Skip to main content
Glama

france-data-mcp

by io.github.cturkieh

get_commune_by_code

Read-onlyIdempotent

Récupère une commune par son code INSEE. Retourne un objet LookupResult discriminé par found. found: true → champs commune à plat (nom, codesPostaux, centre…). found: false → { found: false, key, lookupStatus: 'not_found', message } orientant vers autocomplete_commune pour disambiguer.

Alias acceptés : code_insee/codeInsee/insee → code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesCode INSEE 5 caractères. Ex: "75056" Paris, "59009" Villeneuve-d'Ascq, "2A004" Ajaccio.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoClé recherchée (SIREN, num_finess, code INSEE, …).
foundYes
messageNoExplication actionnable quand `found=false` (cause probable + remédiation).
lookupStatusYes

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds value by detailing the discriminated return type and the not_found behavior with a suggestion for alternative tool, but does not contradict annotations.

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 very concise with four lines, front-loaded with the core purpose, and each sentence adds necessary information without redundancy.

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

Completeness5/5

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

Given the low complexity, high annotation coverage, and presence of output schema, the description fully covers the return behavior and fallback, leaving no gaps.

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

Parameters4/5

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

Schema coverage is 100% with examples. The description adds alias information (code_insee/codeInsee/insee) that is not in the schema, enhancing understanding beyond the schema definition.

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 verb 'Récupère' and the resource 'commune par son code INSEE'. It distinguishes from sibling 'autocomplete_commune' by mentioning it for disambiguation.

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

Usage Guidelines5/5

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

The description explicitly tells the agent what to do when the commune is not found (use autocomplete_commune), providing clear guidance on fallback behavior.

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

All france-data-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation3/5

While tools have distinct purposes, there is overlap among several similar tools (e.g., multiple professional and establishment search tools). The detailed descriptions help differentiate, but an agent may struggle to choose correctly among them.

Naming Consistency2/5

Naming mixes French and English, with no consistent pattern (e.g., 'enrichir_concurrents' vs 'inspect_site', 'etablissement_by_finess' vs 'etablissements_finess_in_radius'). This inconsistency makes the toolset harder to navigate.

Tool Count3/5

36 tools is high but justified given the broad domain. However, there are multiple tools for similar tasks (e.g., four professional search tools), suggesting some redundancy. The scope is borderline but acceptable.

Completeness4/5

The toolset covers a wide range of needs for French health data analysis: establishments, professionals, population, geocoding, demographics, and composite analyses. Few obvious gaps exist, though some specialized tasks might require additional integration.

Resources