OpenAQ MCP. Access global pollution data in seconds.

OpenAQ connects your AI agent straight into the world’s largest open air quality database. You can use it to track pollution levels and analyze global air trends using simple natural language queries. This server pulls data from thousands of monitoring stations worldwide.

Finding Stations and Locations

You'll find stations in several ways. If you need a quick overview, get_countries lists every country that has active monitoring stations, giving you counts for how many cities and locations are covered there. Need to narrow it down? You can use get_locations to search for air quality stations by filtering criteria like a specific country, city name, pollutant type, or even a geographic bounding box.

Once you know the general area, if you need all the details on one known station, get_location_by_id retrieves every piece of data tied to that unique monitoring ID.

To find out what physical hardware is running these readings, you've got sensor tools too. Use get_sensors to list air quality sensors, letting you filter by location or the type of pollutant they monitor. If you know a specific sensor’s identifier, get_sensor_by_id fetches all its details for you.

Getting Measurements and Data Trends

The server gives you two main ways to get readings: current status or history. To check the most recent pollution levels without pulling massive amounts of historical data, use get_latest_measurements. This function grabs the absolute newest air quality reading for a specific monitored location ID, covering pollutants like PM2.5, O3, NO2, SO2, and CO.

For deep dives into trends, you'll rely on get_measurements. You can pull time-series readings with timestamps by filtering this function using the required location, a specific pollutant parameter, and a defined date range. This lets your agent track long-term pollution patterns over weeks or months. When you just need to know what pollutants are even measurable, run get_parameters which lists every available air quality parameter—including units of measure and whether they're considered core parameters like PM10 or Ozone (O3).

If you only care about one specific pollutant, use get_parameter_by_id to get detailed info on that single chemical.

Sensor Details and Pollutant Types

If you want a list of every measurable air quality pollutant available, run get_parameters. This returns the full catalog, which includes units for parameters like Nitrogen Dioxide (NO2) and Carbon Monoxide (CO), plus whether they are designated as core monitoring types. For sensor hardware details, if you need to find out what specific pollutants a general category of sensors monitors, use get_sensors, allowing filtering by location or pollutant type.

When your AI client uses these tools—for instance, running get_locations first, then feeding that result into get_latest_measurements, and finally using get_parameter_by_id to check the units for PM2.5—it builds a complete picture of air quality data from start to finish.