mcp-ClinicalTrial
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_clinical_trialsC | Search clinical trials using ClinicalTrials.gov API v2. Returns study information including protocols, interventions, and outcomes. |
| get_study_detailsB | Get detailed information about a specific clinical trial by NCT ID |
| compare_adverse_eventsC | Compare adverse events between treatment and control groups for a specific drug across clinical trials. Provides baseline reference and evidence for drug safety analysis. |
| ae_pipeline_ragA | Advanced RAG pipeline for adverse events analysis. Fetches, extracts, chunks, retrieves and summarizes clinical trial data in one call to prevent LLM response truncation. |
| analyze_safety_profileC | Analyze safety profile of a drug by extracting and comparing adverse events data across multiple clinical trials. Provides risk assessment and dose-response relationships. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Most tools have distinct purposes, but there is some potential overlap between 'analyze_safety_profile' and 'compare_adverse_events' as both involve adverse events analysis. The descriptions help differentiate them, with one focusing on overall safety profiling and the other on group comparisons, but an agent might initially confuse their scopes.
The naming conventions are mixed, with tools using verb_noun patterns like 'search_clinical_trials' and 'get_study_details', but others like 'ae_pipeline_rag' and 'analyze_safety_profile' deviate with acronyms or noun-heavy structures. This inconsistency reduces predictability, though the names remain generally readable.
With 5 tools, the count is well-scoped for a clinical trial server, covering search, retrieval, and analysis functions. Each tool appears to earn its place without redundancy, providing a focused set for typical agent workflows in this domain.
The tool set covers core operations like search, retrieval, and analysis of clinical trial data, with good lifecycle coverage from finding trials to detailed analysis. A minor gap exists in update or management functions, but this is reasonable for a read/analysis-focused server, and agents can work around it effectively.