mcp-data-gouv-fr

data_gouv_fr_search_organizations

Find French public organizations and data producers on data.gouv.fr. Search for certified entities like Etalab, INSEE, IGN, ministries, or local governments.

Instructions

Search data.gouv.fr organizations and producers. Useful to find certified public producers such as Etalab, INSEE, IGN, ministries, regions, departments, or municipalities.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "data_gouv_fr_search_organizations"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Organization search query, e.g. "insee", "etalab", "ign", "réunion".
`page_size`	No	Number of organizations to return.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 20, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations are provided, so the description carries the burden of explaining behavior. 'Search' clearly implies a read-only operation, and the description states what is being searched. However, it does not mention result shape, pagination behavior, ordering, rate limits, or any other limits, leaving some behavioral ambiguity.

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 two sentences long, front-loaded with the core action and resource, and every sentence adds useful context. The examples are concise and help clarify the intended search space without unnecessary detail.

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 simple two-parameter, read-only search with full schema coverage, the description gives enough context to invoke the tool correctly. It does not describe the expected return shape because there is no output schema, but the tool name and action make the fundamentals clear.

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%, with both 'query' and 'page_size' already well described in the schema. The description adds no new parameter-level semantics beyond context about what kinds of organizations are relevant, so the baseline score of 3 is appropriate.

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 specific action and resource: 'Search data.gouv.fr organizations and producers.' It further distinguishes itself from sibling tools by focusing on organizations/producers rather than datasets, sources, or dataservices, and gives concrete example producers like INSEE and IGN.

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 has a clear use case: 'Useful to find certified public producers such as Etalab, INSEE, IGN, ministries, regions, departments, or municipalities.' It does not explicitly mention when not to use it or name alternative tools, but the target resource is distinct enough for an agent to make a reasonable selection.

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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