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france-data-mcp

by io.github.cturkieh

etablissement_by_siret

Read-onlyIdempotent

Récupère le détail d'un établissement par son SIRET (14 chiffres) via l'API SIRENE INSEE V3.11 : raison sociale de l'unité légale, enseigne commerciale, NAF de l'établissement, dates de création/fermeture, statut administratif actif/fermé, adresse complète, tranche d'effectif. Source : SIRENE INSEE V3.11 (api.insee.fr).

Format de retour : objet LookupResult discriminé par found.

  • found: true → établissement à plat (siret, siren, actif, dateFermeture, enseigne, adresse, …)

  • found: false → { found: false, key, lookupStatus: 'not_found', message }. Cas typiques : clé INSEE_SIRENE_API_KEY non configurée côté serveur (message explicite), SIRET inexistant SIRENE, diffusion partielle INSEE.

⚠️ Différence avec entreprise_by_siren : ce tool renvoie UN établissement précis (un site), alors que entreprise_by_siren renvoie l'unité légale + sa liste d'établissements. Pour détecter un SIRET fermé encore listé actif côté FINESS, lire actif: false + dateFermeture.

Pas de coords : l'endpoint INSEE /siret/<siret> ne renvoie pas les coordonnées GPS. Pour géolocaliser, croiser avec geocode_adresse côté caller ou utiliser entreprises_in_radius.

Rate limit INSEE : 30 req/min (retry-after géré côté serveur).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siretYesSIRET exact, 14 chiffres.

Output Schema

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

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnly=true, idempotent=true, non-destructive. Description adds significant behavioral context: the tool queries INSEE V3.11 API, returns a discriminated LookupResult (found true/false with specific fields), describes two not_found scenarios (API key missing, SIRET not found in SIRENE or diffusion partielle), explicitly states no GPS coordinates are returned, and explains rate limiting behavior. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is detailed with well-structured sections (return format, error cases, sibling distinction, limitations, rate limit). However, it is somewhat verbose (multiple paragraphs); some sentences could be condensed. Front-loaded with purpose and key details, earning a 4.

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 tool's simplicity (1 param, output schema present, rich annotations), the description covers all essential aspects: return type, error handling, source, limitations (no coords), rate limit, and comparison with sibling tool. No gaps for an AI agent to misunderstand usage.

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 has 100% coverage for the single parameter 'siret' (string, 14 digits). Description reinforces that SIRET must be exact 14 digits and adds context about format expectations. While schema already documents the parameter, the description provides meaningful usage context (exactness) justifying a score above baseline 3.

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 it retrieves details of an establishment by SIRET (14 digits) via the INSEE SIRENE API, listing specific fields returned (e.g., raison sociale, NAF, address, status). It explicitly differentiates from sibling 'entreprise_by_siren' by noting that this tool returns a single establishment site while the sibling returns the legal unit plus its establishments.

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?

Provides explicit when-to-use: retrieving details of a specific establishment by SIRET. Contrasts with 'entreprise_by_siren' for legal unit vs. establishment. Advises on detecting closed SIRET still active on FINESS by checking 'actif' and 'dateFermeture'. Notes rate limit (30 req/min) with server-side retry handling. Offers alternative tools for geocoding ('geocode_adresse', 'entreprises_in_radius').

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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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.

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