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datagouv

datagouv-mcp

by datagouv

Search datasets

search_datasets
Read-onlyIdempotent

Search for datasets on data.gouv.fr by entering keywords to find and explore public data.

Instructions

Search for datasets on data.gouv.fr by keywords.

This is typically the first step in exploring data.gouv.fr. Use short, specific queries (the API uses AND logic, so generic words like "données" or "fichier" may return zero results).

Use sort to order results. Accepted values: created, last_update, reuses, followers, views. Optionally prefixed with '-' for descending (e.g. -last_update). Use last_update_range to restrict results to recently updated datasets: last_30_days, last_12_months, last_3_years.

Typical workflow: search_datasets → list_dataset_resources → query_resource_data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
pageNo
page_sizeNo
sortNo
last_update_rangeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses API behavior (AND logic, zero results for generic words) and explains sort and range options. Annotations already declare readOnly and idempotent, so description adds value without contradiction.

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?

Concise, front-loaded with purpose, no redundant sentences. Well-structured with usage tips and workflow hint.

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?

Covers purpose, key parameters, and typical workflow. Output schema exists so return values need not be detailed. Slightly more guidance on page_size default would help.

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 has 0% description coverage. Description adds meaning for sort and last_update_range, but query, page, and page_size lack elaboration beyond schema basics. Acceptable given query is self-explanatory.

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?

Clearly states the tool searches for datasets on data.gouv.fr by keywords. Differentiates from siblings by being the first step and listing a typical workflow.

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?

Provides explicit guidance on query format (short, specific, AND logic) and sort/last_update_range parameters. Mentions typical workflow but does not explicitly exclude alternatives.

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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