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clinicaltrialsgov-mcp-server

by cyanheads

Clinicaltrials Get Study Record

clinicaltrials_get_study_record
Read-onlyIdempotent

Fetch the full study record for an NCT ID from ClinicalTrials.gov, returning protocol details, eligibility, outcomes, arms, interventions, contacts, and locations. Use optional caps to trim data.

Instructions

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.
Behavior5/5

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

Adds meaningfully beyond the readOnly/openWorld/idempotent annotations: explains that caps preserve original totals in filtersApplied only when a list is actually trimmed, that primary outcomes and seeAlsoLinks are never capped, and that nearLocation geocoding is city-centroid and drops locations without coordinates. This is exactly the kind of non-obvious runtime behavior an agent needs.

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 front-loaded sentences with no filler: first states the primary purpose, second captures the one non-obvious behavioral subtlety about caps and filtersApplied. The prose is dense but every clause adds value.

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?

The output schema handles return-value expectations, the param schema thoroughly documents behavior, annotations cover safety and idempotency, and the description adds scope, cap semantics, and geocoding limitations. For an agent deciding whether and how to call this tool, nothing meaningful is missing.

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 every parameter already has a thorough description including ranges, defaults, and behavior. The tool description itself adds little beyond a concise summary of the trimming behavior, so the baseline score of 3 is appropriate.

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?

Starts with a specific verb and resource: 'Fetch a single clinical trial study by NCT ID'. Unambiguously distinguishes this from sibling tools like the search/count tools, and the 'by NCT ID' identifier makes the invocation target crystal clear.

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 clear this is the tool for fetching one study by NCT ID, and the nearLocation parameter description explicitly points to clinicaltrials_search_studies for broad geographic filtering. However, it does not directly contrast with all relevant siblings such as clinicaltrials_get_study_results, so the routing guidance is good but not exhaustive.

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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