eurostat-mcp-suite

eurostat-mcp-suite

MCP server for Eurostat statistics, enabling seamless search, query, and analysis of over 8,900 EU datasets with support for SDMX, DuckDB SQL, NUTS regional filtering, and CSV export.

Category
访问服务器

README

<div align="center">

🇪🇺 eurostat-mcp-suite

The Unified Model Context Protocol (MCP) Server for Eurostat Statistics & EU Data Analysis

Seamlessly search, query, and analyze 8,900+ official European Union statistical datasets via MCP.
Supports SDMX 3.0, SDMX 2.1 Comext (International Trade), DuckDB In-Memory SQL Canvas, NUTS Regional Levels, CSV Exports, Resources, and Prompts.

Python MCP SDK FastMCP DuckDB License

</div>


🌟 Overview

eurostat-mcp-suite is a unified, high-performance MCP server designed to provide AI Agents (Claude Desktop, Cursor, Roo Code, Antigravity CLI, Windsurf, Goose, Zed) with complete access to official Eurostat data.

It combines all capabilities into one robust, clean architecture:

  1. Full API Coverage: Connects to both Eurostat SDMX 3.0 (economy, demography, health, energy) and SDMX 2.1 Comext (international trade with DS- prefixes).
  2. DuckDB SQL Dataframe Canvas: Stages complete datasets into an in-memory DuckDB database so AI agents can execute read-only SELECT queries without blowing context window token limits.
  3. NUTS Regional Filtering: Filter geographic observations by NUTS regional levels (aggregate, country, nuts1, nuts2, nuts3).
  4. Catalogue Discovery: Tokenized search with cursor pagination and Eurostat theme tree navigation.
  5. Local CSV Exporting: Export single or batch datasets directly to local CSV files.
  6. Native Resources & Prompts: Standardized eurostat:// URI resources and guided analytical workflows.

⚡ Agent Auto-Installation Prompt

You can copy and paste the prompt below directly to your AI Assistant (Cursor, Roo Code, Antigravity CLI, Windsurf, Claude) to let it automatically configure and verify eurostat-mcp-suite:

Please read the instructions from https://github.com/ManoloZocco/eurostat-mcp-suite and automatically install the Eurostat MCP Suite server for my environment:
1. Detect my OS (macOS/Windows/Linux) and current client editor (Claude Desktop, Cursor, Roo Code, VS Code, Windsurf, AGY).
2. Check if Python 3.10+ and `uv` (or `pip`) are available.
3. Clone https://github.com/ManoloZocco/eurostat-mcp-suite.git to a persistent directory if not present.
4. Add `eurostat-mcp-suite` to my client's MCP configuration file (e.g. claude_desktop_config.json, mcp_config.json, settings.json).
5. Verify that the server starts successfully and test `search_datasets("GDP")`.

🧰 Available Tools (12 Tools)

🔍 Discovery & Catalogue Navigation

Tool Description
search_datasets(query, limit, cursor) Search Eurostat catalogue by keyword with tokenized matching & cursor pagination
browse_themes(theme_code) Drill down Eurostat top-level statistical themes (Economy, Population, Trade, Energy, etc.)
list_popular_datasets(category) List pre-curated high-value Eurostat datasets by domain

📊 Metadata & Data Retrieval

Tool Description
get_dataset_info(dataset_id) Inspect dataset title, dimensions, observation count, and sample values
get_dimension_values(dataset_id, dimension_code, nuts_level) List valid codes for a dimension with optional NUTS regional filtering (country, nuts1, nuts2, nuts3)
query_dataset(dataset_id, filters, nuts_level, since_period, until_period, last_n_periods, limit) Query decoded statistical observations with OBS_FLAG status markers

🦆 In-Memory DuckDB SQL Canvas

Tool Description
download_dataset_to_sql(dataset_id, table_name, filters) Download complete dataset into an in-memory SQL table for high-speed analysis
sql_query(query) Run read-only SQL SELECT queries across staged DuckDB tables
list_staged_tables() List currently staged SQL tables and row counts
describe_table(table_name) Inspect table schema and sample rows

📁 Local File Export

Tool Description
export_to_csv(dataset_id, filepath, filters) Save dataset observations directly to a local CSV file
export_multiple_datasets(dataset_ids, output_dir) Batch export multiple datasets to a target directory

🔗 Resources & Prompts

📦 MCP Resources

  • eurostat://datasets/{query}: Live search resource matching keywords.
  • eurostat://dataset/{code}/dimensions: Dimension structure resource for a dataset.
  • eurostat://themes: Root theme tree resource.
  • eurostat://popular: Pre-curated popular datasets list resource.

💡 MCP Prompts

  • explore_topic(topic): Guided step-by-step workflow to analyze any European statistical topic.
  • compare_countries(indicator_dataset, countries): Template for cross-country EU comparative analysis.
  • trade_analysis(trade_dataset, reporter): Template for EU international trade & Comext statistical analysis.

🚀 Installation & Configuration

Prerequisites

  • Python 3.10+
  • uv (Recommended, curl -LsSf https://astral.sh/uv/install.sh | sh) or pip

1. Claude Desktop

Add the following to your claude_desktop_config.json:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

With uv (recommended):

{
  "mcpServers": {
    "eurostat-suite": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/eurostat-mcp-suite",
        "run",
        "server.py"
      ]
    }
  }
}

With standard python:

{
  "mcpServers": {
    "eurostat-suite": {
      "command": "python",
      "args": [
        "/path/to/eurostat-mcp-suite/server.py"
      ]
    }
  }
}

2. Cursor IDE

  1. Open Cursor Settings -> Features -> MCP.
  2. Click + Add New MCP Server.
  3. Set Name: eurostat-suite
  4. Set Type: command
  5. Set Command: uv --directory /path/to/eurostat-mcp-suite run server.py

Alternatively, add to your Cursor .cursor/mcp.json:

{
  "mcpServers": {
    "eurostat-suite": {
      "command": "uv",
      "args": ["--directory", "/path/to/eurostat-mcp-suite", "run", "server.py"]
    }
  }
}

3. VS Code (Roo Code / Cline / MCP Extension)

In your VS Code settings.json or Roo Code / Cline MCP settings (cline_mcp_settings.json):

{
  "mcpServers": {
    "eurostat-suite": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/eurostat-mcp-suite",
        "run",
        "server.py"
      ]
    }
  }
}

4. Windsurf / Codeium

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "eurostat-suite": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/eurostat-mcp-suite",
        "run",
        "server.py"
      ]
    }
  }
}

5. Antigravity CLI / AGY

Run:

agy mcp add eurostat-suite -- command uv --directory /path/to/eurostat-mcp-suite run server.py

6. Goose CLI

Run:

goose mcp add eurostat-suite -- command uv --directory /path/to/eurostat-mcp-suite run server.py

📖 Usage Examples

Example 1: High-Speed GDP Analysis via DuckDB SQL Canvas

User: "Download the annual GDP dataset nama_10_gdp and run a SQL query to show average GDP for Germany, France, and Italy over the last 5 years."

Agent steps:
1. download_dataset_to_sql(dataset_id="nama_10_gdp", table_name="gdp_table")
2. sql_query("SELECT geo, geo_label, AVG(value) as avg_gdp FROM gdp_table WHERE geo IN ('DE', 'FR', 'IT') GROUP BY geo, geo_label ORDER BY avg_gdp DESC")

Example 2: International Trade Analysis (Comext SDMX 2.1)

User: "Query EU extra-trade statistics for dataset DS-045409."

Agent steps:
1. get_dataset_info("DS-045409")
2. query_dataset(dataset_id="DS-045409", filters={"reporter": ["EU27_2020"]}, limit=50)

📄 License

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

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选