World Bank Countries MCP. Map global countries by region, income, or code.

World Bank Country Data: The Definitive Global Metadata Toolset

Forget wrestling with messy spreadsheets or juggling multiple API keys just to map out global data. This server gives your AI agent the full World Bank taxonomy—it's how you nail down country ISO codes, regional groupings, and economic classifications using official World Bank standards.

Your agent uses this toolset for mapping countries based on everything: their income level (you know, HIC or LIC), or where they sit geographically. It lets your AI client build highly accurate filtering and mapping logic right into your workflow without you having to write massive SQL joins.

Core Tools and Mechanisms

list_countries: You can call this tool to get an exhaustive, comprehensive list of every single country the World Bank tracks. It spits out not only the official name but also the capital city and that unique international standard code (the ISO code) for each one.

search_income_levels: Need to narrow down the global count by economics? This tool filters the whole list, letting you pull up only those countries belonging to a specific economic income group. You can target groups like High Income Countries (HIC), Low-Income Countries (LIC), or others based on World Bank classifications.

search_regions: If you just want to know what major geographic blocks exist—like 'East Asia & Pacific' or 'Latin America & Caribbean'—this tool lists and identifies those predefined macro-regions. It gives you the authoritative list of groupings available for filtering your data set.

How You Use This Data

The capabilities here let your agent execute complex data validation and mapping tasks instantly:

• Listing Countries and Codes: When you call list_countries, you retrieve a massive dataset containing every supported country, along with its unique international standard code. This is the foundational layer for any global analysis you run.
• Filtering by Income Level: By using search_income_levels, your agent can limit datasets to specific economic classifications like High Income (HIC) or Low-Income (LIC). You don't have to guess; you just call out the required income group, and it handles the filtering.
• Identifying Major Geographic Regions: If you need to know which established macro-regions a country belongs to—say, 'Sub-Saharan Africa' or 'Middle East & North Africa'—you can use search_regions to list and group them correctly. This keeps your regional data clean and consistent.
• Mapping Metadata to Regions: You give the agent a specific country name, and it identifies exactly which World Bank geographic block that place belongs to. It’s instant mapping for global grouping.
• Validating Country Codes: Need to check if a country code or name you're working with actually follows established ISO standards provided by the World Bank? You use this function to validate codes against the official standard, so your data is always clean and trustworthy.

It’s all about precision. This toolset ensures that whether you're analyzing poverty metrics, tracking infrastructure spending, or just building a comprehensive list of global participants, your AI agent uses authoritative numbers every single time.