Mutation Clinical Trial Matching MCP

The Mutation Clinical Trial Matching MCP is a high‑performance, unified Model Context Protocol server designed to bridge Claude Desktop with the clinicaltrials.gov API for genetic‑mutation‑based trial discovery. It solves a critical bottleneck in precision oncology: clinicians and researchers often need to translate a patient’s genomic profile into actionable clinical trial options, but doing so manually is time‑consuming and error‑prone. By exposing a simple MCP interface, this server lets AI assistants parse natural language queries about mutations and instantly return curated trial lists, summaries, and eligibility details.

At its core, the server ingests a mutation description (e.g., “EGFR exon 19 deletion”) and queries the clinicaltrials.gov database, filtering results by mutation relevance, study phase, location, and other criteria. The response is a concise, human‑readable summary that highlights key study attributes—intervention type, eligibility criteria, enrollment status—and links to the full trial record. This capability is invaluable for developers building AI‑augmented decision support tools, as it removes the need to write custom API wrappers or maintain complex query logic. Instead, developers can issue a single MCP call and receive structured trial data ready for downstream processing or display.

Key features of the server include:

• Unified sync/async architecture – A single codebase supports both blocking and non‑blocking runtimes, allowing seamless integration into diverse application stacks.
• Enterprise resilience – Built‑in circuit breakers, retry logic, and distributed caching protect against transient API failures while keeping latency low.
• Observability – Prometheus metrics, cache analytics, and health dashboards provide real‑time insight into performance and usage patterns.
• Zero breaking changes – A compatibility layer guarantees that existing clients continue to work after the architectural overhaul, while new clients benefit from modern type safety and performance gains.
• Extensive testing – A 114‑test suite covers all unified components, ensuring reliability across edge cases.

In practice, the MCP can be employed in several real‑world scenarios. A hospital’s clinical decision support system might query the server whenever a new genomic report is uploaded, automatically populating a “Potential Trials” panel for oncologists. A research portal could surface trial opportunities to patients based on their mutation profiles, enhancing enrollment rates for niche studies. Even a chatbot integrated into an electronic health record could answer patient questions about trial eligibility without leaving the clinical workflow.

Because the server communicates via MCP, it fits naturally into existing AI assistant pipelines. Developers can chain the mutation‑matching call with other MCP tools—such as summarization or data extraction—to build sophisticated, end‑to‑end clinical workflows. The server’s design emphasizes performance (80 % faster than prior iterations) and maintainability, making it a robust foundation for any application that needs to translate genomic data into actionable clinical trial information.