biothings-mcp
by longevity-genie
The biothings-mcp server implements the Model Context Protocol (MCP) for BioThings, providing a standardized interface for accessing and manipulating biomedical data. It enables AI assistants and agents to access specialized biomedical knowledge through structured interfaces to authoritative data sources.
Last updated: N/A
What is biothings-mcp?
The biothings-mcp server is an implementation of the Model Context Protocol (MCP) for BioThings.io. It provides a standardized API interface for accessing and manipulating biomedical data from sources like mygene.info, myvariant.info, and mychem.info, making it easier for AI systems to interact with and utilize this data.
How to use biothings-mcp?
To use the server, you can either run it locally using uv or deploy it using Docker. Once running, you can connect to it using an MCP-compatible AI client, pointing the client to the appropriate configuration file (mcp-config.json for local, mcp-config-remote.json for the publicly hosted server). The API can be accessed via HTTP requests to the server's endpoints.
Key features of biothings-mcp
Structured Access to BioThings data
Support for Natural Language Queries
Type Safety via biothings-typed-client
Seamless Integration with AI assistants and agents
Use cases of biothings-mcp
Integrating biomedical knowledge into AI assistants
Enabling natural language queries against biomedical databases
Building AI agents that can access and manipulate biomedical data
Creating structured interfaces to authoritative data sources for AI systems
FAQ from biothings-mcp
What is MCP?
What is MCP?
MCP (Model Context Protocol) is a protocol that bridges the gap between AI systems and specialized domain knowledge, enabling structured access, natural language queries, and type safety.
What BioThings data sources are supported?
What BioThings data sources are supported?
The server supports mygene.info, myvariant.info, and mychem.info.
How do I run the server locally?
How do I run the server locally?
You can run the server locally using uv run server after installing uv and setting up the environment.
How do I deploy the server using Docker?
How do I deploy the server using Docker?
You can deploy the server using Docker Compose or directly with Docker, following the instructions in the README.
How do I integrate the server with my AI system?
How do I integrate the server with my AI system?
Point your MCP-compatible AI client to the appropriate configuration file (mcp-config.json or mcp-config-remote.json).