---name: biomcp-server description: Open source biomedical Model Context Protocol (MCP) toolkit for connecting LLMs to biomedical data sources (PubMed, ClinicalTrials, Genomics). license: MIT metadata: author: LobeHub / GenomOncology source: "https://lobehub.com/mcp/genomoncology-biomcp" version: "1.0.0" compatibility: - system: MCP-compliant Client (Claude Desktop, BioKernel) allowed-tools: - web_fetch keywords: - biomcp - automation - biomedical measurable_outcome: execute task with >95% success rate. ---" # BioMCP Server BioMCP is a standardized Model Context Protocol (MCP) server that provides AI agents with direct, structured access to essential biomedical databases and APIs. It acts as a bridge between the LLM and the vast world of biomedical data. ## When to Use This Skill * **Literature Search**: When you need to search PubMed or PMC for recent papers. * **Entity Normalization**: When you need to map text to gene IDs, disease codes, or chemical IDs (using PubTator3). * **Clinical Data**: To search for active clinical trials. * **Genomic Information**: To look up variant information or gene summaries. ## Core Capabilities 1. **PubMed/PMC Search**: Execute complex queries against the NCBI literature databases. 2. **PubTator3 API**: Annotate biomedical text with normalized entities (Genes, Diseases, Chemicals, Species). 3. **ClinicalTrials.gov**: Search and retrieve clinical trial protocols. 4. **Genomic Variants**: Retrieve information about specific genetic variants. ## Workflow 1. **Connect**: The agent connects to the running BioMCP server. 2. **Call Tool**: The agent selects the appropriate tool (e.g., `search_pubmed`, `annotate_text`). 3. **Process**: The server executes the API call and returns structured JSON. 4. **Response**: The agent uses the data to answer the user's query. ## Example Usage **User**: "Find recent clinical trials for CAR-T therapy in glioblastoma and list the key inclusion criteria." **Agent Action**: 1. Calls `biomcp_search_clinical_trials(query="CAR-T glioblastoma", status="Recruiting")`. 2. Parses the returned trial JSON. 3. Extracts and summarizes the inclusion criteria.