Open Targets MCP Server

Overview

The Augmented Nature Open Targets MCP Server provides a ready‑made bridge between AI assistants and the rich, curated data of the Open Targets platform. By exposing a set of well‑defined tools—searching for genes, diseases, and their associations—the server eliminates the need for developers to write custom API wrappers or manage authentication. This makes it straightforward to incorporate high‑quality therapeutic target information directly into conversational AI workflows, enabling smarter, data‑driven responses.

The server solves a common pain point in drug discovery and precision medicine: accessing up‑to‑date, cross‑referenced evidence on gene–disease relationships. Researchers and clinicians often need to query thousands of targets, filter by evidence scores from multiple databases, or retrieve detailed ontological descriptions. The MCP server consolidates these capabilities into a single endpoint, allowing an AI assistant to perform complex queries in one step and return structured results that can be rendered or further processed by downstream applications.

Key capabilities are delivered through six specialized tools:

• search_targets and search_diseases let users find genes or conditions by keyword, returning ranked results with identifiers and brief descriptions.
• get_target_disease_associations provides evidence‑scored links between a specific target and disease, supporting hypothesis generation.
• get_disease_targets_summary offers a prioritized list of therapeutic targets for any disease, ideal for target‑prioritization pipelines.
• get_target_details and get_disease_details expose comprehensive metadata, including ontologies, pathways, and related drug information.
• Resource templates (e.g., ) enable quick navigation to Open Targets web pages directly from the AI interface.

These tools empower real‑world scenarios such as a researcher asking an assistant to “list high‑confidence targets for breast cancer,” or a clinician requesting the latest evidence on a gene’s role in a rare disease. The assistant can then retrieve, format, and present the data without leaving the conversation.

Integration with AI workflows is seamless: an MCP‑enabled client (e.g., Claude Desktop) can invoke any tool by name, pass arguments, and receive JSON responses. The assistant can chain calls—searching for a target, pulling its details, and then fetching associated diseases—to construct comprehensive answers or feed the data into downstream analytics. The server’s live connection to Open Targets ensures that every query reflects the latest curation, giving developers confidence in the freshness and accuracy of the information they deliver to users.