Life Sciences Research

About

This tool establishes a "Structured Truth Layer" for AI agents, enabling them to seamlessly query critical life sciences databases such as Open Targets, ChEMBL, and UniProt through the Model Context Protocol (MCP). It provides a microservices-based approach, offering 12 operational MCP servers for various biological data layers, from genes and proteins to compounds, pathways, and clinical trials. By aggregating disparate data sources and providing a unified interface, it empowers AI agents to perform tasks like validating scientific claims, resolving biological identifiers, and discovering interactions, ultimately accelerating drug discovery, drug repurposing, and broader biomedical research efforts.

Key Features

• Provides 12 operational AI agent wrappers (MCP servers) for key life sciences APIs.
• Offers comprehensive test suites with over 500 integration tests ensuring data reliability.
• Utilizes the Model Context Protocol (MCP) and FastMCP for AI agent communication and data grounding.
• 3 GitHub stars
• Integrates data from over 15 major biological databases including Open Targets, UniProt, ChEMBL, and ClinicalTrials.gov.
• Facilitates fuzzy search and strict lookup capabilities for biological entities (genes, proteins, compounds).

Use Cases

• Accelerating drug discovery and repurposing efforts with AI-driven data integration.
• Grounding AI agent claims and scientific reasoning with validated, structured biological data.
• Developing integrative computational drug discovery pipelines leveraging diverse biological databases.