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france-data-mcp

by io.github.cturkieh

centres_sante_in_radius

Read-onlyIdempotent

Recherche des Centres de Santé (CDS) dans un rayon géographique (PostGIS ST_DWithin). Source : Annuaire santé Ameli, Assurance Maladie (mention obligatoire L.1461-2 CSP — sync hebdomadaire CNAM). Différenciateur métier vs etablissements_finess_in_radius filtré famille=124 : expose carte_vitale, APCV, spécialités exercées sur place (Annexe A nomenclature CNAM, ~70 codes).

CDS = structures de soins ambulatoires non lucratives encadrées L.6323-1 CSP (associations, mutuelles, communes, hôpitaux). Volume ~3K en France. Filtres :

  • specialite_codes : array Annexe A (ex: ['01'] médecine générale, ['53'] dentaire). Match any-of — retourne les CDS qui exercent AU MOINS UNE des spécialités demandées.

  • accepte_carte_vitale : true / false / omis. Quasi-totalité accepte CV en pratique → filtre surtout utile en false pour audits.

  • type_etab_codes : ['124'] CDS standard, ['125'] CDS dentaire (deprecated CNAM, en voie d'extinction).

Coords = centroïde commune (~3 km moyenne) — pour précision adresse, pivoter via etab_finess retourné avec etablissement_by_finess. PAS d'horaires/tarifs/secteur 1/2 (retirés du nouvel annuaire CNAM post-2025).

Alias acceptés : radius/radius_meters → radius_km, latitude/longitude → lat/lon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYesLatitude du centre (WGS84). Ex: 48.872 (Paris).
lonYesLongitude du centre (WGS84). Ex: 2.317 (Paris).
limitNoNombre max de résultats (1-500, défaut 100).
radius_kmNoRayon en km (0.1-50, défaut 5).
type_etab_codesNoCodes type établissement Annexe B : ['124'] CDS standard (défaut implicite), ['125'] CDS dentaire deprecated. Vide = tous types.
specialite_codesNoCodes spécialité CNAM Annexe A (ex: ['01'] médecine générale, ['53'] chirurgien-dentiste). Match any-of. Vide = pas de filtre spécialité.
include_freshnessNoSi true, ajoute un champ `data_freshness` au payload (dans `query_metadata` si présent, sinon à la racine) listant la dernière ingestion réussie par source (FINESS, Ameli, RPPS, CDS) avec `staleness_days`. Opt-in pour ne pas alourdir les payloads par défaut. Cache 5min côté serveur — coût négligeable.
accepte_carte_vitaleNoFiltre par acceptation carte Vitale. true = uniquement CDS qui acceptent CV, false = uniquement ceux qui ne l'acceptent pas. Omis = pas de filtre.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNombre d'entrées retournées dans `results` (post-troncature).
totalNoEffectif réel avant troncature. Présent sur les tools de nomenclature paginés (lister_*) : `count` = échantillon, `total` = total réel, re-appeler avec un `limit` supérieur si `truncated`.
resultsYesEntrées métier (shape spécifique au tool, cf. description du tool).
freshnessNoFraîcheur des sources (présent si `include_freshness: true`).
perimetreNoLentille de la source : ce que le comptage inclut/exclut. Lire `completeness_note` et la restituer au lecteur final.
truncatedNotrue si le total réel dépasse `limit` (re-paginer via `offset` si supporté, ou augmenter `limit` sur les lister_*). Optional sur les tools de listing exhaustif (lister_*).
query_metadataNoMetadata de la query (radius_km, departement, filtres appliqués, …).
activite_hebergeeNoCompte juxtaposé des sites hébergeant l'activité correspondant à la famille filtrée, sous une autre catégorie FINESS. Distinct du `count` principal — lire `note` pour comprendre la sémantique et ne JAMAIS additionner les deux comptes sans préciser leur nature.

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds valuable context: coordinates are centroïdes of communes (≈3 km avg), no schedules/tariffs, and aliases for parameters. No contradiction 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?

The description is relatively long but well-structured with clear sections. Every sentence adds value, and the main function is front-loaded. Minor reduction in score due to length, but still efficient.

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 complexity (8 parameters, output schema exists), the description covers all essential aspects: data source, update frequency, filters, edge cases (deprecated codes), and limitations (no schedules/tariffs). It is complete for agent understanding and 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 description coverage is 100%, so baseline is 3. The description adds meaning beyond the schema by explaining the any-of logic for specialite_codes, the practical use of accepte_carte_vitale (audits), and the deprecated status of type_etab_codes ['125']. It also notes accepted aliases for parameters.

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 searches for Centres de Santé within a geographic radius using PostGIS ST_DWithin. It distinguishes itself from the sibling tool `etablissements_finess_in_radius` by listing specific exposed fields (carte_vitale, APCV, specialties) and explicitly mentions the differentiation.

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 provides explicit guidance on when to use this tool (for CDS, not other establishments) and names the alternative `etablissements_finess_in_radius` for filtered family=124. It also states what the tool does NOT provide (horaires/tarifs), giving clear context for appropriate usage.

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.

Resources