Biothings MCP Server

The biothings‑mcp server turns the rich, curated datasets of BioThings into a first‑class resource for AI assistants. By exposing Gene, Variant, Chemical, Taxon and Download tools through the Model Context Protocol (MCP), it removes the friction that typically surrounds biomedical data access. Developers can now embed precise, type‑safe queries directly into conversational agents, enabling those assistants to retrieve authoritative annotations, perform sequence downloads, or even run alignment analyses without leaving the chat interface.

At its core, MCP provides a structured bridge between AI language models and domain knowledge. Instead of relying on ad‑hoc REST calls or parsing unstructured text, the server presents a clean API surface where each tool maps to a specific BioThings client. For example, the handler wraps , allowing a user to ask an assistant for gene symbols, synonyms or functional annotations and receive a strongly typed JSON response. This type safety is crucial for downstream processing, ensuring that the assistant’s output can be programmatically validated and consumed by other services.

The server’s download capabilities are particularly valuable for research workflows that require raw data files. Through , users can fetch NCBI Entrez records in formats such as FASTA, GenBank, or JSON and have them automatically stored in a designated output directory. The system handles file naming conflicts by prefixing UUIDs, and it supports custom directories via a simple flag. This feature lets developers build end‑to‑end pipelines where an AI assistant not only queries a database but also hands the resulting data to downstream bioinformatics tools.

Real‑world use cases abound: a clinical decision support assistant can pull variant pathogenicity scores on demand; a drug discovery chatbot can fetch chemical properties and ADMET data; a genomics education tool can retrieve gene function annotations while simultaneously downloading reference sequences for local analysis. In each scenario, the MCP server reduces boilerplate code, guarantees consistency with BioThings’ authoritative sources, and keeps data handling secure and reproducible.

Because MCP is designed for interoperability, the biothings‑mcp server can be deployed behind any AI workflow—whether it’s a Claude agent, a LangChain pipeline, or a custom LLM orchestration platform. Its lightweight Python implementation, coupled with the library, ensures minimal overhead while delivering a rich set of biomedical capabilities. For developers looking to embed deep domain knowledge into conversational AI, this server provides a turnkey, type‑safe solution that scales from prototyping to production.