{
  "mcpServers": {
    "datagouv": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.data.gouv.fr/mcp"
      ]
    }
  }
}

{
  "isUsingBuiltInNodeForMcp": false,
  "mcpServers": {
    "datagouv": {
      "command": "npx",
      "args": ["mcp-remote", "https://mcp.data.gouv.fr/mcp"]
    }
  }
}

{
  "mcpServers": {
    "datagouv": {
      "url": "https://mcp.data.gouv.fr/mcp",
      "transport": "http"
    }
  }
}

{
  "servers": {
    "datagouv": {
      "url": "https://mcp.data.gouv.fr/mcp",
      "type": "http"
    }
  }
}

{
  "mcpServers": {
    "datagouv": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.data.gouv.fr/mcp"]
    }
  }
}

# Clone the repository
git clone git@github.com:datagouv/datagouv-mcp.git
cd datagouv-mcp

# Run with default settings (port 8000, prod environment)
docker compose up -d

# Run with custom settings
MCP_PORT=8007 DATAGOUV_API_ENV=demo LOG_LEVEL=DEBUG docker compose up -d

# Stop
docker compose down

# Clone the repository
git clone git@github.com:datagouv/datagouv-mcp.git
cd datagouv-mcp

# Install dependencies
uv sync

# Create environment file
cp .env.example .env

# Edit .env as needed (optional)
# MCP_HOST=127.0.0.1
# MCP_PORT=8007
# DATAGOUV_API_ENV=prod
# LOG_LEVEL=INFO

# Load environment variables
set -a && source .env && set +a

# Start the server
uv run main.py

"Find datasets about real estate prices in France"
"Quels jeux de données existent sur la pollution de l'air?"
"Show me population data for Paris"

"What datasets does INSEE publish?"
"List all datasets from the Ministry of Health"

"Give me information about dataset ID abc123"
"What resources are available in this dataset?"

import asyncio
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

async def search_datasets():
    server_params = StdioServerParameters(
        command="npx",
        args=["mcp-remote", "https://mcp.data.gouv.fr/mcp"]
    )
    
    async with stdio_client(server_params) as (read, write):
        async with ClientSession(read, write) as session:
            # Initialize the connection
            await session.initialize()
            
            # Search for datasets
            result = await session.call_tool(
                "search_datasets",
                arguments={"q": "population", "page_size": 5}
            )
            
            print(result)

asyncio.run(search_datasets())

{
  "mcpServers": {
    "datagouv-local": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "http://127.0.0.1:8007"
      ]
    }
  }
}

# docker-compose.yml
services:
  mcp-server:
    build: .
    ports:
      - "8007:8007"
    environment:
      - MCP_HOST=0.0.0.0
      - MCP_PORT=8007
      - MCP_ENV=prod
      - DATAGOUV_API_ENV=prod
      - LOG_LEVEL=INFO
      - SENTRY_DSN=${SENTRY_DSN}
    restart: unless-stopped

# Search for recent environmental datasets from a specific org
result = await session.call_tool(
    "search_datasets",
    arguments={
        "q": "environment climate",
        "organization": "ademe",
        "badge": "climate-change",
        "page_size": 10
    }
)

# Get first page
page1 = await session.call_tool(
    "search_datasets",
    arguments={"q": "transport", "page": 1, "page_size": 20}
)

# Get next page
page2 = await session.call_tool(
    "search_datasets",
    arguments={"q": "transport", "page": 2, "page_size": 20}
)

{
  "isUsingBuiltInNodeForMcp": false,
  "mcpServers": { ... }
}

# Install dev dependencies
uv sync --dev

# Run tests
uv run pytest

# Run with coverage
uv run pytest --cov=src

LOG_LEVEL=DEBUG uv run main.py

DATAGOUV_API_ENV=demo uv run main.py