BioMCP is an open source (MIT License) toolkit that empowers AI assistants and agents with specialized biomedical knowledge. Built following the Model Context Protocol (MCP), it connects AI systems to authoritative biomedical data sources, enabling them to answer questions about clinical trials, scientific literature, and genomic variants with precision and depth.

While Large Language Models have broad general knowledge, they often lack specialized domain-specific information or access to up-to-date resources. BioMCP bridges this gap for biomedicine by:

• Providing structured access to clinical trials, biomedical literature, and genomic variants
• Enabling natural language queries to specialized databases without requiring knowledge of their specific syntax
• Supporting biomedical research workflows through a consistent interface
• Functioning as an MCP server for AI assistants and agents

BioMCP integrates with three key biomedical data sources:

• PubTator3/PubMed - Biomedical literature with entity annotations
• ClinicalTrials.gov - Clinical trial registry and results database
• MyVariant.info - Consolidated genetic variant annotation from multiple databases

• article_searcher: Search for articles by genes, diseases, variants, or keywords
• article_details: Get detailed article information including abstracts and full text

• trial_searcher: Advanced trial search with filtering by condition, intervention, phase, etc.
• trial_protocol: Detailed trial protocol information
• trial_locations: Trial site locations and contact information
• trial_outcomes: Results and outcome measures
• trial_references: Related publications

• variant_searcher: Search for genetic variants with sophisticated filtering
• variant_details: Comprehensive annotations from multiple sources (CIViC, ClinVar, COSMIC, dbSNP, etc.)

1. Install uv if you don't have it (recommended):

   # MacOS
   brew install uv
   
   # Windows/Linux
   pip install uv

2. Configure Claude Desktop:

   • Open Claude Desktop settings
   • Navigate to Developer section
   • Click "Edit Config" and add:

   {
     "mcpServers": {
       "biomcp": {
         "command": "uv",
         "args": ["run", "--with", "biomcp-python", "biomcp", "run"]
       }
     }
   }

   • Restart Claude Desktop and start chatting about biomedical topics!

# Using pip
pip install biomcp-python

# Using uv (recommended for faster installation)
uv pip install biomcp-python

# Run directly without installation
uv run --with biomcp-python biomcp trial search --condition "lung cancer"

BioMCP provides a comprehensive CLI for direct database interaction:

# Get help
biomcp --help

# Run the MCP server
biomcp run

# Examples
biomcp article search --gene BRAF --disease Melanoma
biomcp article get 21717063 --full
biomcp trial search --condition "Lung Cancer" --phase PHASE3
biomcp trial get NCT04280705 Protocol
biomcp variant search --gene TP53 --significance pathogenic
biomcp variant get rs113488022

Test your BioMCP setup with the MCP Inspector:

npx @modelcontextprotocol/inspector uv run --with biomcp-python biomcp run

This opens a web interface where you can explore and test all available tools.

OncoMCP extends BioMCP with GenomOncology's enterprise-grade precision oncology platform (POP), providing:

• HIPAA-Compliant Deployment: Secure on-premise options
• Real-Time Trial Matching: Up-to-date status and arm-level matching
• Healthcare Integration: Seamless EHR and data warehouse connectivity
• Curated Knowledge Base: 15,000+ trials and FDA approvals
• Sophisticated Patient Matching: Using integrated clinical and molecular profiles
• Advanced NLP: Structured extraction from unstructured text
• Comprehensive Biomarker Processing: Mutation and rule processing

Learn more: GenomOncology

For comprehensive documentation, visit https://biomcp.org

Looking to see BioMCP in action?

Check out the companion repository: 👉 biomcp-examples

It contains real prompts, AI-generated research briefs, and evaluation runs across different models. Use it to explore capabilities, compare outputs, or benchmark your own setup.

Have a cool example of your own? We’d love for you to contribute! Just fork the repo and submit a PR with your experiment.

This project is licensed under the MIT License.