Which integrations are available for this server?

Enables searching [PubMed](/mcp/servers/integrations/pubmed) literature and retrieving biological research articles through NCBI's PubMed database. The BioPython MCP server is distributed through [PyPI](/mcp/servers/integrations/pypi) for installation via pip.

BioPython MCP Server

Python 3.10+ License: MIT Code style: black

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:

uvx biopython-mcp

Or run from source:

git clone https://github.com/kmaneesh/biopython-mcp.git cd biopython-mcp uvx --from . biopython-mcp

Install from PyPI

pip install biopython-mcp

Install from Source with uv

git clone https://github.com/kmaneesh/biopython-mcp.git cd biopython-mcp uv venv --python 3.10 source .venv/bin/activate # On Windows: .venv\Scripts\activate uv pip install -e ".[dev]"

Install from Source with pip

git clone https://github.com/kmaneesh/biopython-mcp.git cd biopython-mcp pip install -e ".[dev]"

Development Installation

For contributing or development:

git clone https://github.com/kmaneesh/biopython-mcp.git cd biopython-mcp uv venv --python 3.10 source .venv/bin/activate uv pip install -e ".[dev]" pre-commit install

Quick Start

Running the Server

Start the MCP server:

# With uvx (no installation needed) uvx biopython-mcp # Or if installed biopython-mcp

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):

{ "mcpServers": { "biopython": { "command": "uvx", "args": ["biopython-mcp"] } } }

Using installed package:

{ "mcpServers": { "biopython": { "command": "biopython-mcp" } } }

Using local development version:

{ "mcpServers": { "biopython": { "command": "uvx", "args": ["--from", "/path/to/biopython-mcp", "biopython-mcp"] } } }

Basic Usage Example

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

User: Translate the DNA sequence ATGGCCATTGTAATGGGCCGC to protein Claude: [Uses translate_sequence tool] Result: MAIVMGR (7 amino acids) User: What's the GC content of this sequence? Claude: [Uses calculate_gc_content tool] Result: 57.14% GC content

Available Tools

Sequence Operations

Tool	Description
`translate_sequence`	Translate DNA/RNA to protein
`reverse_complement`	Get reverse complement of DNA
`transcribe_dna`	Transcribe DNA to RNA
`calculate_gc_content`	Calculate GC percentage
`find_motif`	Find sequence motifs

Alignment

Tool	Description
`pairwise_align`	Align two sequences
`multiple_sequence_alignment`	Align multiple sequences
`calculate_alignment_score`	Score alignments

Database Access

Tool	Description
`fetch_genbank`	Retrieve GenBank records
`fetch_uniprot`	Retrieve UniProt entries
`search_pubmed`	Search PubMed literature
`fetch_sequence_by_id`	Get sequences by ID

Structure Analysis

Tool	Description
`fetch_pdb_structure`	Download PDB structures
`calculate_structure_stats`	Analyze structure statistics
`find_active_site`	Extract active site info

Phylogenetics

Tool	Description
`build_phylogenetic_tree`	Build phylogenetic trees
`calculate_distance_matrix`	Compute distance matrices
`draw_tree`	Visualize trees

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)

Setting Environment Variables

export NCBI_EMAIL="your.email@example.com" export NCBI_API_KEY="your_api_key_here"

Examples

Analyze a Gene Sequence

# 1. Fetch from GenBank fetch_genbank(accession="NM_000207", email="user@example.com") # 2. Calculate GC content calculate_gc_content(sequence="ATGGCC...") # 3. Translate to protein translate_sequence(sequence="ATGGCC...") # 4. Find start codons find_motif(sequence="ATGGCC...", motif="ATG")

Compare Sequences

# Perform global alignment pairwise_align( seq1="ATGGCCATTGTAATGGGCCGC", seq2="ATGGCCATTGTTATGGGCCGC", mode="global" )

Build Phylogenetic Tree

# Build tree from aligned sequences build_phylogenetic_tree( sequences=["ATGGCC...", "ATGGCT...", "ATGGCA..."], method="nj", labels=["Species_A", "Species_B", "Species_C"] )

See examples/ for complete workflow examples.

Documentation

Contributing

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

Development Setup

Fork the repository
Clone your fork: git clone https://github.com/yourusername/biopython-mcp.git
Install development dependencies: pip install -e ".[dev]"
Install pre-commit hooks: pre-commit install
Create a feature branch: git checkout -b feature-name
Make your changes and commit
Run tests: pytest
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:

pytest

Run tests with coverage:

pytest --cov=src --cov-report=term-missing

Run type checking:

mypy src/

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:

@software{biopython_mcp, title = {BioPython MCP: Model Context Protocol Server for BioPython}, author = {BioPython MCP Contributors}, year = {2026}, url = {https://github.com/kmaneesh/biopython-mcp} }

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

BioPython - The core library
Model Context Protocol - The MCP specification
FastMCP - MCP framework for Python

Made with BioPython and MCP