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  3. France Data MCP
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Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 3:46:39 PM

France Data MCP

User RatingsBe the first to rate and review this MCP server!
View Repository3 GitHub StarsTotal stargazers on GitHub for the source repository (3 stars).Visit Website
francelocation-serviceshealthcareopen-datageocoding

Cross-reference French public data on healthcare, businesses, demographics, geocoding, and property activity.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Automated check passed— started and listed 36 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON â–Ÿ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "cturkieh-france-data-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "france-data-mcp"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (36) Directory Badge Claim listing AlternativesđŸ—ș More in Location Services

Overview

This MCP combines 13 French public registries, including INSEE, FINESS, RPPS, Ameli, IGN, DVF, and PLU sources. It reconciles healthcare, business, demographic, geographic, and property data for territorial analysis. Use it for healthcare mapping, local market studies, civic-tech research, or site potential assessment.

Use cases

‱Map healthcare facilities and professionals around a location
‱Compare healthcare supply with neighborhood demographics
‱Identify business records and closed SIRET establishments
‱Assess property potential using sales, permits, and PLU zones
‱Research local healthcare and territorial conditions

Key features

‱Cross-references 13 French public data sources
‱Searches FINESS, RPPS, Ameli, SIRENE, and healthcare center records
‱Provides commune lookup, address geocoding, and reverse geocoding
‱Queries IRIS demographics, population, income, and healthcare density
‱Combines DVF prices, building permits, and PLU development zones
‱Exposes source freshness and reconciles records across registries

Capabilities & Tool Schemas (36) ~18.6k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by France Data MCP.

autocomplete_commune

Recherche de communes françaises par nom, code postal ou code INSEE. IdĂ©al pour autocomplĂ©tion. Source : geo.api.gouv.fr (DINUM/Etalab). Un (au moins) parmi `nom`, `codePostal`, `code` est requis. Alias acceptĂ©s : `q`/`query`/`search` → `nom`, `codepostal`/`postal_code` → `codePostal`, `code_insee`/`insee` → `code`.

get_commune_by_code

RĂ©cupĂšre une commune par son code INSEE. Retourne un objet `LookupResult` discriminĂ© par `found`. `found: true` → champs commune Ă  plat (nom, codesPostaux, centre
). `found: false` → `{ found: false, key, lookupStatus: 'not_found', message }` orientant vers `autocomplete_commune` pour disambiguer. Alias acceptĂ©s : `code_insee`/`codeInsee`/`insee` → `code`.

geocode_adresse

Géocode une adresse française en coordonnées GPS. Source : IGN Géoplateforme (data.geopf.fr). Précision au numéro de rue. Le champ `score` (0-1) qualifie la fiabilité du match : >= 0.8 fiable, < 0.5 = match douteux (souvent un fallback rue/commune sans rapport avec l'adresse demandée). Le champ booléen `confidence_low` vaut `true` dans ce cas : ne PAS utiliser `point` pour une décision quand `confidence_low: true`. Le champ `type` indique aussi la granularité (housenumber > street > locality > municipality).

reverse_geocode

GĂ©ocodage inverse : Ă  partir de coordonnĂ©es GPS, retrouve l'adresse la plus proche. Source : IGN GĂ©oplateforme. Couverture France mĂ©tropolitaine + DOM uniquement : des coordonnĂ©es hors zone (ex. New York) ou en pleine mer renvoient `null` (pas une erreur — c'est l'absence de rĂ©sultat, pas une panne).

population

Population d'une COMMUNE (code INSEE 5 car.), d'un DÉPARTEMENT (2-3 car.) OU d'un IRIS infracommunal (9 car.) — granularitĂ© auto-dĂ©tectĂ©e par la longueur du `code`. Retourne un `LookupResult` discriminĂ© par `found`. - IRIS (9 car., ex `751103701` = commune `75110` + IRIS `3701`) : population totale du quartier au Recensement 2022 (champ `population`, comptes bruts), + `libelle`, `code_commune`, `type_iris` (H/A/D/Z). Source : INSEE RP 2022 (table ingĂ©rĂ©e, gĂ©o 01/01/2024). Maille la plus fine (quartier) pour les villes ; en zone peu dense la commune = 1 IRIS (`type_iris` Z, code `COM+0000`). Pour le profil dĂ©mographique dĂ©taillĂ© d'un Ăźlot ou d'un bassin (Ăąge, CSP, familles, revenu), utiliser `profil_iris`. - Commune (5 car., ex `75056` Paris, `13055` Marseille, `2A004` Ajaccio) : PMUN/PCAP/PTOT. Source INSEE Melodi (DS_POPULATIONS_REFERENCE). PMUN = base lĂ©gale DREES. Commune fusionnĂ©e → `found: false` + orientation `autocomplete_commune`. INSEE n'expose PAS les arrondissements PLM (75101-75120, 13201-13216, 69381-69389) → passer la commune-mĂšre ou le dĂ©partement. - DĂ©partement (2-3 car., ex `75`, `59`, `2A`, `971`) : Mayotte (`976`) ABSENTE de Melodi → `lookupNotFound`. Alias acceptĂ©s : `code_insee`/`codeInsee`/`insee`, `code_dept`/`dept`/`departement`/`code_departement`, `code_iris`/`iris` → `code`.

profil_iris

Profil dĂ©mographique au grain QUARTIER (IRIS) — la « demande » d'un territoire (Ăąge, CSP, familles, revenu), Ă  croiser avec l'offre de soins pour l'aide Ă  l'implantation. Source : INSEE RP 2022 + FILOSOFI 2021 (tables ingĂ©rĂ©es, gĂ©o 01/01/2024). Retourne un `LookupResult` discriminĂ© par `found`. EntrĂ©e : EXACTEMENT un de `point` (`lat`+`lon`) OU `code_iris` (9 car.). `rayon_km` optionnel (0 < r ≀ 10) → DEUX modes : - SANS `rayon_km` → profil de l'ÎLOT seul (~2000 hab) sous le point / du code. `mode: "ilot"`, `revenu_median` = mĂ©diane rĂ©elle de l'Ăźlot. - AVEC `rayon_km` → AGRÉGAT du BASSIN = Ăźlots dont le CENTROÏDE est dans le disque (chaque Ăźlot comptĂ© 1 fois). `mode: "bassin"`, `population_bassin`, `nb_iris_agreges`, et `revenu_median_pondere` = PROXY (moyenne pondĂ©rĂ©e population des mĂ©dianes des Ăźlots couverts — PAS une vraie mĂ©diane de bassin) + `couverture` {`revenu_pct_population`, `iris_revenu_manquants`} car FILOSOFI ne couvre que les communes ≄5000 hab. Les parts `age` (part_65_plus/75_plus) et `csp` (cadres, prof_interm, employĂ©s, ouvriers, agriculteurs, artisans_comm, retraitĂ©s, autres) sont des ratios sur comptes bruts (ÎŁ/ÎŁ). Pour une simple population de commune/dept, utiliser `population`. `not_found` motivĂ© si code absent ou point hors mĂ©tropole / en mer.

Documentation Overview

france-data-mcp

MCP TypeScript qui croise et rĂ©concilie 13 rĂ©fĂ©rentiels publics français (INSEE SIRENE, IRIS & Melodi, FINESS DREES, RPPS / Annuaire SantĂ© ANS, Annuaire SantĂ© Ameli, Centres de SantĂ© CNAM, DVF / DGFiP, Sit@del / SDES, PLU via apicarto, IGN GĂ©oplateforme, geo.api.gouv.fr & Recherche Entreprises DINUM). DĂ©tecte les SIRET fermĂ©s invisibles cĂŽtĂ© DREES, distingue site vs groupe, croise l'offre de soins avec la dĂ©mographie au quartier, Ă©value le potentiel immobilier d'un site (prix DVF €/mÂČ, permis de construire, zones AU du PLU), expose la fraĂźcheur de chaque source.

License: MIT CI MCP npm smithery badge

đŸ‡«đŸ‡· Documentation principale en français. English version →


Installation

Option 1 — URL distante (claude.ai, Claude Code, Cursor)

https://france-data-mcp.vercel.app/mcp

ClientConfig
claude.aiSettings → Connectors → Add custom connector → URL ci-dessus
Claude Code~/.claude.json → mcpServers → { "type": "http", "url": "..." }
Cursor~/.cursor/mcp.json → mĂȘme configuration

Option 2 — Wrapper npm stdio (Claude Desktop natif, autres clients)

config.json
{
  "mcpServers": {
    "france-data": {
      "command": "npx",
      "args": ["-y", "france-data-mcp"]
    }
  }
}

Le wrapper forwarde stdio → endpoint HTTPS distant. Aucune DB locale à provisionner. Override possible : FRANCE_DATA_MCP_URL=https://mon-miroir.example/mcp.

Détails par client + self-hosting : docs/installation-claude.md.


Pourquoi ce projet

Les APIs officielles (INSEE, FINESS DREES, RPPS ANS, Annuaire Ameli, Centres de SantĂ© CNAM, IGN, DINUM) existent mais sont Ă©clatĂ©es, sous-documentĂ©es et pleines de piĂšges : rate limits, formats CSV propriĂ©taires, latence DREES de 1-2 mois, diffusion partielle INSEE, mappings inconsistants Ameli ↔ RPPS.

france-data-mcp est le premier MCP qui croise factuellement ces sources pour rĂ©pondre Ă  des questions concrĂštes — cartographie d'offre de soins, Ă©tude de marchĂ© territoriale, journalisme local, civic-tech.


PĂ©rimĂštre — 13 sources publiques croisĂ©es

  • đŸ—ș Territoire (2) : geo.api.gouv.fr (DINUM, communes), IGN GĂ©oplateforme (gĂ©ocodage)
  • đŸ„ SantĂ© (3) : FINESS / ANS (~105 K Ă©tablissements en service, DOM inclus — flux JSON quotidien qui remplace le CSV DREES arrĂȘtĂ© en juillet 2026), Annuaire SantĂ© Ameli (~466 K libĂ©raux), RPPS / ANS (~2,28 M PS actifs)
  • đŸ©ș Centres de SantĂ© (1) : Annuaire santĂ© CNAM (~3 K structures L.6323-1 CSP, sync hebdomadaire)
  • 📊 DĂ©mographie infracommunale (2) : INSEE IRIS (~48,6 K quartiers — RP 2022, FILOSOFI 2021 revenu, contours IGN) + INSEE Melodi (population de rĂ©fĂ©rence)
  • 🏱 Entreprises (2) : DINUM Recherche Entreprises + INSEE SIRENE V3.11
  • đŸ—ïž Immobilier (3) : ventes fonciĂšres DVF / DGFiP (€/mÂČ, cache paresseux PostGIS), permis de construire Sit@del via API DiDo / SDES (live), zones AU du PLU via apicarto / IGN (live)

Cross-source : rĂ©conciliation FINESS ↔ RPPS ↔ SIRENE pour dĂ©tecter SIRET fermĂ©s, rebrandings, raisons sociales pĂ©rimĂ©es.


Outils MCP (36 tools)

đŸ—ș Territoire (4)

autocomplete_commune · get_commune_by_code · geocode_adresse · reverse_geocode

🏱 Entreprises (3)

entreprises_in_radius · entreprise_by_siren (+ fallback INSEE SIRENE V3.11) · etablissement_by_siret

đŸ„ Établissements santĂ© FINESS (3)

etablissements_finess_in_radius · etablissements_finess_by_categorie · etablissement_by_finess

24 familles couvrant ~92 % du volume. Source ANS publiĂ©e quotidiennement, ingĂ©rĂ©e le 1á”‰Êł et le 15 du mois.

đŸ‘šâ€âš•ïž Professionnels libĂ©raux Ameli (2)

professionnels_in_radius · professionnels_par_specialite_dept

Libéraux conventionnés uniquement (~462 K). Découverte des codes spécialité/type_ps : lister_nomenclature (voir ci-dessous).

đŸ©ș Tous les PS — RPPS / Annuaire SantĂ© ANS (5)

professionnels_rpps_in_radius · professionnels_rpps_par_dept · rpps_dans_etablissement · rpps_search_by_name (fuzzy) · professionnel_by_rpps (+ fallback FHIR ANS)

~2,2 M PS actifs (libéraux + salariés privés + hospitaliers contractuels + agents publics). Par défaut : Civils uniquement.

đŸ©ș Centres de SantĂ© — Annuaire CNAM (2)

centres_sante_in_radius · centres_sante_by_finess

Structures de soins ambulatoires non lucratives (L.6323-1 CSP, ~3 K). Différenciateur vs FINESS famille=124 : expose carte Vitale, APCV et spécialités exercées sur place (Annexe A CNAM, ~70 codes). Coords = centroïde commune. Sync hebdomadaire.

📊 DĂ©mographie & densitĂ©s — INSEE Melodi + IRIS (3)

Population de rĂ©fĂ©rence INSEE croisĂ©e avec RPPS / FINESS — mĂ©thodologie DREES (ratios pour 100 k hab.). Maille IRIS (quartier, ~48,6K zones) pour la DEMANDE, Ă  croiser avec l'offre de soins.

population (IRIS 9 car., commune 5 car. ou dĂ©partement 2-3 car. — granularitĂ© auto-dĂ©tectĂ©e par la longueur du code) · densite_sante (cible: professionnels RPPS ou etablissements FINESS — labos, pharmacies, EHPAD, hĂŽpitaux ; + comparaison nationale matview <50 ms) · profil_iris (point ou code_iris, rayon_km?) — profil dĂ©mo d'un Ăźlot ou d'un bassin (Ăąge, CSP, familles, revenu) au RP 2022 + FILOSOFI 2021

🔎 DĂ©couverte des nomenclatures (1)

lister_nomenclature (referentiel: ameli_specialites | ameli_types_ps | rpps_savoir_faire) — codes spĂ©cialitĂ©/type_ps Ameli et savoir_faire RPPS dans un seul tool (remplace les 3 anciens lister_*).

🧭 AgrĂ©gateurs & Ă©tudes composites (4)

  • panorama_sante_territoire (V0.9) — 1 call : population + densitĂ©s mĂ©decins/infirmiers/pharmaciens vs national + count FINESS par famille (labo, pharmacie, EHPAD, MCO, MSP/CPTS) + bloc demande IRIS (profil dĂ©mo commune : Ăąge, CSP, familles, revenu). GranularitĂ© explicite (niveau: commune, niveauEtablissements: departement | indisponible).
  • inspect_site (V0.10) — vue 360 d'un Ă©tablissement en 1 call : identification FINESS + statut administratif SIRENE (resolver SIRET) + PS rattachĂ©s + historique INSEE.
  • panorama_implantation_complet (V0.23) — Ă©tude d'implantation labo en 1 call : 7 sections (territoire, demande IRIS du bassin, concurrents, pourvoyeurs MCO/EHPAD/SSR, prescripteurs RPPS+IDEL, centres de santĂ©, qualitĂ© rĂ©fĂ©rentiels). RĂ©sumĂ©s, jamais de listes brutes ; dĂ©gradation par section.
  • enrichir_concurrents (V0.23) — enquĂȘte sur le top concurrents (statut actif + Ă©quipe + signal M&A + groupe parent), cap dur max=3.

đŸ—ïž Immobilier — potentiel d'un site (2)

dynamique_immobiliere (V0.26) — composite en 1 call : permis de construire (Sit@del / DiDo SDES, live) + zones AU du PLU (apicarto / IGN, live) + ventes de terrains DVF. Sortie 2 registres : note (volume → scoring) / info (quartiers AU + prix → contexte) ; geojson = polygones des zones AU. · cout_foncier (V0.26) — prix mĂ©dian €/mÂČ DVF (P25/P75, n_ventes, pĂ©riode), info seule.

Source DVF / DGFiP (cache paresseux PostGIS, anon lit / service écrit). Permis et zones AU = live (pas d'ingestion). Pensé pour les rapports d'implantation.

🔀 Croisement multi-source (7)

RĂ©conciliation FINESS ↔ RPPS ↔ SIRENE ↔ CNAM — faits bruts sans interprĂ©tation mĂ©tier.

data_freshness · verifier_site_actif · compare_raison_sociale_finess_vs_rpps · compare_adresse_cnam_vs_finess · historique_etablissement · reconcilier_finess_sirene · finess_sirene_coverage_in_radius


Garde-fous publics

  • Rate limit : 60 req/min par IP sur tools/call (les mĂ©thodes meta restent libres). Au-delĂ  : erreur -32000 avec data.retryAfterSeconds.
  • Logs JSON structurĂ©s par requĂȘte : ts, method, tool, ip_hash (SHA-256 salĂ©), duration_ms, outcome. Aucune IP en clair, aucun argument tool persistĂ©.
  • Sentry error monitoring sur les 500 internes (tags mcp.method, mcp.tool, mcp.outcome).
  • RGPD : rĂ©tention 30j sur Axiom, hash IP salĂ©, droits d'accĂšs / effacement. Politique complĂšte dans PRIVACY.md.

Usage intensif : throttler cÎté client ou self-héberger.


État du projet

✅ V0.30.0 — en production. Sur le registry MCP officiel. DĂ©tail : CHANGELOG.

DerniÚre version (V0.30.0) : FINESS alimenté par le flux ANS quotidien, 97,6 % des établissements géolocalisés avec geo_precision par résultat et le SIRET déclaré par l'ANS, vigie post-cron qui ouvre une issue et envoie un email quand un run vert sert une donnée malade. Surface inchangée (13 référentiels / 36 outils).


Contribuer

Ouvrir une issue pour discuter avant d'envoyer une PR.


Licence

MIT — voir LICENSE. Les donnĂ©es restent sous leurs licences respectives :

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
3
Stargazers on the source repository.
npm downloads
1.3k
Package downloads in the last 30 days.
Last commit
4d ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
36
Callable tools this server registers over MCP.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

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Frequently Asked Questions about France Data MCP

It uses French public sources including INSEE, FINESS/DREES, RPPS/ANS, Annuaire Santé Ameli, CNAM, IGN, DINUM, DVF/DGFiP, Sit@del/SDES, and apicarto.

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Technical Specs & Signals

CategoryđŸ—șLocation Services
PricingFree
More technical detailsExpand â–Ÿ
TransportSTDIO
RuntimeNode.js
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor
Last updatedSep 7, 2026
11/11 checks healthy over the last 33d
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars3
GitHub Star CountTotal stargazers on GitHub representing community popularity (3 stars).
Last commit4d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Sep 7, 2026
npm downloads1,300/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
73Quality signal: Great · 73/100How this signal is calculated â–Ÿ
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity8/15
Community engagement0/10

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Scanned 27d ago via OSV.dev · france-data-mcp (npm)

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