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clinicaltrialsgov-mcp-server

by io.github.cyanheads

Clinicaltrials Get Study Record

clinicaltrials_get_study_record
Read-onlyIdempotent

Fetch a single clinical trial study by NCT ID from ClinicalTrials.gov. Returns the full study record including protocol details, eligibility criteria, outcomes, arms, interventions, contacts, and locations. Optional locationLimit / outcomeLimit / referenceLimit / nearLocation parameters trim locations, outcomes, and references — original totals are preserved in filtersApplied only when a cap actually trims the set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nctIdYesNCT identifier — format `NCT` followed by 8 digits (e.g., `NCT03722472`).
nearLocationNoFilter returned locations to those within radius of (lat, lon) and sort by distance. Adds distanceMi to each location. Locations without published coordinates are dropped — most US sites carry them; international sites less reliably so. Distances reflect ClinicalTrials.gov geocoding granularity — typically city-centroid, not facility-level — so multiple sites in the same city resolve to near-identical distances. For broader geographic filtering across studies, use clinicaltrials_search_studies with geoFilter.
outcomeLimitNoOptional cap on the number of secondary and other outcomes returned. Omit for no cap (full upstream lists). Primary outcomes are never capped. Original totals preserved in filtersApplied.totalSecondaryOutcomes / totalOtherOutcomes only when the cap trims a list.
locationLimitNoOptional cap on the number of locations returned. Omit for no cap (full upstream list). Pairs naturally with nearLocation for narrowing a large multi-site trial. Original total preserved in filtersApplied.totalLocations only when the cap trims the list.
referenceLimitNoOptional cap on the number of references returned. Omit for no cap (full upstream list). Original total preserved in filtersApplied.totalReferences only when the cap trims the list. seeAlsoLinks are never capped.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
studyNoFull study record with caller-requested filters already applied to locations and outcomes. Top-level keys: protocolSection (identification, status, sponsor, conditions, design, arms/interventions, outcomes, eligibility, contacts/locations), derivedSection (MeSH-normalized terms), hasResults, documentSection. The heavy resultsSection is omitted — see resultsSummary for counts and clinicaltrials_get_study_results for full results data. Use clinicaltrials_get_field_definitions to explore the schema.
filtersAppliedNoMetadata about the filtering applied to `study`.
resultsSummaryNoCompact counts of posted results, present when hasResults is true. The full resultsSection is intentionally omitted from this record-level tool — fetch it via clinicaltrials_get_study_results or the clinicaltrials://{nctId} resource.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark this as readOnly, idempotent, and open-world, so the safety profile is covered. The description adds valuable behavioral context beyond those annotations: cap parameters trim locations/outcomes/references, primary outcomes are never capped, and original totals are preserved in filtersApplied only when a cap actually trims the set. This gives an agent accurate expectations about how limits behave.

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?

The description is two sentences, front-loads the core purpose, lists the returned content compactly, and then states the cap-related behavior without redundancy. Every clause contributes information an agent needs; there is no filler or rephrasing of the tool name.

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 the rich input schema, effective annotations, and an existing output schema, the description provides what is missing: the scope of the full study record and the nuanced behavior of optional trimming parameters. An agent has enough information to select and invoke this tool correctly without needing return-format details, since the output schema covers that.

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

Parameters3/5

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

Schema description coverage is 100%, and each parameter already carries detailed descriptions including defaults, bounds, and filter behavior. The tool description only summarizes the trimming behavior already documented in the schema, so it adds little semantic value beyond the structured field definitions. This is the correct baseline for full schema coverage.

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?

The description opens with a specific verb and resource: 'Fetch a single clinical trial study by NCT ID from ClinicalTrials.gov.' It clearly differentiates this single-record retrieval tool from the sibling search, count, and results tools, and names exactly what the returned record contains.

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

Usage Guidelines4/5

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

The description makes the core usage explicit: use this tool when you need a single study record by NCT ID. It also provides one concrete routing rule in the nearLocation parameter, directing broader geographic filtering to clinicaltrials_search_studies with geoFilter. It does not enumerate exclusions for every sibling, but the context is otherwise clear.

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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TDQS

A4.7/5.0
Disambiguation5/5

Each tool targets a distinct action: finding eligible trials, resolving field names, discovering field values, counting studies, fetching full records, fetching results, and searching. Even the count tool is clearly separated from search by its lightweight, no-data purpose. No two tools have ambiguous boundaries.

Naming Consistency5/5

All tools follow a strict 'clinicaltrials_' prefix followed by a descriptive verb_noun pattern (find_eligible, get_study_record, search_studies). The naming is uniform in snake_case and clearly indicates the operation and object. This consistency makes the tool set predictable.

Tool Count5/5

Seven tools is well within the ideal range for a focused MCP server. Each tool covers a necessary aspect of the ClinicalTrials.gov API (search, retrieval, counting, field exploration, results, eligibility matching) without bloat or redundancy. The scope feels complete for a read-only clinical trials interface.

Completeness5/5

The tool set covers the full read-only lifecycle: discovering the data model, searching, counting, fetching protocol records, fetching results, and matching patients to trials. There are no obvious gaps like missing location details or result statistics (both handled via parameters). The server fulfills its stated purpose without dead ends.

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