mcp-french-transport-data

french_transport_data_search_datasets

Search French transport datasets by text to find relevant data from transport.data.gouv.fr.

Instructions

Search transport.data.gouv.fr datasets by text using the public API.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "french_transport_data_search_datasets"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No
`query`	No	Text filter applied locally to dataset title/slug after fetching the API list.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 23, 2026

TDQS

C2.3/5.0

Behavior1/5

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

With no annotations to rely on, the description carries full responsibility for behavioral transparency. It only mentions 'using the public API' without detailing side effects, rate limits, authentication requirements, or the nature of the response, leaving significant behavioral aspects undisclosed.

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, clear sentence with no extraneous details. It is appropriately sized for the tool's simple purpose and contains no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema and annotations, the description is too sparse. It does not clarify what the tool returns (e.g., dataset metadata, pagination details), nor does it provide any context about the underlying process (e.g., that it fetches a list and then filters locally). This leaves important gaps for an agent deciding to invoke the tool.

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

Parameters1/5

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

The tool description adds no information about its parameters beyond the schema. Although the schema includes a description for 'query', the overall schema coverage is only 50% (limit lacks any description), and the tool description does not compensate for the missing parameter semantics.

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 verb 'search' and the specific resource 'transport.data.gouv.fr datasets', making the tool's purpose unambiguous. However, it does not explicitly distinguish itself from sibling tools such as 'french_transport_data_get_dataset' or 'french_transport_data_search_data_gouv', so it falls short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It lacks any mention of scenarios where this search is preferred or where a sibling tool would be more appropriate, leaving the agent without usage context.

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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