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Query official statistics through MCP, with periods, places and citable sources in every answer.

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Streamable HTTP · MCP 2025-11-25
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6 tools
compareCompare places
Read-onlyIdempotent
Inspect

Compare one indicator across 2 to 10 places for the same period, using one shared source and definition whenever possible. Use it for "how does X compare with Y and Z". Places can mix levels, for example a city, a larger city and its region. Example: {"indicator": "registered_unemployment_rate", "places": ["Mataró", "Barcelona", "Cataluña"]}. Returns {indicator, period, comparable, values: [{place, value, period?, status?}], source or sources, notes?}. When comparable is false the values come from different sources (and sometimes periods) and notes explain why; mention it in your answer. For unemployment in municipalities use registered_unemployment_rate: the survey unemployment_rate is not published below province level.

ParametersJSON Schema
NameRequiredDescriptionDefault
periodNoOptional. "2024" (year), "2024-Q3" (quarter), "2024-S1" (half year) or "2024-09" (month). Omit for the latest value.
placesYesPlace names or ids.
countryNoOptional ISO 3166-1 alpha-2 code to disambiguate the place, for example "ES" or "US".
indicatorYesIndicator id from search_indicators, for example "population", "registered_unemployment_rate", "unemployment_rate", "cpi_annual_change", "net_income_per_person".
get_seriesGet a time series
Read-onlyIdempotent
Inspect

Get the time series of an indicator for one place, oldest to newest, from one source so the points are comparable. Use it for trends: "evolution of the CPI by month", "population of Mataró since 2015". Example: {"indicator": "cpi_annual_change", "place": "España", "from": "2023-01"}. Returns {indicator, place, frequency, points: [[period, value], ...], total_points, truncated?, flags?: {period: status}, gaps?, source, other_frequencies?, longer_history?, note?, projections_available?}. gaps lists periods the source did not publish. Projections (for example population to 2050) are never mixed into points. Pass include_projections: true to get them in a separate projections block {label, vintage, points, source}; always say a projected figure is a projection. Free and Builder plans receive 60 points: the latest ones, or the first ones from "from" when you pass it. truncated says when history was cut.

ParametersJSON Schema
NameRequiredDescriptionDefault
toNoOptional last period, inclusive.
fromNoOptional first period, inclusive. Same formats as period.
placeYesPlace name or id. Examples: "Mataró", "Barcelona", "provincia de Barcelona", "Cataluña", "España", "Germany", "EU", "es-mun-08121", "08121" (INE code), "ES51" (NUTS), "Texas", "Travis County, Texas", "us-county-48453", "fips:48453" (US county FIPS).
countryNoOptional ISO 3166-1 alpha-2 code to disambiguate the place, for example "ES" or "US".
frequencyNoOptional. Force a frequency when the indicator exists in several (for example monthly and annual unemployment).
indicatorYesIndicator id from search_indicators, for example "population", "registered_unemployment_rate", "unemployment_rate", "cpi_annual_change", "net_income_per_person".
include_projectionsNoAlso return the publisher projections after the last observed period, kept apart from points. Default false.
get_valueGet one value
Read-onlyIdempotent
Inspect

Get one official figure for an indicator and place: the latest by default, or a given period. Use it for questions like "population of Mataró", "inflation in Spain in 2024-09", "unemployment rate in Cataluña", "unemployment rate in Texas". Example: {"indicator": "population", "place": "Mataró"}. Returns {indicator: {id, name, unit}, place: {id, name, level}, period, value, status?, source: {name, title, url, retrieved, published?, citation, inputs?}, note?}. note is a caveat about the source series served. Always cite source.citation or source.url when you answer. When source.via is present (Data Commons), the publisher is still the original agency; the citation already names both. status "provisional" or "estimated" means the figure may be revised; say so. status "low_reliability" means the publisher flags the figure as of low reliability (usually a small survey sample); say so and treat it as a rough indication. If the indicator is not published for that place you get an error that names the levels where it exists and related indicators that do have data.

ParametersJSON Schema
NameRequiredDescriptionDefault
placeYesPlace name or id. Examples: "Mataró", "Barcelona", "provincia de Barcelona", "Cataluña", "España", "Germany", "EU", "es-mun-08121", "08121" (INE code), "ES51" (NUTS), "Texas", "Travis County, Texas", "us-county-48453", "fips:48453" (US county FIPS).
periodNoOptional. "2024" (year), "2024-Q3" (quarter), "2024-S1" (half year) or "2024-09" (month). Omit for the latest value.
countryNoOptional ISO 3166-1 alpha-2 code to disambiguate the place, for example "ES" or "US".
frequencyNoOptional. Force a frequency when the indicator exists in several (for example monthly and annual unemployment).
indicatorYesIndicator id from search_indicators, for example "population", "registered_unemployment_rate", "unemployment_rate", "cpi_annual_change", "net_income_per_person".
rank_placesRank places
Read-onlyIdempotent
Inspect

Rank every place of one level inside an area by an indicator: all countries of the world, EU countries, US states, the counties of a state, the regions of a country, the municipalities of a Spanish province. Use it for "which state has the highest unemployment", "top 10 countries by GDP per capita", "poorest counties in Texas", "EU countries with the lowest inflation". level is the level of the ranked places (country, region, province, municipality); within is the area they belong to. US states are regions of "United States"; US counties are provinces of a state; EU NUTS 2 regions are regions of "EU" or of a country. Example: {"indicator": "unemployment_rate", "level": "region", "within": "United States", "limit": 5}. Countries of the world: {"indicator": "population", "level": "country"}. Returns {indicator, level, within, period, comparable, order, total, values: [{rank, place, value, status?}], source, notes?}. Every value comes from one source and one period. order "asc" lists the lowest first. Cite source.citation. For rates across municipalities pass min_population (for example 5000) so very small places, where a few people move the rate, do not top the list.

ParametersJSON Schema
NameRequiredDescriptionDefault
levelYesLevel of the places ranked.
limitNoOptional. Rows to return, 10 by default.
orderNoOptional. desc (highest first, default) or asc.
periodNoOptional. "2024" (year), "2024-Q3" (quarter), "2024-S1" (half year) or "2024-09" (month). Omit for the latest value.
withinNoOptional area that contains the ranked places, for example "United States", "EU", "Germany", "Texas", "Cataluña". Omit to rank all countries.
countryNoOptional ISO 3166-1 alpha-2 code to disambiguate the place, for example "ES" or "US".
indicatorYesIndicator id from search_indicators, for example "population", "registered_unemployment_rate", "unemployment_rate", "cpi_annual_change", "net_income_per_person".
min_populationNoOptional. Leave out places with fewer residents.
resolve_placeResolve place
Read-onlyIdempotent
Inspect

Turn a place name into the normalized entity Invokely uses, with its official codes (INE, Idescat, NUTS, ISO, US FIPS) and parent. Use it when a name is ambiguous or you want to confirm which entity a number refers to. The other tools accept names directly, so this call is optional. Ambiguous names prefer the municipality ("Barcelona" is the city); the province and region come back in alternatives. Ask for "provincia de Barcelona" to get the province. US states are regions and US counties are provinces. Names shared by several places of the same level, such as "Washington County", return an AMBIGUOUS_PLACE error with suggestions; add the state ("Washington County, Oregon") or pass a suggested id. Example: {"name": "Mataró"}. Returns {match: {id, name, level, country, population, parent, codes}, alternatives: [{id, name, level}]}.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYesPlace name or id. Examples: "Mataró", "Barcelona", "provincia de Barcelona", "Cataluña", "España", "Germany", "EU", "es-mun-08121", "08121" (INE code), "ES51" (NUTS), "Texas", "Travis County, Texas", "us-county-48453", "fips:48453" (US county FIPS).
levelNoOptional preferred level.
countryNoOptional ISO 3166-1 alpha-2 code to disambiguate the place, for example "ES" or "US".
search_indicatorsSearch indicators
Read-onlyIdempotent
Inspect

Find official statistical indicators by natural language, in English or Spanish. Use this first when you do not know the exact indicator id. Coverage: the United States (nation, states, counties), EU countries and regions, Spain (municipalities, provinces, regions, national), the United Kingdom, Canada, Australia, Ireland and New Zealand (national and regional series from their statistics offices), and every country plus the World from the World Bank. Topics: population and demography, unemployment and employment, prices and inflation, income and poverty, GDP, housing, companies, tourism, interest rates, public finance, health, AI and digital economy, energy, emissions, agriculture. Pass geography when the question is about a specific place: only indicators with data for that place are listed, and matches published elsewhere are named in not_available_for_place. Example: {"query": "tasa de paro", "geography": "Mataró"}. Returns {indicators: [{id, name, unit, frequencies, levels, definition, note?}], place?, not_available_for_place?}. Read note: it explains common confusions, such as survey unemployment rate versus registered unemployment.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesWhat you are looking for, for example "inflation", "paro registrado", "average income per person".
geographyNoOptional place the data is for. Same format as place in the other tools.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 6 tool updates
    • First observedcompare
    • First observedget_series
    • First observedget_value
    • First observedrank_places
    • First observedresolve_place
    • First observedsearch_indicators

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