Countries

Global development indicators — population, GDP, life expectancy, CO₂, and thousands more, for every country and year.

Data from World Bank (CC BY 4.0). See Countries for coverage, freshness and credits.

Your agent reaches these on Vistazo's MCP server, https://mcp.vistazo.ai/mcp, through search_tools and call_tool, as countries__<tool> — for example countries__search_indicators.

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Search World Bank indicators by keyword (e.g. "GDP per capita", "life expectancy"). Returns results: matching indicators with their id, database_id, definition, and coverage — the entry point for every other tool. Optionally verify a country is covered. Sibling ids differ by unit suffix: _CD = current US$ (the headline figure), _KD = constant US$ (growth over time), _PP_CD = PPP international $ (living-standard comparisons), _CN/_KN = local currency — pick by what the chart compares.

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List the indicator ids in a database, paginated in indicators (limit/offset, default 200 per page; the response carries the full count and has_more). Use search_indicators first to find the database_id — and prefer it for discovery, since large databases hold thousands of ids.

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Fetch an indicator's full metadata — definition, methodology, source, limitations, and aggregation_method (how the source computes its regional/income aggregate rows, e.g. 'Weighted average' or 'Sum'). Use to understand exactly what a number measures before charting it, and before quoting an aggregate as a regional average.

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List the dimensions available for an indicator, in dimensions — which years have data (TIME_PERIOD), how many countries (REF_AREA), and breakdowns like SEX/AGE. Call this before get_data to know valid years and filters. REF_AREA is summarized as a count plus a short sample; to check whether a specific country is present, pass contains (e.g. "italy") to search that codelist by code or name.

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Translate a human name into the standardized code the API needs — e.g. "Kenya" → "KEN", "European Union" → "EUU", "female" → "F", "South America" → "M49_005". Returns ranked matches (preferring codes get_data actually accepts); use the top id. A match with dimension COUNTRY_GROUP is a UN M49 geographic subregion: expand it with expand_country_group, never pass it to get_data.

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Expand a group code into its member countries — a World Bank group, e.g. "SAS" (South Asia) or "LIC" (Low income), or a UN M49 geographic subregion, e.g. "M49_005" (South America) → countries [{code, name}] plus country_codes. The seven World Bank regions are EAS, ECS, LCN, MEA, NAC, SAS and SSF; the income groups LIC, LMC, UMC and HIC. Membership is the World Bank's own country list, so SAS holds six economies (no Afghanistan or Pakistan). Use to turn a group into countries for get_data, rank_countries or compare_periods. A subregion has no published aggregate rows; its members carry status "sovereign" or "territory", with sovereign_codes / territory_codes alongside. Pre-computed aggregates (e.g. "EUU", "WLD") can't be expanded but are flagged as usable directly.

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Fetch the actual time-series observations for one indicator — or for up to 10 at once, by passing several ids in indicator_id separated by ";" or ",". Returns rows, one per indicator-country-year (indicator_id, ref_area, time_period, obs_value) — chart-ready, and a multi-indicator result feeds a multi-series chart from ONE call, which is how to build a themed dashboard instead of firing a call per indicator. Also returns the constant unit hoisted out of the rows (single-indicator form), aggregate_codes naming which returned areas are regional/income aggregates rather than countries, and per_indicator carrying each id's own count and coverage note. For particular years, pass years (e.g. [2013, 2023]) and omit limit: each comes back complete for every country, except that one response holds at most 1000 rows (12,000 for a notebook's call — vistazo.call or a data cell), so with several indicators each gets 1000 ÷ indicators (a full year is ~265 rows — three indicators for one year fit whole) and the response marks any it cut INCOMPLETE. Indicators × named years is capped at 20 upstream fetches per call. A wide span with a small limit keeps only the newest years, and the response names the ones it dropped. Breakdowns default to totals unless you filter. For the LATEST year per country, rank_countries with no year picks the most recent year with broad coverage and returns the year it used; here the newest rows come first. Call get_disaggregation first to learn valid years and filters.

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Rank countries by an indicator value for a year — leaderboards and top/bottom lists. Rank the whole world, a group (via country_group like "SAS"), or an explicit set (country_codes). Returns rankings (not rows): rank, country, value, and percentile per entry, plus the database_id/indicator_id ranked and the values' unit (unit_measure code, units code → name; unit_measure is null when the values carry several units). Percentile is position WITHIN the ranked set — areas in the chosen universe with a value that year — so ranking two countries gives 100 and 50, not their world standing.

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Rank countries by how much an indicator CHANGED between two years — "grew the most over the last decade", "fell furthest since 2010". One call returns rows: each country's start value, end value, absolute change and % change, sorted (sort_by change_pct | change | end_value | start_value) and capped by top_n. Do not assemble this from two get_data calls. Regional and income aggregates (EUU, WLD, IDA…) are excluded unless you ask for them, population rides along, and min_population keeps very small economies from dominating a percentage ranking. Both years are compared exactly — an area missing either one is excluded and counted, never silently shifted to a nearby year.