open-data-mcp

dataandbeyond--clinical-trials

Read-only

Search ClinicalTrials.gov trials by condition, intervention, sponsor, phase, status, location, or NCT ID via the official API v2 to find relevant study records.

Instructions

ClinicalTrials.gov search by condition, intervention, sponsor, phase or NCT ID. Calls the official API v2 directly.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "dataandbeyond--clinical-trials"
  }
}

Input Schema

Name	Required	Description
`nctIds`	No	Fetch specific trials. Example values: ["NCT04368728"]
`phases`	No	e.g. 2, 3
`sponsor`	No	e.g. Novo Nordisk
`location`	No	e.g. Denmark
`statuses`	No	e.g. RECRUITING, COMPLETED, ACTIVE_NOT_RECRUITING
`waitSecs`	No	Max seconds (0–45, default 30) to cap the wait for the Actor run to reach terminal state. For long-running Actors the response returns at the cap with the current run status; follow `nextStep` to poll via get-actor-run. Set to 0 to fire-and-forget.
`condition`	No	e.g. type 2 diabetes Example values: "obesity"
`maxResults`	No	Max results Example values: 50
`searchTerm`	No	Free text
`intervention`	No	e.g. semaglutide

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Oct 30, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuine context by stating it calls the official API v2 directly, implying first-party, authoritative data rather than scraping. It does not mention rate limits, result pagination, or the async actor-run wait behavior that dominates the schema.

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 sentences, zero filler, with the searchable scope front-loaded ahead of the data-source note. Every clause carries information an agent would otherwise have to infer.

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

Completeness4/5

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

For a read-only search tool with no required parameters and full schema coverage, the definition covers what the tool queries and where the data comes from. The main gap is return-value shape: with no output schema, a brief note on what a result contains (NCT ID, title, status, phase, sponsor, enrollment) would close the loop.

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%, so the schema already documents all ten parameters, including the nuanced waitSecs semantics. The description's enumeration of searchable fields maps to a subset of the parameters but adds no syntax, format, or combination rules beyond what the schema states. Baseline 3 applies when the schema does the heavy lifting.

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

Purpose4/5

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

The description names a specific verb (search) and resource (ClinicalTrials.gov trials) plus the dimensions searched: condition, intervention, sponsor, phase, NCT ID. It also names the data source ('official API v2'), which distinguishes it from generic web-scraping or literature siblings like pubmed-search and scholar-search. It stops short of explicitly ruling out those siblings.

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

Usage Guidelines3/5

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

The field list ('by condition, intervention, sponsor, phase or NCT ID') implicitly tells an agent when this tool is the right choice, and the ClinicalTrials.gov framing hints at the clinical-trials domain. However, there is no explicit guidance on when to prefer it over pubmed-search or scholar-search, and no note about what happens when multiple filters are combined.

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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