gios-air-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_stationsA | List GIOŚ air-quality monitoring stations. Optional filters: city, voivodeship — both case-insensitive substring match. The full network is ~200 stations; use filters or |
| get_station_sensorsA | List the sensors installed at a station (each sensor measures one pollutant/indicator such as PM10, PM2.5, NO2, SO2, O3, C6H6). |
| get_sensor_readingsA | Get recent measurement readings from a sensor. Each reading is a (measured_at, value) pair. Returns latest ~24 hours. |
| get_air_indexB | Get the composite air-quality index for a station (aggregates all pollutants into a single category: very good / good / moderate / poor / very poor / hazardous). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct resource and action: stations, sensors, readings, and air index. There is no overlap, and an agent can easily determine which tool to call for a given query.
All tool names follow a consistent verb_noun pattern (list_stations, get_station_sensors, get_sensor_readings, get_air_index). The naming is uniform, predictable, and uses clear, specific verbs.
With exactly 4 tools, the server is tightly scoped to air quality monitoring without redundancy. Each tool covers a necessary step in the workflow, making the count ideal for the domain.
The tool surface covers the full core workflow: discover stations, inspect sensors, fetch readings, and get an aggregated index. Minor gaps include lack of historical readings beyond 24 hours and no station metadata endpoint, but these are acceptable for a minimal yet functional set.