Find air-quality monitoring stations (measured by physical sensors, not modeled) near a point, within a bounding box, or by country. Returns each station's id, name, coordinates, distance from the query point (when searching by coordinates), country, provider, the parameters its sensors measure, and the timestamp of its most recent data (datetimeLast). Required first step: openaq_get_readings and openaq_get_measurements key on the location id this returns. Coverage is uneven and real — a station only reports the parameters it measures, and the absence of a nearby station means no monitoring there, not clean air. For dense modeled coverage anywhere on Earth, use open-meteo-mcp-server's air-quality tool instead.
Latest measured value for every sensor at a monitoring station — the current-conditions tool. Returns one record per parameter, each with the value, its unit, the UTC and local timestamp, and the sensor id, joined so every value carries its pollutant and unit (the raw latest feed is keyed only by sensor id). Pass a locationId from openaq_find_locations, or pass coordinates to auto-resolve to the nearest station that measures the requested parametersId. Data recency varies by station reporting cadence — read each value's timestamp to know whether "latest" is minutes or hours old. These are measured observations with coverage gaps, not a modeled grid.
Historical measurement series for one pollutant at one station over a date range — for trend analysis and "was last week worse than the monthly average?". Pass a locationId and a parametersId; the tool resolves the station's sensor for that parameter internally (v3 series are sensor-scoped, but you think in stations). Choose aggregation: raw (every reported value), hourly, or daily — daily and hourly add a per-bucket statistical summary (min, median, max, mean, sd). Large ranges produce thousands of rows and spill to a DataCanvas: the response returns a preview plus a canvasId and table name you query with openaq_dataframe_query. Values carry their unit; the server never converts between µg/m³, ppm, and ppb.
Catalog of every measurable pollutant and its canonical unit: id, code, display name, unit, and a one-line description (pm25, pm10, o3, no2, so2, co, bc, and ~38 more). This is the unit-disambiguation reference — the same pollutant exists under several ids with different units (CO is id 4 in µg/m³, id 8 in ppm, id 102 in ppb), so use this to pick the exact parametersId for openaq_find_locations / openaq_get_readings / openaq_get_measurements and to interpret a reading's unit. A small bounded catalog fetched live from OpenAQ.
Catalog of country-level coverage: id, ISO code, name, the date span of available station data (datetimeFirst/datetimeLast), and which parameters are measured anywhere in that country. The availability check before a regional sweep — answers "which countries have NO2 monitoring?" and tells you whether a country has recent data before you call openaq_find_locations. Coverage is uneven worldwide; this surfaces where measured data exists.
Run a read-only SQL SELECT against the measurement tables openaq_get_measurements staged on a DataCanvas. Reference tables by the name the measurements call returned (measurements_<sensorId>). For aggregation (monthly means, exceedance counts) and cross-sensor comparison over series too large to inline. Only SELECT is allowed — a four-layer gate rejects writes, DDL, and file/network table functions.
List the tables and columns staged on a DataCanvas so you can write valid SQL for openaq_dataframe_query without guessing column names. Returns each measurement table (measurements_<sensorId>) with its row count and column names. Throws canvas_unavailable when DuckDB is off.