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BACH-AI-Tools

Clinical Trials MCP Server

search_by_sponsor

Find clinical trials by sponsor or organization to identify research studies funded by specific companies, institutions, or government agencies.

Instructions

Search clinical trials by sponsor or organization

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sponsorYesSponsor name or organization (e.g., "Pfizer", "National Cancer Institute")
sponsorTypeNoType of sponsor
pageSizeNoNumber of results to return (default 10, max 100)

Implementation Reference

  • The `handleSearchBySponsor` method implements the logic for the `search_by_sponsor` tool. It takes `sponsor` and `sponsorType` as arguments and queries the ClinicalTrials.gov API.
    private async handleSearchBySponsor(args: any) {
      if (!args?.sponsor) {
        throw new McpError(
          ErrorCode.InvalidParams,
          "Sponsor parameter is required"
        );
      }
    
      const params: any = {
        format: "json",
        pageSize: args?.pageSize || 10,
        "query.spons": args.sponsor,
      };
    
      if (args?.sponsorType) {
        params["filter.leadSponsorClass"] = args.sponsorType;
      }
    
      try {
        const response: AxiosResponse<StudySearchResponse> =
          await this.axiosInstance.get("/studies", { params });
    
        const studies = response.data.studies || [];
        const results = studies.map((study) => ({
          ...this.formatStudySummary(study),
          sponsorDetails:
            study.protocolSection.sponsorCollaboratorsModule?.leadSponsor,
        }));
    
        return {
          content: [
            {
              type: "text",
              text: JSON.stringify(
                {
                  searchCriteria: {
                    sponsor: args.sponsor,
                    sponsorType: args.sponsorType,
                  },
                  totalCount: response.data.totalCount || 0,
                  resultsShown: results.length,
                  studies: results,
                },
                null,
                2
              ),
            },
          ],
        };
      } catch (error) {
        if (axios.isAxiosError(error)) {
          return {
            content: [
              {
                type: "text",
                text: `Clinical Trials API error: ${
                  error.response?.data?.message || error.message
                }`,
              },
            ],
            isError: true,
          };
        }
        throw error;
      }
    }
  • src/index.ts:300-326 (registration)
    The tool `search_by_sponsor` is registered within the `ListToolsRequestSchema` handler in `src/index.ts`. It takes a `sponsor` string and optional `sponsorType` and `pageSize` arguments.
      name: "search_by_sponsor",
      description: "Search clinical trials by sponsor or organization",
      inputSchema: {
        type: "object",
        properties: {
          sponsor: {
            type: "string",
            description:
              'Sponsor name or organization (e.g., "Pfizer", "National Cancer Institute")',
            minLength: 2,
          },
          sponsorType: {
            type: "string",
            description: "Type of sponsor",
            enum: ["INDUSTRY", "NIH", "FED", "OTHER"],
          },
          pageSize: {
            type: "number",
            description:
              "Number of results to return (default 10, max 100)",
            minimum: 1,
            maximum: 100,
          },
        },
        required: ["sponsor"],
      },
    },

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations available, the description carries the full burden of behavioral disclosure. It only states the search action without revealing details such as whether partial matches are allowed, how results are ordered, or what the response structure contains. The description adds no behavioral context beyond what is already obvious from the name.

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 a single, well-structured sentence that front-loads the verb and object. It is appropriately minimal, containing no filler or redundant content.

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?

The description covers the core purpose but omits any mention of return values, pagination, or optional filtering by sponsor type. Given that this is a simple search tool with high schema coverage, the description is minimally adequate but could be more informative about what the search yields.

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?

All three parameters have rich descriptions in the input schema (100% coverage), so the schema already provides the necessary semantic meaning. The tool description does not add any parameter-related information, warranting the baseline score of 3.

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 clearly states the tool searches clinical trials by sponsor or organization, using a specific verb and resource. It is unambiguous but does not explicitly differentiate from sibling tools like search_by_condition or search_by_location, so it misses the top score.

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 description implies its use case (searching trials by sponsor), but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any constraints or exclusions. It is sufficient for a straightforward search tool but lacks comparative direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.