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Air quality

get_air_quality
Read-onlyIdempotent

Latest PM2.5, NO2, O3 from the nearest monitoring stations (OpenAQ; the server needs an OPENAQ_API_KEY), with each station's data licence.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "get_air_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault
latitudeYesLatitude in degrees (WGS84)
longitudeYesLongitude in degrees (WGS84)

Output Schema

NameRequiredDescriptionDefault
queryNo
unitsNoUnit of each numeric field
statusNook
channelYes
featuresYesRecords from the data source
warningsNoCaveats to tell the user
provenanceNoSource, licence, attribution, retrieval time and method
total_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare read-only, idempotent, open-world and non-destructive, so the bar is lower. The description adds genuinely new behavioral facts: a server-side API key is required, readings are approximated via 'nearest' stations rather than the exact point, and each station's data licence is returned.

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?

A single sentence with the resource front-loaded and the auth/source/licence caveats tucked into a parenthetical. No filler, nothing repeated from annotations.

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?

An output schema exists, so return values need not be described. For a two-parameter read tool, the description covers what is fetched, from where, the auth prerequisite, and the licence caveat — everything an agent needs to call it and interpret it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with two fully documented WGS84 coordinates, so the schema carries the load. The description only indirectly implies that the coordinates are used to find the closest station; it adds no format or precision guidance beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource (PM2.5, NO2, O3 readings) plus the mechanism ('from the nearest monitoring stations') and the upstream source (OpenAQ). This clearly separates it from siblings like get_weather or get_elevation, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: give a coordinate, get nearby readings. The OPENAQ_API_KEY note is a useful prerequisite, but there is no statement of when to prefer this over get_weather or location_report, and no exclusions or coverage limits (radius, station count).

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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