- LOCATION
- CAPABILITY
- GAP ANALYSIS
- HUMAN
Short answer
How can I audit sensor networks using my AI?
Your AI uses OpenAQ to find specific monitoring stations and check exactly what they measure. You'll get a clear picture of sensor coverage and data types in any region. This breakdown shows how to map those networks.
Audit outcomes
What you get from the audit
The AI processes the raw OpenAQ data into these specific outputs.
LOCATION
Station mapping
The AI identifies all active monitoring sites in your target area. You get a list of coordinates and station names.
CAPABILITY
Sensor specs
Your agent pulls the exact parameters each station tracks. This tells you if a site measures PM2.5, NO2, or other pollutants.
GAP ANALYSIS
Coverage gaps
By comparing station locations against your area of interest, the AI highlights where monitoring is missing.
HUMAN
Manual verification
You decide which data points are reliable enough for your specific research or regulatory needs.
The workflow
What your AI does when the request arrives.
The AI moves from broad geographic searches to granular sensor details.
Locate stations
The AI finds all relevant monitoring sites within your specified coordinates or region.
get_locationsIdentify hardware
Once stations are found, the AI identifies the specific sensors active at those sites.
get_sensorsCheck parameters
The AI looks up the specific pollutants or metrics each sensor is configured to measure.
get_parametersSummarize findings
The AI compiles the station locations, sensor types, and measurement capabilities into a single report.
get_locationsget_sensorsget_parameters
Try it
Copy these to start.
Use these prompts to kick off your audit.
Starting points
Swap out the bracketed text for your specific city, country, or pollutant of interest.
OpenAQ Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_VGsxrLcNairCyPHFbpo3PocA4AcTLLX4zk50pkNW/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — OpenAQ capabilities are ready to use.
{
"mcpServers": {
"openaq-mcp": {
"url": "https://edge.vinkius.com/vk_preview_VGsxrLcNairCyPHFbpo3PocA4AcTLLX4zk50pkNW/mcp"
}
}
}Find all active monitoring stations in [London, UK].
What specific pollutants are being measured by sensors in [Los Angeles]?
List all sensors in [Delhi] that can measure PM2.5.
Show me the measurement capabilities for all stations near [New York City].
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect OpenAQ once, then ask.
One click connects the OpenAQ MCP to your AI client. Your credentials stay encrypted and the setup is handled on our end.
Connect OpenAQ to your AIFAQ
How this task behaves
- 01
Can the AI add new sensors to the network?
No. The AI can only read existing data from OpenAQ; it cannot modify or add hardware or station configurations.
- 02
Can I use this to download historical data files?
No. The tools are designed to identify locations, sensors, and parameters, not to export bulk historical datasets.
- 03
Does the AI know the exact physical condition of a sensor?
No. The AI only sees the capabilities and parameters reported by the OpenAQ API.
- 04
How does the AI find stations in a specific city?
It uses the location tool to find stations within the geographic bounds you provide.
- 05
Can the AI tell me which sensors are broken?
No. The AI can only report what the sensors are capable of measuring, not their real-time operational health.
More questions about OpenAQ? The Connector page answers them. See everything the OpenAQ Connector can do
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