DuckDB Eurostat MCP Server

A Model Context Protocol (MCP) server that enables querying Eurostat data using natural language. This server leverages the DuckDB Eurostat extension to translate human queries into SQL and execute them efficiently against the Eurostat database.

Features

• 🗣️ Natural Language Queries - Ask questions in plain English, get SQL and data back
• 🤖 Flexible LLM Support - Choose from Anthropic, OpenAI, Ollama (local), or Azure OpenAI
• 🚀 DuckDB Powered - Fast query execution with filter pushdown optimization
• 📊 Rich Dataset Access - Access all Eurostat datasets (GDP, unemployment, population, etc.)
• 🔍 Dataset Discovery - Browse and search available datasets
• 📈 Schema Inspection - Understand dataset structure before querying
• 🎯 Direct SQL Support - Execute raw SQL for advanced use cases
• 🔒 Privacy Options - Use local LLMs with Ollama for complete data privacy

Key Differentiator

Unlike other Eurostat MCP implementations that use direct SDMX API calls, this server:

• Uses the DuckDB Eurostat extension for optimized data access
• Provides SQL-based querying with automatic filter pushdown
• Supports natural language to SQL translation via Claude API
• Offers better performance through DuckDB's query optimization

Installation

Prerequisites

• Python 3.10 or higher
• LLM Provider (choose one):
  • Anthropic API key (default, recommended)
  • OpenAI API key
  • Ollama (local, free, no API key needed)
  • Azure OpenAI (enterprise)

Install with pip

# Clone the repository
git clone https://github.com/dar4datascience/duckdb-eurostat-mcp.git
cd duckdb-eurostat-mcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install with your preferred LLM provider
pip install -e ".[anthropic]"  # Anthropic Claude (default)
# OR
pip install -e ".[openai]"     # OpenAI GPT
# OR
pip install -e ".[ollama]"     # Ollama (local)
# OR
pip install -e ".[azure]"      # Azure OpenAI
# OR
pip install -e ".[all-providers]"  # All providers

# For development (includes all providers)
pip install -e ".[dev]"

Configuration

LLM Provider Setup

The server supports multiple LLM providers. Choose the one that fits your needs:

Option 1: Anthropic Claude (Default, Recommended)

export LLM_PROVIDER=anthropic
export ANTHROPIC_API_KEY=your-api-key-here

Get API Key: https://console.anthropic.com/

Option 2: OpenAI GPT

export LLM_PROVIDER=openai
export OPENAI_API_KEY=your-api-key-here

Get API Key: https://platform.openai.com/api-keys

Option 3: Ollama (Local, Free, Private)

export LLM_PROVIDER=ollama
# No API key needed!

Setup:

1. Install Ollama: https://ollama.ai/
2. Pull a model: ollama pull llama3.1
3. Start Ollama: ollama serve

Benefits: No API costs, complete privacy, works offline

Option 4: Azure OpenAI

export LLM_PROVIDER=azure
export AZURE_OPENAI_API_KEY=your-api-key-here
export AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
export AZURE_OPENAI_DEPLOYMENT=your-deployment-name

Claude Desktop Configuration

Add to your Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

With Anthropic (default):

{
  "mcpServers": {
    "duckdb-eurostat": {
      "command": "python",
      "args": ["-m", "duckdb_eurostat_mcp.server"],
      "env": {
        "LLM_PROVIDER": "anthropic",
        "ANTHROPIC_API_KEY": "your-api-key-here"
      }
    }
  }
}

With OpenAI:

{
  "mcpServers": {
    "duckdb-eurostat": {
      "command": "python",
      "args": ["-m", "duckdb_eurostat_mcp.server"],
      "env": {
        "LLM_PROVIDER": "openai",
        "OPENAI_API_KEY": "your-api-key-here"
      }
    }
  }
}

With Ollama (local):

{
  "mcpServers": {
    "duckdb-eurostat": {
      "command": "python",
      "args": ["-m", "duckdb_eurostat_mcp.server"],
      "env": {
        "LLM_PROVIDER": "ollama"
      }
    }
  }
}

See docs/LLM_PROVIDERS.md for detailed configuration guide.

Available Tools

1. query_eurostat

Query Eurostat data using natural language.

Example:

Query: "Get population data for Germany in 2020"

2. list_dataflows

List available Eurostat datasets with optional filtering.

Parameters:

• provider (optional): Filter by provider (e.g., 'ESTAT')
• search (optional): Search term to filter by label
• limit (optional): Maximum results (default: 50)

3. get_dataflow_structure

Get the structure (dimensions and concepts) of a specific dataset.

Parameters:

• provider_id: Provider ID (e.g., 'ESTAT')
• dataflow_id: Dataset ID (e.g., 'DEMO_R_D2JAN')

4. execute_sql

Execute raw SQL queries against the DuckDB Eurostat database.

Parameters:

• sql: SQL query to execute
• limit (optional): Maximum rows to return (default: 100)

5. list_providers

List all available Eurostat API endpoints/providers.

Usage Examples

Natural Language Queries

"Show unemployment rates for EU countries in 2023"
"What was the GDP of France from 2015 to 2020?"
"List population data for Germany by age group"

Direct SQL Queries

-- Get population data for Germany
SELECT * FROM EUROSTAT_Read('ESTAT', 'DEMO_R_D2JAN') 
WHERE geo = 'DE' AND time_period = '2020'
LIMIT 10;

-- List available datasets about GDP
SELECT dataflow_id, label 
FROM EUROSTAT_Dataflows(language := 'en')
WHERE label ILIKE '%GDP%'
LIMIT 20;

-- Get dataset structure
SELECT dimension, concept 
FROM EUROSTAT_DataStructure('ESTAT', 'DEMO_R_D2JAN', language := 'en');

Popular Datasets

• DEMO_R_D2JAN - Population by age, sex, and NUTS-2 region
• UNE_RT_A - Unemployment rates
• NAMA_10_GDP - GDP and main components
• PRC_HICP_MIDX - HICP - Monthly index (inflation)
• COMEXT - International trade data

Development

Setup Development Environment

# Create virtual environment
python -m venv venv
source venv/bin/activate

# Install with dev dependencies
pip install -e ".[dev]"

Run Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=duckdb_eurostat_mcp --cov-report=html

# Run specific test file
pytest tests/test_duckdb_manager.py -v

Code Quality

# Format code
black src/ tests/

# Lint code
ruff check src/ tests/

# Type check
mypy src/

Testing with MCP Inspector

# Install MCP Inspector
npx @modelcontextprotocol/inspector

# Run your server
python -m duckdb_eurostat_mcp.server

Project Structure

duckdb-eurostat-mcp/
├── src/
│   └── duckdb_eurostat_mcp/
│       ├── __init__.py
│       ├── server.py           # Main MCP server
│       ├── duckdb_manager.py   # DuckDB connection management
│       └── query_translator.py # Natural language to SQL
├── tests/
│   ├── test_server.py
│   ├── test_duckdb_manager.py
│   └── test_query_translator.py
├── .windsurf/
│   ├── workflows/              # Development workflows
│   └── memories/               # Project documentation
├── pyproject.toml
└── README.md

Workflows

This project includes helpful workflows in .windsurf/workflows/:

• setup-and-test.md - Setup development environment and run tests
• deploy-to-github.md - Deploy to GitHub with CI/CD
• add-new-feature.md - Add new features to the server

Use them with: /setup-and-test, /deploy-to-github, /add-new-feature

Troubleshooting

DuckDB Extension Not Loading

Ensure you have internet connection on first run to download the extension.

API Key Errors

Verify ANTHROPIC_API_KEY is set correctly in your environment.

Query Performance

Use filters to reduce data volume:

WHERE geo = 'DE' AND time_period >= '2020'

See .windsurf/memories/common-issues.md for more solutions.

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Run tests (pytest)
5. Format code (black src/ tests/)
6. Commit changes (git commit -m 'Add amazing feature')
7. Push to branch (git push origin feature/amazing-feature)
8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• DuckDB Eurostat Extension by ahuarte47
• Model Context Protocol by Anthropic
• Eurostat for providing the data

Related Projects

• eurostat-mcp - Alternative MCP implementation using direct SDMX API
• DuckDB - Fast in-process analytical database

Support

For issues and questions:

• Open an issue on GitHub
• Check .windsurf/memories/common-issues.md for common problems
• Review the workflows in .windsurf/workflows/