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xpay Academic Research Collection

search_trials_by_intervention

Search clinical trials by intervention/treatment.

This tool allows you to search for clinical trials based on a list of interventions or treatments.

Input:

  • interventions: A list of strings, where each string is an intervention or treatment to search for. The search will find trials related to any of the specified interventions. Example: ['aspirin', 'chemotherapy']

  • max_studies: The maximum number of studies to return. Defaults to 50.

  • fields: A list of specific fields to return in the results. If not provided, returns SEARCH_TOOL_DEFAULTS (9 essential fields: NCTId, BriefTitle, Acronym, Condition, Phase, InterventionName, LeadSponsorName, OverallStatus, HasResults).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoSpecific fields to return
max_studiesNoMaximum number of studies to return
interventionsYesInterventions/treatments to search for

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations are present, so the description bears the burden of behavioral disclosure. It explains the OR-semantics for interventions and the default fields via SEARCH_TOOL_DEFAULTS, but it does not mention read-only status, potential errors, or output structure. These are useful but not fully comprehensive; a search tool implies read-only, yet this is not explicitly stated.

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?

The description is well-structured with an intro and bullet-point-style parameter explanations. It is reasonably concise, though it slightly repeats 'intervention/treatment' and could be tighter. The example and defaults list are valuable, so it earns a high score for structure without being overly verbose.

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

Completeness3/5

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

With no output schema, the description should explain return values. It partially does by naming the default return fields, but it does not describe the result container or pagination. Given the tool's simplicity, this is adequate but leaves gaps for an agent trying to consume results. It is complete enough for basic use but lacks full contextual details.

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%, so baseline is 3. The description adds meaningful value beyond schema by clarifying that multiple interventions are matched using OR, providing an example for the interventions parameter, and explicitly listing the SEARCH_TOOL_DEFAULTS fields when fields is not provided. This goes beyond the schema's simple parameter names.

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 'Search clinical trials by intervention/treatment' with a specific verb and resource, and distinguishes it from sibling tools like search_trials_by_condition and search_trials_by_sponsor by explicitly naming the search dimension (interventions).

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 provides clear context on usage—it searches for trials matching any of the provided interventions, with defaults for max results and return fields. However, it does not explicitly mention alternative tools or exclusions (e.g., 'use this instead of search_trials_by_condition'), so it lacks the when-not-to-use guidance for a top score.

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

C2.6/5.0
Disambiguation1/5

Multiple tools appear to serve the same purpose, such as search_arxiv and search-arxiv, or papers-search-basic, paper-search-advanced, search_papers, and search. The download/read tools for different sources follow similar patterns, but some return 'not supported' messages, making it unclear which tools are actually functional.

Naming Consistency1/5

Tool names mix snake_case, kebab-case, and bare verbs without a consistent pattern. For example, about_nanci, analysis-citation-network, download-full-paper-arxiv, fetch, and search_arxiv all coexist, and the same action for different sources alternates conventions (search-arxiv vs search_arxiv).

Tool Count1/5

With 53 tools, the server is heavily over-scoped. Many tools are redundant or near-duplicates, such as six source-specific search tools plus an aggregate search, and the inclusion of both paper and clinical trial tools in one server creates unnecessary bloat.

Completeness3/5

The server covers a wide range of research workflows, including search, download, read, citations, authors, and clinical trials. However, several tools (crossref/pubmed download/read) are non-functional dead ends, and the redundancy makes it harder to navigate the surface.

Resources