datagouv-mcp vs mcp-server-qdrant

Side-by-side comparison to help you pick between these two MCP servers.

	datagouv-mcp by datagouv	mcp-server-qdrant by qdrant
Stars	★ 1,460	★ 1,397
30d uses	—	—
Score	55	55
Official	—	—
Categories	AI / LLM ToolsDatabaseSearch	DatabaseAI / LLM ToolsDeveloper Tools
Language	Python	Python
Last commit	this month	1 mo ago

datagouv-mcp · Summary

Official MCP server for data.gouv.fr that enables AI chatbots to search and analyze French open data.

mcp-server-qdrant · Summary

Official Qdrant MCP server for semantic memory storage and retrieval using vector embeddings.

datagouv-mcp · Use cases

Ask about real estate prices in specific French regions
Retrieve latest demographic data for French cities
Search and analyze public datasets through conversational AI

mcp-server-qdrant · Use cases

Building AI applications with long-term memory capabilities
Code search and retrieval for development environments
Enhancing LLM applications with vector-based semantic search

datagouv-mcp · Install

Installation

Using Public Hosted Server

The recommended approach is to use the public instance at https://mcp.data.gouv.fr/mcp.

Claude Desktop Configuration

Add to your Claude Desktop configuration file:

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

Local Installation with Docker

git clone git@github.com/datagouv/datagouv-mcp.git
cd datagouv-mcp
docker compose up -d

Manual Installation

# Install dependencies
uv sync

# Copy environment file
cp .env.example .env

# Start the server
uv run main.py

mcp-server-qdrant · Install

Installation Options

Using uvx

QDRANT_URL="http://localhost:6333" \
COLLECTION_NAME="my-collection" \
EMBEDDING_MODEL="sentence-transformers/all-MiniLM-L6-v2" \
uvx mcp-server-qdrant

Using Docker

docker build -t mcp-server-qdrant .
docker run -p 8000:8000 \
  -e FASTMCP_SERVER_HOST="0.0.0.0" \
  -e QDRANT_URL="http://your-qdrant-server:6333" \
  -e QDRANT_API_KEY="your-api-key" \
  -e COLLECTION_NAME="your-collection" \
  mcp-server-qdrant

Claude Desktop Configuration

Add to claude_desktop_config.json:

{
  "qdrant": {
    "command": "uvx",
    "args": ["mcp-server-qdrant"],
    "env": {
      "QDRANT_URL": "https://xyz-example.eu-central.aws.cloud.qdrant.io:6333",
      "QDRANT_API_KEY": "your_api_key",
      "COLLECTION_NAME": "your-collection-name",
      "EMBEDDING_MODEL": "sentence-transformers/all-MiniLM-L6-v2"
    }
  }
}

Comparison generated from public README + GitHub signals. Last updated automatically.