berba-q/faostat-mcp

MCP server that exposes the full FAOSTAT API as tools for AI assistants — query UNFAO Food & Agriculture Statistics in natural language via Claude, Cursor, or any MCP-compatible client. # FAOSTAT MCP Server > Query UN food and agriculture statistics with AI — powered by the Model Context Protocol An MCP (Model Context Protocol) server that exposes the full FAOSTAT API as tools for AI assistants. Connect any MCP-compatible client — Claude, Cursor, Windsurf, Zed, or your own agent — to the world's most comprehensive database of food, agriculture, fisheries, forestry, and nutrition statistics, covering 245 countries and territories from the United Nations Food and Agriculture Organization (FAO). **Keywords:** FAOSTAT, MCP server, Model Context Protocol, AI agriculture data, FAO statistics, food security AI, agricultural data Python, UN data, crop production statistics, Claude, Cursor, Windsurf --- ## Why Use This? Researchers, data journalists, policy analysts, and developers can ask natural-language questions and get answers directly from FAOSTAT — without writing a single API call. Your AI assistant handles domain discovery, filtering, and interpretation automatically. **Who is this for?** - Agricultural economists and food security researchers - Journalists and policy analysts working with FAO data - Developers building AI pipelines on top of FAOSTAT - Anyone who wants to explore crop, trade, nutrition, or emissions data conversationally --- ## What is FAOSTAT? FAOSTAT is the statistical database of the United Nations Food and Agriculture Organization (FAO). It is the world's most comprehensive freely available source of data on food and agriculture, covering: - **Crop and livestock production** — yields, harvested area, and quantities for hundreds of commodities - **Trade** — import/export volumes and values between countries - **Food security** — prevalence of undernourishment, dietary energy supply, and access indicators - **Emissions** — greenhouse gas emissions from agriculture, land use, and food systems - **Forestry and fisheries** — production and trade data - **Prices, inputs, and population** — producer prices, fertilize …