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Glama

xpay Academic Research Collection

by sh.xpay.mcp.research

search_trials_by_sponsor

Search clinical trials by sponsor/organization.

This tool allows you to search for clinical trials based on a list of sponsor organizations.

Input:

  • sponsors: A list of strings, where each string is a sponsor organization to search for. The search will find trials sponsored by any of the specified organizations. Example: ['National Cancer Institute', 'Pfizer']

  • 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
sponsorsYesSponsor organizations to search for
max_studiesNoMaximum number of studies to return

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden. It discloses the OR behavior across sponsors, the default return fields (SEARCH_TOOL_DEFAULTS), and the max_studies parameter. This gives a good sense of what the tool does and its constraints.

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 front-loaded with a one-sentence summary, then uses a structured bullet list for parameters. It is thorough without being verbose, and every sentence contributes information.

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?

For a read-only search tool with no output schema, the description covers the purpose, all parameters, defaults, and return field behavior. It is self-contained and sufficient for an agent to invoke the tool correctly.

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

Parameters5/5

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

The input schema has brief descriptions, but the tool description adds substantial value: explains that sponsors is a list with OR logic, gives an example, explains the default fields, and states that max_studies defaults to 50. This goes well 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 opens with 'Search clinical trials by sponsor/organization,' which clearly specifies the verb (search), resource (clinical trials), and scope (by sponsor/organization). This distinguishes it from sibling tools like search_trials_by_condition or search_trials_by_acronym.

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 clearly indicates the use case (searching trials by sponsor) but does not explicitly compare with alternatives or state exclusions. However, the context is clear enough that an agent would know when to invoke it.

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