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Weather MCP Server by Meteosource

get_air_quality

Hourly air-quality (smog) forecast for up to 20 locations, about 4 days ahead.

Columns: `air_quality` (index, 1 = good, higher = worse) and pollutant
surface concentrations — default pm10, pm25, no2_surface, so2_surface,
ozone_surface; also available via `variables`: co_surface, no_surface,
ozone_total, aerosol_550, dust_550nm, dust_mixing_ratio_05. Output is a
table per location (`columns` once, `rows` as arrays), trimmed to `hours`.
Not available on the free tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNo
timezoneNoauto
locationsYes
variablesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the return shape (a table per location with `columns` once and `rows` as arrays), that output is trimmed to `hours`, the default variable set, the 20-location cap, the ~4-day horizon, and a tier restriction. It stops short of error behavior or auth/rate-limit details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then output shape, then caveats; every sentence contributes. The pollutant variable enumeration is long but earns its place by telling the agent what values `variables` accepts.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no annotations, so the description must stand alone — and it covers output layout, defaults, geographic limit, horizon, and tier restriction. It is nearly complete for invocation, with only timezone semantics and over-limit error behavior left undocumented.

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

Parameters4/5

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

Top-level schema description coverage is 0%, yet the description names the default variables (pm10, pm25, no2_surface, so2_surface, ozone_surface), enumerates the additional options for `variables`, and explains that `hours` trims the table. It adds meaning well beyond the schema, though `timezone` and the place_id-vs-lat/lon choice go unaddressed here.

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 verb+resource with scope: hourly air-quality (smog) forecast for up to 20 locations, ~4 days ahead. The purpose is unmistakable and clearly distinct from weather-oriented siblings like get_forecast, but the description never explicitly differentiates itself from those siblings.

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 implied by the resource name and the note that it is 'Not available on the free tier,' which is a useful eligibility constraint. However, there is no explicit when-to-use guidance, no guidance on when to supply custom `variables` versus the defaults, and no routing away from alternatives such as get_forecast.

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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