A
license-
qualityC
maintenanceAccess air quality data from Open-Meteo API, free and without authentication.
Last updated
14
MIT
Air Quality MCP
Server Details
Free, keyless real-time air quality (US AQI plus PM2.5, PM10, ozone, NO2, SO2, CO) for any city.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
A4.9/5.0
Tool DescriptionsA
Average 5/5 across 1 of 1 tools scored.
Server CoherenceA
Disambiguation5/5
Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is clear and singular.
Naming Consistency5/5
The single tool name follows a clear verb_noun convention (get_air_quality), which is consistent with standard MCP naming practices. There are no other names to conflict.
Tool Count4/5
One tool is slightly below the typical 3-15 range, but for a narrowly focused air quality server, it is a reasonable and well-scoped choice. The tool covers the core need without unnecessary bloat.
Completeness4/5
The server provides a comprehensive current air quality report including AQI, pollutants, and location resolution. Minor gaps like forecasts or historical data would be enhancements, but the core use case is fully covered.
Available Tools
1 toolget_air_qualityARead-onlyInspect
Get the current air quality for a city, from real-time monitoring and atmospheric model data. Use for any "what's the air quality in X", "is it safe to go outside in Y", "how polluted is Z" style question, or whenever pollen/smog/wildfire-smoke/pollution conditions are relevant to a plan (running, cycling, sensitive-groups advice, travel).
city is a free-text place name (e.g. "Bangkok", "Berlin", "Springfield, US").
Returns a dict with:
location: resolved place name/country/admin1us_aqi: the current US Air Quality Index (0-500+)aqi_category: plain-language category computed fromus_aqi-- "Good" (0-50), "Moderate" (51-100), "Unhealthy for Sensitive Groups" (101-150), "Unhealthy" (151-200), "Very Unhealthy" (201-300), or "Hazardous" (301+); "Unknown" if no AQI could be resolved for that locationpm2_5,pm10: particulate matter concentrations (ug/m3)ozone,nitrogen_dioxide,sulphur_dioxide,carbon_monoxide: trace gas concentrations (ug/m3)local_time: the timestamp of the reading, in the location's local timeattribution
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond the readOnlyHint annotation by detailing data sources (real-time monitoring and atmospheric model data), the full structure of the return dictionary, and the exact mapping from us_aqi to aqi_category including the 'Unknown' fallback. This provides rich behavioral context without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded: it opens with a one-sentence summary, then lists usage contexts, parameter guidance, and output fields. Every sentence adds value, and the length is justified by the detailed return schema and category definitions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having only one parameter and no nested objects, the description covers all necessary context: what the tool does, when to use it, how to format the parameter, and exactly what fields are returned. It even explains the category computation logic, leaving no gaps for an agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines `city` as a required string with no description (0% coverage). The description compensates fully by explaining that `city` is a free-text place name and providing examples ('Bangkok', 'Berlin', 'Springfield, US'), which is essential for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Get the current air quality for a city', clearly stating what the tool does. It enumerates the exact output fields (us_aqi, pm2_5, etc.) and differentiates itself by focusing on air quality rather than weather or other data, even without sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides usage scenarios: 'Use for any ... style question' and 'whenever pollen/smog/wildfire-smoke/pollution conditions are relevant to a plan'. This gives clear context for when to invoke the tool, covering both direct queries and indirect use cases. No alternatives are needed since there are no sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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