mcp-gouv-fr

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datagouv_search_datasets

Search datasets on data.gouv.fr by title, description, or organization. Enter a free-text query and choose page number and size for paged results.

Instructions

Search datasets (title, description, organization).

Args: query: Free-text search query. page: Page number (1-based). page_size: Page size (keep reasonably small, e.g. ≤ 100).

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": "datagouv_search_datasets"
  }
}

Input Schema

Name	Required	Description	Default
`page`	No
`query`	Yes
`page_size`	No

Output Schema

Name	Required	Description
`page`	No	Current 1-based page index returned by the API.
`total`	No	Total matching datasets reported by the API, if available.
`datasets`	No	Datasets matching the query for this page (API key 'data' mapped here).
`next_page`	No	Absolute URL to fetch the next page, or null when there is no next page.
`page_size`	No	Number of items requested per page (may cap server-side).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

A4.1/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It adds useful search-scope details and a page_size guard ('keep reasonably small, e.g. ≤ 100'), but it does not disclose authentication needs, rate limits, result ordering, or whether search is fuzzy/exact.

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 main purpose is front-loaded in one line, followed by compact and complete Args entries. Every sentence earns its place, and there is no repetition of schema defaults or irrelevant 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 3-parameter search tool with an output schema, the core calling contract (free-text query, pagination, size limit) is fully covered. The main missing context is explicit differentiation from sibling toolsarkan otherwise minor gap given the output schema covers return shape.

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?

Schema description coverage is 0%, but the description compensates fully for all three parameters: query is labeled 'free-text search', page is '1-based', and page_size gets explicit sizing guidance. This adds real meaning beyond the raw schema property names and defaults.

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 states 'Search datasets' and specifically lists the searchable fields (title, description, organization), making the tool's action and resource clear. This clearly differentiates it from the sibling datagouv_get_dataset, which is a direct fetch rather than a search.

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?

It implies this is the dataset discovery/search tool, but it never explicitly says when to use it versus datagouv_get_dataset or the geo/insee search siblings. No alternatives, exclusions, or routing conditions are stated.

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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