mcp-airq

Official

Overview Schema Source Related Servers Discussions Admin

get_air_quality

Read-only

Query air quality sensor values from devices by name, location, or group. Choose time-averaged or instantaneous readings, with sensor unit documentation provided.

Instructions

Get current air quality sensor readings from one or more devices.

Specify exactly one of:
- 'device' — query a single device by name
- 'location' — query all devices at a given location (e.g. "Wohnzimmer")
- 'group' — query all devices in a group (e.g. "zu Hause")

When using 'location' or 'group', the response contains one entry per
device. Returns sensor names mapped to values. Set return_average=True
for time-averaged data (recommended) or False for instantaneous readings.
The response includes a _sensor_guide field with full unit and index
documentation — read it before interpreting any values.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
`device`	No
`location`	No
`group`	No
`return_average`	No
`clip_negative`	No
`include_uncertainties`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.6.3Jun 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral details: when using location/group, each device gets its own entry; the response includes a _sensor_guide field with documentation; and the option for averaged vs instantaneous readings. This goes beyond the 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 concise and well-structured: the first sentence states the purpose, followed by a clear bullet-like list of query modes, then a sentence on response structure and a recommendation. Every sentence adds value without redundancy.

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?

Given that an output schema exists, the description does not need to detail return values. It mentions that the response contains sensor names mapped to values and includes a _sensor_guide field. It covers the three main parameters and return_average, but misses two supplementary parameters. Overall, it is mostly complete for a 6-parameter tool with an output schema.

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 0% (no parameter descriptions), so the description must compensate. It explains the three mutually exclusive parameters (device, location, group) and return_average, but does not explain clip_negative or include_uncertainties. Thus, not all parameters are fully documented.

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 clearly states the tool gets current air quality sensor readings from one or more devices. It distinguishes itself from siblings like get_air_quality_history (historical) and list_devices (device listing) by specifying the real-time nature and the options for single device, location, or group queries.

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

Usage Guidelines4/5

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

The description explicitly says to specify exactly one of 'device', 'location', or 'group', with examples for each. It recommends using return_average=True. However, it does not explicitly state when to use this tool over alternatives like get_air_quality_history or export_air_quality_history, though the sibling context provides some distinction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.