Clinical Trials
Delivers programmatic access to clinical trials data registries like ClinicalTrials.gov via MCP. Supports searches by condition, location, phase, status, sponsor; retrieves trial summaries, eligibility criteria, contacts, and results. Used by medical researchers, pharma developers, and healthcare data analysts for trial discovery and integration.
Overview
The @lulzasaur9192/mcp-clinical-trials MCP server provides an interface for querying clinical trials databases, enabling AI models and applications to access structured data on ongoing and completed trials. It pulls from public sources such as ClinicalTrials.gov, allowing filter-based searches and detailed retrievals without direct API keys or web scraping.
Key Capabilities
- search_trials: Queries trials using parameters like NCT ID, condition (e.g., "breast cancer"), location (country/city), status (recruiting/completed), phase (I-IV), and sponsor.
- get_trial: Returns full trial record for a given NCT ID, including protocol summary, eligibility criteria, study locations, contacts, and primary/secondary outcomes.
- filter_sponsors: Lists trials associated with specific sponsors or organizations.
These functions output JSON-formatted data compatible with MCP workflows.
Use Cases
- A researcher runs search_trials with condition="diabetes" and status="recruiting" location="USA" to identify eligible phase III studies for patient recruitment.
- Healthcare app developers call get_trial to display eligibility quizzes and contact info in a trial-matching mobile app.
- Pharma analysts use filter_sponsors to track competitors' trials by sponsor name, extracting outcome data for competitive intelligence.
- Academic teams retrieve results from completed trials via NCT ID for meta-analyses on drug efficacy.
Who This Is For
- Medical researchers screening trials for studies or collaborations.
- Developers integrating trial data into AI agents, patient portals, or research dashboards.
- Pharmaceutical and biotech analysts monitoring pipelines.
- Clinicians querying trials for personalized patient recommendations.