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Weather MCP Server

Weather MCP Server

by isdaniel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_air_quality_details

Retrieve detailed air quality data for a specified city including pollutants like PM10, PM2.5, and gases. Returns structured JSON for programmatic analysis.

Instructions

Get detailed air quality information for a specified city as structured JSON data. This tool provides raw air quality data for programmatic analysis and processing.

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": {
      "city": "<city>"
    },
    "name": "get_air_quality_details"
  }
}

Input Schema

NameRequiredDescriptionDefault
cityYesThe name of the city to fetch air quality information for, PLEASE NOTE English name only, if the parameter city isn't English please translate to English before invoking this function.
variablesNoAir quality variables to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations provided; description only says it provides raw data. Does not disclose any behavioral traits such as rate limits, authentication requirements, or data freshness. For a read-only tool this is minimal.

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?

Two concise sentences with a clear statement of purpose and usage context. Some whitespace formatting but no unnecessary content.

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

Completeness3/5

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

Given the tool has only two parameters and no output schema, the description covers the basic purpose and output format. However, it could specify data freshness or whether it returns current or historical data.

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 covers 100% of parameters with descriptions. The description does not add significant meaning beyond schema, aside from reinforcing the 'English name only' hint already present in the city parameter.

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?

Clearly states verb 'Get' and resource 'detailed air quality information' with output format 'structured JSON data'. Distinguishes from sibling 'get_air_quality' which likely provides simpler data.

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?

Indicates it provides raw data for programmatic use, but does not explicitly differentiate from 'get_air_quality' or specify when to use this tool over others.

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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