP Server

⚠️ UNDER CONSTRUCTION ⚠️

This project is currently under active development. While the core functionality is operational, please be aware that:

• No guarantee is provided that the software is bug-free
• Breaking changes may occur without notice
• Some features may be incomplete or experimental
• Use at your own risk in production environments

Feedback and contributions are welcome as we work to improve the server!

A Model Context Protocol (MCP) server providing access to the EMBL-EBI Protein database. This server enables LLMs and other MCP clients to search, retrieve, and analyze protein data from UniProt and related databases.

Quick Start

Installation

Requirements: Python 3.10+ (due to MCP library requirements)

# Create virtual environment with Python 3.10+
python3.11 -m venv venv  
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install the package
pip install -e .

Running the MCP Server

# Start the MCP server
embl_ebi_protein_mcp

The server runs on stdio and is ready to accept MCP protocol requests.

Features

New Enhanced Tools (Recommended)

• get_protein_summary - One-stop comprehensive protein lookup (BEST STARTING POINT)
• find_protein_accession - Easy protein ID lookup for common names

Core Protein Tools

• search_proteins - Search UniProt protein database by text query
• get_protein_by_accession - Get detailed protein information by UniProt accession
• get_protein_interactions - Get known protein-protein interactions
• get_protein_isoforms - Get alternative protein isoforms (splice variants)

Protein Features & Analysis

• search_features - Search for specific protein sequence features
• get_features_by_accession - Get all sequence features for a protein
• get_features_by_type - Get features by specific type (domains, sites, etc.)
• search_variations - Search natural variants in proteins
• get_variations_by_accession - Get variations by UniProt accession

Taxonomy & Classification

• get_taxonomy_by_id - Get taxonomic information by NCBI taxonomy ID
• get_taxonomy_lineage - Get complete taxonomic lineage
• get_taxonomy_children - Get taxonomy children by ID

Advanced Analysis

• search_proteomes - Search proteomes
• get_proteome_by_upid - Get proteome by UniProt Proteome ID
• search_coordinates - Search genomic coordinates
• search_uniparc - Search UniParc entries

Total: 30 tools available

Usage Examples

For LLMs (via MCP client)

// Find human p53 protein - comprehensive overview
{
  "method": "tools/call",
  "params": {
    "name": "get_protein_summary",
    "arguments": {
      "gene_name": "p53",
      "organism": "human"
    }
  }
}

// Find insulin in mouse
{
  "method": "tools/call", 
  "params": {
    "name": "find_protein_accession",
    "arguments": {
      "gene_name": "insulin",
      "organism": "mouse"
    }
  }
}

Python API Usage

import asyncio
from embl_ebi_protein_mcp.bridge import EMBLEBIBridge

async def example():
    async with EMBLEBIBridge() as bridge:
        # Find protein accession
        result = await bridge.find_protein_accession("p53", "human")
        print(f"Found: {result[0]['accession']}")
        
        # Get comprehensive summary
        summary = await bridge.get_protein_summary("insulin", "human")
        print(f"Insulin accession: {summary['accession']}")

asyncio.run(example())

Supported Organisms

The server includes convenient organism name mapping:

Common Name	Taxonomy ID	Example Usage
human	9606	"organism": "human"
mouse	10090	"organism": "mouse"
rat	10116	"organism": "rat"
yeast	559292	"organism": "yeast"
e.coli	83333	"organism": "e.coli"
drosophila	7227	"organism": "drosophila"

MCP Client Configuration

Claude Desktop

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "embl-ebi-proteins": {
      "command": "embl_ebi_protein_mcp",
      "env": {}
    }
  }
}

Other MCP Clients

The server follows the standard MCP protocol and should work with any MCP-compatible client.

Testing

The project uses pytest for comprehensive testing with unit tests, integration tests, and code coverage.

Quick Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=embl_ebi_protein_mcp

# Run only unit tests (fast)
pytest -m unit

# Run only integration tests
pytest -m integration

Using Test Scripts

# Run comprehensive test suite with coverage
./scripts/test.sh

# Run code quality checks (black, flake8, mypy)
./scripts/lint.sh

Test Categories

• Unit tests (-m unit): Fast tests with mocked dependencies
• Integration tests (-m integration): Tests with mocked API calls
• Slow tests (-m slow): Comprehensive workflow tests

Debug Mode

# Run with debug logging
DEBUG=1 embl_ebi_protein_mcp

API Endpoints Used

This server accesses the following EMBL-EBI REST API endpoints:

• Proteins: https://www.ebi.ac.uk/proteins/api/proteins
• Features: https://www.ebi.ac.uk/proteins/api/features
• Variations: https://www.ebi.ac.uk/proteins/api/variation
• Taxonomy: https://www.ebi.ac.uk/proteins/api/taxonomy
• Proteomes: https://www.ebi.ac.uk/proteins/api/proteomes
• Coordinates: https://www.ebi.ac.uk/proteins/api/coordinates
• UniParc: https://www.ebi.ac.uk/proteins/api/uniparc

Development

Project Structure

EMBL-EBI-Protein-mcp/
├── embl_ebi_protein_mcp/
│   ├── __init__.py
│   ├── bridge.py          # API bridge to EMBL-EBI
│   ├── mcp_server.py      # MCP server implementation
│   ├── cli.py             # Command-line interface
│   └── main.py            # Main entry point
├── test_api.py            # API functionality tests
├── test_enhancements.py   # Enhanced features tests
├── ENHANCEMENTS.md        # Enhancement documentation
└── pyproject.toml         # Package configuration

Development Setup

# Install with development dependencies
pip install -e .[dev]

# Run tests
pytest

# Run code quality checks
./scripts/lint.sh

# Format code
black embl_ebi_protein_mcp/ tests/

# Type checking
mypy embl_ebi_protein_mcp/

Recent Enhancements

• Added get_protein_summary for comprehensive protein lookup
• Added find_protein_accession for easy ID lookup
• Enhanced all tool descriptions with usage guidance and examples
• Added organism name mapping for better usability
• Improved error handling and fallback strategies
• Added clear workflow guidance for LLMs

See ENHANCEMENTS.md for detailed information.

Known Limitations

• Some proteins may not have complete data in all endpoints
• Large result sets may be truncated or timeout
• The API requires specific UniProt accession formats for some endpoints
• Rate limiting may apply for high-volume usage

License

MIT License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create a 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

Support

• Issues: Use the GitHub issue tracker
• Questions: Open a discussion on GitHub
• API Documentation: EMBL-EBI Proteins API

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Note: This is an unofficial implementation and is not affiliated with EMBL-EBI. All data is accessed through their public REST API.