BioPython MCP Server

A Model Context Protocol (MCP) server that provides comprehensive BioPython capabilities for biological sequence analysis, alignment, database access, and structural bioinformatics.

Overview

BioPython MCP bridges the powerful BioPython library with MCP-enabled applications like Claude Desktop, allowing seamless integration of bioinformatics tools into AI-assisted workflows. This enables researchers, clinicians, and developers to perform complex biological analyses through natural language interfaces.

Motivation

Bioinformatics workflows often require switching between multiple tools and writing custom scripts. BioPython MCP simplifies this by:

• Unified Interface: Access BioPython's capabilities through a standardized MCP protocol

• AI Integration: Combine computational biology with AI-powered analysis and interpretation

• Workflow Automation: Chain complex bioinformatics tasks through conversational interfaces

• Accessibility: Make advanced bioinformatics tools available to non-programmers

Features

• Sequence Operations

  • DNA/RNA translation and transcription

  • Reverse complement calculation

  • GC content analysis

  • Motif finding and pattern matching

• Sequence Alignment

  • Pairwise global and local alignment

  • Multiple sequence alignment support

  • Alignment scoring with substitution matrices

• Database Access

  • GenBank sequence retrieval

  • UniProt protein data access

  • PubMed literature search

  • NCBI database queries

• Protein Structure Analysis

  • PDB structure fetching and parsing

  • Structure statistics calculation

  • Active site residue analysis

• Phylogenetics

  • Phylogenetic tree construction (NJ, UPGMA)

  • Distance matrix calculation

  • Tree visualization

Installation

Requirements

• Python 3.10 or higher

• pip or uv package manager

Quick Install with uvx (Recommended)

The fastest way to run BioPython MCP without installation:

Or run from source:

Install from PyPI

Install from Source with uv

Install from Source with pip

Development Installation

For contributing or development:

Quick Start

Running the Server

Start the MCP server:

Configuration for Claude Desktop

Add to your Claude Desktop configuration file:

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

Using uvx (recommended):

Using installed package:

Using local development version:

Basic Usage Example

Once configured, you can use BioPython tools through Claude Desktop:

Available Tools

Sequence Operations

Alignment

Database Access

Structure Analysis

Phylogenetics

See the Tools Reference for detailed documentation.

Configuration Options

Environment Variables

• NCBI_EMAIL: Email address for NCBI Entrez queries (recommended)

• NCBI_API_KEY: API key for higher NCBI rate limits (optional)

• OBSIDIAN_VAULT_PATH: Path to your Obsidian vault root directory (optional, for pubmed_review)

  • When set, the LLM will determine the directory path and filename for saving literature reviews

  • Can be overridden per-call with the obsidian_vault parameter

Setting Environment Variables

Examples

Analyze a Gene Sequence

Compare Sequences

Build Phylogenetic Tree

See examples/ for complete workflow examples.

Documentation

• Getting Started Guide

• Tools Reference

• Usage Examples

• API Documentation

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

1. Fork the repository

2. Clone your fork: git clone https://github.com/yourusername/biopython-mcp.git

3. Install development dependencies: pip install -e ".[dev]"

4. Install pre-commit hooks: pre-commit install

5. Create a feature branch: git checkout -b feature-name

6. Make your changes and commit

7. Run tests: pytest

8. Push and create a pull request

Code Quality

We use:

• Black for code formatting

• Ruff for linting

• mypy for type checking

• pytest for testing

• pre-commit for automated checks

Testing

Run tests:

Run tests with coverage:

Generate coverage reports (HTML and XML):

View HTML coverage report:

Run type checking:

CI/CD Coverage

The project uses GitHub Actions for continuous integration with automatic coverage reporting to Codecov.

Coverage is automatically uploaded when:

• Tests run on Ubuntu with Python 3.11

• Pull requests are created or updated

• Commits are pushed to main or develop branches

Note for Contributors: Coverage reports are publicly available. The CI workflow uses the CODECOV_TOKEN secret for authenticated uploads. Repository maintainers should configure this secret in GitHub repository settings.

License

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

Citation

If you use BioPython MCP in your research, please cite:

Acknowledgments

• Built on the excellent BioPython library

• Uses FastMCP for MCP implementation

• Inspired by the Model Context Protocol

Support

• Issues: GitHub Issues

• Discussions: GitHub Discussions

• Email: Contact maintainers

Roadmap

• Add support for protein secondary structure prediction

• Implement BLAST search integration

• Add sequence feature annotation tools

• Support for custom HMM profiles

• Interactive structure visualization

• Batch processing capabilities

• REST API wrapper

Related Projects

• BioPython - The core library

• Model Context Protocol - The MCP specification

• FastMCP - MCP framework for Python

Made with BioPython and MCP