Clinical Trial Gov MCP Server
ClinicalTrials.gov data access for AI agents using semantic search and trial metrics.
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Overview
This server acts as a semantic intelligence layer for the ClinicalTrials.gov database. It translates natural language requests into complex Essie query syntax, allowing AI models to retrieve clinical trial data without manual API interaction. The server features 10 specialized tools designed for clinical research, including eligibility scoring, enrollment pace analysis, and competitive landscape mapping. It processes raw database responses into structured insights such as trial maturity and geographic distribution.
Our verdict
With a security score of 16/100, this tool carries a high risk level. It is a community-maintained project that has not been editorially reviewed, and the absence of a clear license creates uncertainty regarding its legal status. Furthermore, the repository has not received updates for over 200 days. Given these factors, it is recommended only for non-sensitive research environments where audit trails and security guarantees are not required.
- Supports natural language queries with automatic Essie syntax translation.
- Provides computed metrics like trial maturity and enrollment pace.
- Small supply-chain surface area with zero direct dependencies.
- High risk security score with no official vendor maintenance.
- Repository has been inactive for over 200 days.
- Unclear legal terms due to no detected license.
Tools
| Tool | Description | Risk |
|---|---|---|
| search_clinical_trials | Natural language trial discovery with comprehensive filtering. | low |
| analyze_trial_details | Deep-dive analysis with eligibility parsing, arm/intervention mapping, outcomes, and computed metrics. | low |
| match_patient_to_trials | Patient-centric matching with eligibility scoring, explanations, and actionable next steps. | low |
| get_trial_metadata_schema | Self-documenting API introspection — discover available fields, enums, and query syntax. | low |
| find_similar_trials | Competitive landscape analysis with similarity scoring across conditions, interventions, and phases. | low |
| analyze_trial_outcomes | Extract and compare primary/secondary outcome measures across trials. | low |
| get_enrollment_intelligence | Market capacity analysis with enrollment patterns, saturation scores, and velocity insights. | low |
| analyze_sponsor_network | Organization portfolio analysis with therapeutic focus, pipeline stage distribution, and collaborations. | low |
| export_and_format_trials | Batch export in JSON, CSV, or Markdown with grouping and summary statistics. | low |
| query_trial_statistics | Aggregate analytics: geographic distribution, disease landscape, enrollment patterns. | low |
Compatibility
| Client | Local | Docker | Remote | Read-only |
|---|---|---|---|---|
| Claude Desktop | ||||
| Cursor | ||||
| VS Code | ||||
| Windsurf | ||||
| ChatGPT |
Frequently asked questions
›What are the system requirements to run this MCP server?
You need Python 3.11+ and a package manager like pip installed on your system.
›Does this server support containerized deployment?
Yes, you can build and run the server using the provided Docker configuration.
›How is the server configured for use with an IDE or CLI?
You can connect by adding the clinicaltrials server configuration to your MCP settings file, pointing to the HTTP URL http://localhost:8000/mcp.
›Does the server provide raw data or processed analytics?
The server provides both, including high-level semantic tools for computed metrics like enrollment pace and trial maturity, alongside raw data exports.
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