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clinicaltrialsgov-mcp-server

Clinicaltrials Get Study Results

clinicaltrials_get_study_results
Read-onlyIdempotent

Retrieve detailed clinical trial results—outcome statistics, adverse events, participant flow, baseline data, and limitations—from ClinicalTrials.gov for completed studies with results.

Instructions

Fetch clinical trial results data from ClinicalTrials.gov for completed studies — outcome measures with statistics, adverse events, participant flow, baseline characteristics, and results metadata (limitations & caveats, certain-agreement disclosure restrictions, results point of contact). Only available for studies where hasResults is true. Use clinicaltrials_search_studies first to find studies with results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nctIdsYesOne or more NCT IDs (max 20). E.g., "NCT12345678" or ["NCT12345678", "NCT87654321"]. Use summary=true for large batches to avoid large payloads.
sectionsNoFilter which sections to return. Values: outcomes, adverseEvents, participantFlow, baseline, moreInfo. Omit for all sections.
summaryNoReturn condensed summaries instead of full data. Reduces payload from ~200KB to ~5KB per study. Summaries include outcome titles, types, timeframes, group counts, and top-level stats — omitting individual measurements, analyses, and per-group data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesResults per study.
studiesWithoutResultsNoNCT IDs that do not have results data.
fetchErrorsNoStudies that could not be fetched.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description adds context beyond annotations by detailing what data is returned (outcome measures, adverse events, participant flow, baseline, metadata) and the prerequisite, without contradicting annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences: first defines scope, second provides usage conditions. No redundant information, front-loaded with key purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given output schema exists and annotations are rich, description covers purpose, usage, prerequisites, and parameter hints comprehensively for a tool fetching multiple result sections.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed descriptions; description adds extra guidance on using summary=true for large batches, improving parameter understanding beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it fetches clinical trial results data for completed studies, listing specific sections (outcomes, adverse events, etc.). It differentiates from sibling tools by noting it requires hasResults=true and advising to use search_studies first.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Only available for studies where hasResults is true' and 'Use clinicaltrials_search_studies first to find studies with results', providing clear when-to-use and alternative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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