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lzinga

US Government Open Data MCP

by lzinga

clinical_trials_by_location

Read-onlyIdempotent

Search for clinical trials within a radius of any latitude/longitude point, and filter by condition, intervention, or status to find relevant studies nearby.

Instructions

Search for clinical trials near a geographic location. Uses the ClinicalTrials.gov geo-distance filter to find trials within a radius of a latitude/longitude point. Combine with condition or intervention filters to find specific trials nearby.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoFilter by status (default: RECRUITING)
distanceNoSearch radius with unit: '50mi' (default), '100km'
latitudeYesLatitude of the search center: 38.9072 (Washington DC)
conditionNoFilter by condition: 'diabetes', 'breast cancer'
longitudeYesLongitude of the search center: -77.0369 (Washington DC)
page_sizeNoResults per page (default 10)
interventionNoFilter by intervention: 'pembrolizumab'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / page_size / default
      Added value: +10
  2. Addedv2026.4.11

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds the behavioral detail that it uses the ClinicalTrials.gov geo-distance filter, which explains the underlying mechanism. However, it doesn't disclose potential limitations like maximum radius, behavior when no trials are found, or whether results are sorted by distance. The description doesn't contradict annotations.

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

Conciseness4/5

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

Three sentences with no wasted words. The core purpose is front-loaded in the first sentence, the mechanism in the second, and usage guidance in the third. It's appropriately sized for a tool with 7 parameters and clear scope.

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 100% schema coverage and no output schema, the description covers the essential context: what it does, how it works, and how to refine results. It could be more complete by noting the default radius (50mi) and that results are paginated, but these are already in the schema. The sibling list shows this is one of several clinical_trials tools, and the description does enough to differentiate it.

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 7 parameters with examples and defaults. The description adds the conceptual context that latitude/longitude form a search center and that distance is a radius, but this is largely redundant with the schema's parameter descriptions. The description's mention of combining with condition/intervention filters does add some strategic value beyond the 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?

The description clearly states the tool searches for clinical trials near a geographic location, using a specific geo-distance filter mechanism. It distinguishes itself from sibling tools like clinical_trials_search (which likely searches by text/condition) and clinical_trials_detail (which retrieves a specific trial). The verb 'search' plus the resource 'clinical trials' and the location-based scope make the purpose unambiguous.

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 explains the core use case (find trials near a location) and suggests combining with condition or intervention filters for more specific searches. It doesn't explicitly name sibling alternatives or state when NOT to use this tool, but the context signals and sibling list make the distinction fairly clear. The guidance to combine with other filters is useful but could be more explicit about when to choose this over clinical_trials_search.

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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