# MCP Server: Legifrance JORF (Journal Officiel) for AI Agents (`dltik/mcp-server-legifrance`) Actor Apify MCP server exposing 6 tools to query the French Journal Officiel (JORF) - laws, decrees, arretes, decisions - via DILA Open Data. AI agents ready. No API key needed. $0.01 per tool call. - **URL**: https://apify.com/dltik/mcp-server-legifrance.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** Developer tools, Business, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $10.00 / 1,000 tool calls This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Legifrance MCP Server - French Journal Officiel (JORF) for AI Agents (Laws, Decrees, Arretes) > Apify-hosted **Legifrance MCP server** giving AI agents live access to the French Journal Officiel (JORF) - laws, decrees, arretes, decisions - backed by the free official **DILA Open Data** feed (`echanges.dila.gouv.fr/OPENDATA/JORFSIMPLE/`). 6 tools, no API key, no proxy, no OAuth. **$0.01 per tool call**. Bookmark this Legifrance MCP Server - Apify ranks actors by bookmarks, so it directly helps this server stay visible on the Apify Store. ### What is the Legifrance MCP Server? The **Legifrance MCP Server** is an Apify actor implementing the [Model Context Protocol](https://modelcontextprotocol.io/) for the French [Journal Officiel](https://www.legifrance.gouv.fr/), the official daily publication of every French law, decree, ministerial arrete, decision and circulaire. This MCP server fetches the daily JORF archives published by [DILA](https://www.dila.premier-ministre.gouv.fr/) (Direction de l'information legale et administrative) and exposes 6 tools that your AI agent can call directly. Wire it into Claude Desktop, Cursor, or Continue.dev to give your agent live read access to French primary legal sources - search a JORF issue, fetch a specific decree, list every law promulgated in the past month. ### Why this exists (Light Legifrance) The full [PISTE Legifrance API](https://api.piste.gouv.fr/) requires manually registering a free OAuth2 client (cannot be done headlessly, gates the use case for agents). This actor takes the same primary source - the official DILA JORF dumps - and serves it through a simple MCP interface. The data is identical: laws, decrees, arretes published in the Journal Officiel of the French Republic. Coverage: the rolling ~10 most recent months of JORF (DILA's retention window for the public open-data feed). For older archives, use the static historical dumps on data.gouv.fr. ### Use cases - **Legal-research agents** - "Find the JORF entry for LOI n.2026-381 of 19 May 2026" - **Compliance monitoring** - daily scan of new arretes from `Ministere du travail` affecting payroll - **Public-sector intelligence** - "Has any decree been signed in the last 14 days mentioning `transition ecologique`?" - **Government-contract teams** - cross-reference JORF dates with [BOAMP](https://apify.com/dltik/boamp-fr-scraper) tender publications - **Newsroom / journalism bots** - feed the latest LOI promulgations into a daily summary pipeline ### Tools available | Tool | What it returns | | --- | --- | | `list_jorf_days(days)` | Which calendar dates have an available JORF archive (rolling window). | | `get_jorf_summary(date)` | Table of contents + per-nature counts for one JORF issue. | | `search_jorf(date, query, limit)` | Full-text search within one JORF day (title + visas + notice + body). | | `get_jorf_text(date, text_id)` | Full text of a specific JORF entry by `JORFTEXT...` id. | | `list_recent_laws(days, nature, limit)` | List recent LOI / DECRET / ARRETE / DECISION across N days. | | `search_text_id(text_id)` | Locate a JORFTEXT id by scanning recent days. | | `list_tools` | Free - schema discovery. | ### Input ```json { "mode": "call_tool", "tool_name": "search_jorf", "arguments": { "date": "2026-05-19", "query": "transition ecologique", "limit": 10 } } ```` ### Output (sample) ```json { "id": "JORFTEXT000054113360", "nature": "LOI", "title": "LOI n. 2026-381 du 19 mai 2026 visant a soutenir les collectivites territoriales dans la prevention et la gestion des inondations", "num": "2026-381", "nor": "TECX2506131L", "date_publi": "2026-05-20", "date_texte": "2026-05-19", "ministere": null, "id_eli": "https://www.legifrance.gouv.fr/eli/loi/2026/5/19/TECX2506131L/jo/texte", "legifrance_url": "https://www.legifrance.gouv.fr/eli/loi/2026/5/19/TECX2506131L/jo/texte", "body_excerpt": "L'Assemblee nationale et le Senat ont adopte. Le President de la Republique promulgue la loi dont la teneur suit ..." } ``` ### Pricing **PAY\_PER\_EVENT - $0.01 per tool call** (= $10 per 1,000 calls). The `list_tools` discovery call is free. No charge on errors. Result count does not affect the charge - one tool call is one charge. ### FAQ **What's the latency on new JORF entries?** DILA publishes the daily JORFSIMPLE archive a few hours after the Journal Officiel comes out (typically the same evening or the next morning). This MCP server reads the live index, so new days appear automatically. **Does this cover the full Code du travail / Code civil?** No - only the *JORF* (the daily Journal Officiel containing newly published / modified texts). For consolidated codes you would need PISTE OAuth access. JORF gives you the primary law as published, which is the canonical source. **Why is the coverage limited to ~10 months?** That's the rolling window DILA keeps live on `echanges.dila.gouv.fr`. For historical archives back to 1990, see the bulk dump on [data.gouv.fr](https://www.data.gouv.fr/datasets/jorf-les-donnees-de-l-edition-lois-et-decrets-du-journal-officiel/). **Why MCP and not just a scraper?** An MCP server lets your AI agent chain queries naturally: "List recent LOI, then fetch the full text of the first one, then search the day's JORF for related decrees." For one-shot bulk extraction, [BOAMP Scraper](https://apify.com/dltik/boamp-fr-scraper) (tender announcements) and [BODACC MCP Server](https://apify.com/dltik/mcp-server-bodacc) (commercial court) make a strong FR public-data triad with this actor. *** Found this useful? Bookmark this Legifrance MCP Server - it's the strongest signal for Apify Store ranking. #### Related actors - [BODACC MCP Server](https://apify.com/dltik/mcp-server-bodacc) - 4.5M French commercial court announcements - [Pappers MCP Server](https://apify.com/dltik/mcp-server-pappers) - 26M French companies (SIREN/SIRET, dirigeants, NAF) - [INPI MCP Server](https://apify.com/dltik/mcp-server-inpi) - French trademark + patent registry - [Data Gouv FR MCP Server](https://apify.com/dltik/mcp-server-data-gouv) - DPE / DVF / BAN / INSEE - [BOAMP FR Scraper](https://apify.com/dltik/boamp-fr-scraper) - French public-tender announcements License: MIT - Author: [dltik](https://apify.com/dltik) # Actor input Schema ## `mode` (type: `string`): list\_tools (free, returns tool catalog) or call\_tool (charged $0.01 per call). ## `tool_name` (type: `string`): Tool to invoke. Use mode=list\_tools to discover the full schema of each tool. ## `arguments` (type: `object`): Arguments for the chosen tool (e.g. date, query, text\_id). See list\_tools mode for the per-tool schema. ## Actor input object example ```json { "mode": "call_tool", "tool_name": "list_jorf_days", "arguments": { "days": 7 } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "arguments": { "days": 7 } }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/mcp-server-legifrance").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "arguments": { "days": 7 } } # Run the Actor and wait for it to finish run = client.actor("dltik/mcp-server-legifrance").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "arguments": { "days": 7 } }' | apify call dltik/mcp-server-legifrance --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/mcp-server-legifrance", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP Server: Legifrance JORF (Journal Officiel) for AI Agents", "description": "Apify MCP server exposing 6 tools to query the French Journal Officiel (JORF) - laws, decrees, arretes, decisions - via DILA Open Data. AI agents ready. No API key needed. $0.01 per tool call.", "version": "1.0", "x-build-id": "tC6G4EuTbGGTh52zb" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~mcp-server-legifrance/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-mcp-server-legifrance", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dltik~mcp-server-legifrance/runs": { "post": { "operationId": "runs-sync-dltik-mcp-server-legifrance", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dltik~mcp-server-legifrance/run-sync": { "post": { "operationId": "run-sync-dltik-mcp-server-legifrance", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "mode": { "title": "Mode", "enum": [ "call_tool", "list_tools" ], "type": "string", "description": "list_tools (free, returns tool catalog) or call_tool (charged $0.01 per call).", "default": "call_tool" }, "tool_name": { "title": "Tool name", "enum": [ "list_jorf_days", "get_jorf_summary", "search_jorf", "get_jorf_text", "list_recent_laws", "search_text_id" ], "type": "string", "description": "Tool to invoke. Use mode=list_tools to discover the full schema of each tool.", "default": "list_jorf_days" }, "arguments": { "title": "Arguments", "type": "object", "description": "Arguments for the chosen tool (e.g. date, query, text_id). See list_tools mode for the per-tool schema." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```