# MCP Server: Data Gouv (`dltik/mcp-server-data-gouv`) Actor MCP Server: Data Gouv: an MCP server exposing 6 tools for AI agents. HTTP-only, no API key. Pay $0.01/tool-call. - **URL**: https://apify.com/dltik/mcp-server-data-gouv.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** AI, Developer tools, Business - **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 ## MCP Server: Data Gouv > MCP Server: Data Gouv: an MCP server exposing 6 tools for AI agents. **$0.01 per tool-call**. ⭐ **Bookmark this MCP Server: Data Gouv** — Apify ranks actors by bookmarks, so it directly helps the visibility of this actor on the Apify Store. ### What is the MCP Server: Data Gouv? The **MCP Server: Data Gouv** is an Apify-hosted MCP server exposing **6 tools** (`search_dpe`, `get_dpe_by_id`, `search_dvf`, `geocode_address`, `reverse_geocode`, `insee_codes_postaux`) for AI agents (Claude, Cursor, Continue) to query ai dev data. HTTP-only, no API key, runs on the Apify cloud. ### Use cases - **AI agent integration** — let Claude/Cursor/Continue call MCP Server: Data Gouv tools directly from chat. - **Automated research workflows** — chain tool calls inside an agent for multi-step lookups. - **Data enrichment pipelines** — augment your CRM/database via agent automation. - **MCP catalog expansion** — add this server to your existing MCP stack. - **Prototype before building** — validate an AI use case without writing API client code. ### Input ```json { "mode": "call_tool", "tool_name": "search_dpe", "arguments": { "limit": 5 } } ```` ### Output ```json { "result_field_1": "value extracted by the tool", "result_field_2": "another field", "metadata": { "tool": "search", "query": "example" } } ``` ### Pricing **PAY\_PER\_EVENT — $0.01 per tool-call** (= per 1,000 = the same × 1,000). Failed runs are not charged. `list_tools` mode is free for MCP servers (discovery). ### FAQ — MCP Server: Data Gouv alternatives **Why MCP Server: Data Gouv on Apify vs writing it yourself?** Maintenance. APIs change. CAPTCHAs rotate. Anti-bot fingerprints update. This actor handles all that — you focus on the data. **Can I run it from Python / Node / curl?** Yes. Use Apify's `run-sync-get-dataset-items` endpoint with your token, or the official Apify SDK. **What about rate limits?** The actor handles backoff automatically. For high volume, queue runs sequentially or use Apify's run-pool feature. *** ⭐ **Found this MCP Server: Data Gouv useful? Bookmark it** — Apify ranks actors by bookmarks, it's the strongest signal for Store visibility. #### Related actors - [Pappers MCP Server](https://apify.com/dltik/mcp-server-pappers) — French B2B data for AI agents - [SEC EDGAR MCP Server](https://apify.com/dltik/mcp-server-sec-edgar) — 10K+ US public companies for AI agents - [HackerNews MCP Server](https://apify.com/dltik/mcp-server-hackernews) — 30M HN stories for AI agents License: MIT · Author: [dltik](https://apify.com/dltik) # Actor input Schema ## `mode` (type: `string`): list\_tools (free, returns tool catalog) or call\_tool (charged $0.01 per call). ## `tool_name` (type: `string`): Tool to invoke. Use mode=list\_tools to discover the full catalog. ## `arguments` (type: `object`): Arguments for the chosen tool. See list\_tools mode for full schema per tool. ## Actor input object example ```json { "mode": "call_tool", "tool_name": "search_dpe", "arguments": { "limit": 5 } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "arguments": { "limit": 5 } }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/mcp-server-data-gouv").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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": { "limit": 5 } } # Run the Actor and wait for it to finish run = client.actor("dltik/mcp-server-data-gouv").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": { "limit": 5 } }' | apify call dltik/mcp-server-data-gouv --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/mcp-server-data-gouv", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "MCP Server: Data Gouv", "description": "MCP Server: Data Gouv: an MCP server exposing 6 tools for AI agents. HTTP-only, no API key. Pay $0.01/tool-call.", "version": "1.0", "x-build-id": "zVLdSo82btmxuasiK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~mcp-server-data-gouv/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-mcp-server-data-gouv", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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-data-gouv/runs": { "post": { "operationId": "runs-sync-dltik-mcp-server-data-gouv", "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-data-gouv/run-sync": { "post": { "operationId": "run-sync-dltik-mcp-server-data-gouv", "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", "required": [ "mode" ], "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": [ "search_dpe", "get_dpe_by_id", "search_dvf", "geocode_address", "reverse_geocode", "insee_codes_postaux" ], "type": "string", "description": "Tool to invoke. Use mode=list_tools to discover the full catalog.", "default": "search_dpe" }, "arguments": { "title": "Arguments", "type": "object", "description": "Arguments for the chosen tool. See list_tools mode for full schema per tool." } } }, "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 } } } } } } } } } } ```