BioMCP

# What is BioMCP? BioMCP is an open-source implementation of the Model Context Protocol (MCP) designed for biomedical research. It connects AI assistants to specialized biomedical databases, enabling natural language access to complex scientific data. [](https://www.youtube.com/watch?v=bKxOWrWUUhM) ## The Bridge to Biomedical Data BioMCP provides AI assistants with direct access to specialized biomedical databases that aren't available through general web search. Built on Anthropic's Model Context Protocol standard, it creates a toolbox that enables natural language queries across multiple scientific data sources. ## Connected Data Sources - **PubMed/PubTator3**: 30M+ research articles with entity recognition for genes, diseases, drugs, and variants - **ClinicalTrials.gov**: 400K+ clinical trials searchable by condition, location, phase, and eligibility - **MyVariant.info**: Comprehensive variant annotations with clinical significance - **cBioPortal**: Cancer genomics data automatically integrated with searches - **BioThings APIs**: Real-time gene, drug, and disease information - **NCI CTS API**: Enhanced cancer trial search with biomarker filtering - **AlphaGenome**: Variant effect predictions using Google DeepMind's AI ## How Does It Transform Research? What makes BioMCP particularly powerful is its conversational nature. A researcher might begin with a simple question about a disease, then naturally progress to exploring related clinical trials, and finally investigate genetic variants that affect treatment efficacy—all within a single, flowing conversation. The system remembers context throughout the interaction, allowing for natural follow-up questions and a research experience that mirrors how scientists actually work. Instead of requiring researchers to master complex query languages for each database, BioMCP translates natural language into the precise syntax each system requires. ## Why This Matters BioMCP represents a significant advancement in making specialized biomedical knowledge accessible. For researchers and clinicians, it means spending less time wrestling with complex database interfaces and more time advancing their work. For the broader field of AI in healthcare, it demonstrates how specialized knowledge domains can be made accessible through conversation. As both AI assistants (synchronous conversation partners) and AI agents ( autonomous systems working toward goals over time) continue to evolve, tools like BioMCP will be essential in connecting these systems to the specialized knowledge they need to deliver meaningful insights in complex domains. By open-sourcing BioMCP, we're inviting the community to build upon this foundation, creating more powerful and accessible tools for biomedical research and ultimately accelerating the pace of scientific discovery.