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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

MCP server for direct HTTP communication with air-Q air quality sensor devices

README.md

mcp-airq

!MCP ![PyPI](https://pypi.org/project/mcp-airq/) ![Total Downloads](https://pepy.tech/project/mcp-airq) ![Python](https://pypi.org/project/mcp-airq/) ![License](LICENSE) ![Tests](https://github.com/CorantGmbH/mcp-airq/actions/workflows/tests.yml) ![Coverage](https://codecov.io/gh/CorantGmbH/mcp-airq)

MCP server for air-Q air quality sensor devices. Enables Claude Desktop, Claude Code, and other MCP clients to directly query and configure air-Q devices on your local network.

Built on aioairq, the official async Python library for air-Q.

The same mcp-airq executable also works as a direct CLI when you pass a tool name as a subcommand.

<!-- mcp-name: io.github.CorantGmbH/mcp-airq -->

Installation

pip install mcp-airq

Or run directly with uvx:

uvx mcp-airq

CLI Usage

Use the same command directly from the shell:

mcp-airq list-devices
mcp-airq get-air-quality --device "Living Room"
mcp-airq get-air-quality-history --device "Living Room" --last-hours 12 --sensors co2
mcp-airq plot-air-quality-history --sensor co2 --output-format png
mcp-airq export-air-quality-history --sensor co2 --output-format xlsx
mcp-airq set-night-mode --activated --device "Bedroom"

For historical plots and exports:

  • omit device, location, and group to combine all configured devices into one artifact
  • use location or group to combine only the matching devices
  • plot_air_quality_history returns one file per requested sensor, with one series per matching device
  • export_air_quality_history returns one CSV/XLSX file per request, with rows for all matching devices

The CLI subcommands mirror the MCP tool names. Both styles work:

mcp-airq list-devices
mcp-airq list_devices

To force MCP server mode from an interactive terminal, run:

mcp-airq serve

The CLI is pipe-friendly: successful command output goes to stdout, while tool errors go to stderr with exit code 1.

mcp-airq get-air-quality --device "Living Room" | jq '.co2'
mcp-airq get-air-quality --device "Living Room" --compact-json | jq '.co2'
mcp-airq get-air-quality --device "Living Room" --yaml | yq '.co2'

Device Configuration

Create a JSON file with your device(s), e.g. ~/.config/airq-devices.json:

[
  {"address": "192.168.4.1", "password": "your_password", "name": "air-Q Pro", "location": "Living Room", "group": "Home"},
  {"address": "192.168.4.2", "password": "your_password", "name": "air-Q Radon", "location": "Living Room", "group": "Home"},
  {"address": "office_air-q.local", "password": "other_pass", "name": "Office", "group": "Work"}
]

Each entry requires:

  • address — IP address or mDNS hostname (e.g. abcde_air-q.local)
  • password — Device password (default: airqsetup)
  • name (optional) — Human-readable name; defaults to address
  • location (optional) — Physical room/area for grouping (e.g. "Living Room")
  • group (optional) — Second grouping dimension, orthogonal to location (e.g. "Home", "Work")

Then restrict access to the file (it contains passwords):

chmod 600 ~/.config/airq-devices.json

Alternatively, pass the device list inline via the AIRQ_DEVICES environment variable as a JSON string.

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "airq": {
      "command": "uvx",
      "args": ["mcp-airq"],
      "env": {
        "AIRQ_CONFIG_FILE": "/home/you/.config/airq-devices.json"
      }
    }
  }
}

Claude Code

Register the server once via the CLI:

claude mcp add airq -e AIRQ_CONFIG_FILE=~/.config/airq-devices.json -- uvx mcp-airq

This writes to ~/.claude/settings.json and is automatically picked up by the Claude Code VSCode extension as well — no separate configuration needed.

If the server fails to connect: MCP servers run in a subprocess that may not inherit your shell's PATH. Replace uvx with its full path (which uvx → e.g. /home/you/.local/bin/uvx): ``bash claude mcp add airq -e AIRQ_CONFIG_FILE=~/.config/airq-devices.json -- /home/you/.local/bin/uvx mcp-airq ``

OpenAI Codex

Register the server once via the CLI:

codex mcp add airq --env AIRQ_CONFIG_FILE=~/.config/airq-devices.json -- uvx mcp-airq

This writes to ~/.codex/config.toml and is automatically picked up by the Codex VSCode extension as well.

If the server fails to connect: Use the full path to uvx (see note above).

Available Tools

Read-Only

| Tool | Description | | ------------------------- | -------------------------------------------------------------------- | | list_devices | List all configured air-Q devices (with location/group if set) | | get_air_quality | Get sensor readings — by device, location, or group | | get_air_quality_history | Get historical sensor data as column-oriented JSON | | plot_air_quality_history | Render one historical chart per sensor across all matching devices | | export_air_quality_history | Export one historical sensor as one csv/xlsx across matching devices | | get_device_info | Get device metadata (name, model, firmware version) | | get_config | Get full device configuration | | get_logs | Get device log entries | | identify_device | Make device blink its LEDs for visual identification | | get_led_theme | Get current LED visualization theme | | get_possible_led_themes | List all available LED visualization themes | | get_night_mode | Get current night mode configuration | | get_brightness_config | Get current LED brightness configuration |

Configuration

| Tool | Description | | ------------------- | ------------------------------------------------------- | | set_device_name | Rename a device | | set_led_theme | Change LED visualization (CO₂, VOC, Humidity, PM2.5, …) | | set_night_mode | Configure night mode schedule and settings | | set_brightness | Adjust LED brightness (day/night) | | configure_network | Set static IP or switch to DHCP |

Device Control

| Tool | Description | | ----------------- | ---------------------------------------------- | | restart_device | Restart the device (~30s downtime) | | shutdown_device | Shut down the device (manual restart required) |

Multi-Device Support

When multiple devices are configured, specify which device to query:

  • By exact name: "air-Q Pro"
  • By partial match (case-insensitive): "pro", "radon"

If only one device is configured, it is selected automatically.

Location and Group Queries

get_air_quality accepts two optional grouping parameters:

  • location — query all devices in the same room (e.g. "Living Room")
  • group — query all devices sharing a group tag (e.g. "Home")

Both are independent: a device can have a location, a group, both, or neither. Matching is case-insensitive and substring-based.

get_air_quality(location="Living Room")  → air-Q Pro + air-Q Radon
get_air_quality(group="Home")            → air-Q Pro + air-Q Radon + …
get_air_quality(device="air-Q Radon")   → just that one device

Exactly one of device, location, or group may be specified per call.

Historical Data

Three tools provide access to data stored on the device's SD card:

Plotting charts

plot_air_quality_history renders a chart for one sensor. When multiple devices match, each device becomes a separate series in the same chart.

!CO₂ area chart — single device

Single device (24 h, area chart, PNG)

!CO₂ area chart — multiple devices

Multiple devices at one location (24 h, area chart, PNG)

# Single device, last 24 hours (default), PNG output (default)
mcp-airq plot-air-quality-history --sensor co2 --device "Living Room"

# All devices at a location, custom time range, SVG output
mcp-airq plot-air-quality-history --sensor co2 --location "Living Room" \
  --from-datetime "2026-03-16T00:00:00" --to-datetime "2026-03-17T00:00:00" \
  --output-format svg --output co2.svg

# All configured devices, dark mode, line chart
mcp-airq plot-air-quality-history --sensor co2 --dark --chart-type line

# Save to file
mcp-airq plot-air-quality-history --sensor co2 --output co2_chart.png

Output formats: png (default), webp, svg, html (interactive Plotly chart with hover tooltips and zoom)

Customization: --title, --x-axis-title, --y-axis-title, --chart-type (line/area), --dark, --timezone-name

Exporting data

export_air_quality_history produces one CSV or Excel file containing all matching devices.

# CSV export (default)
mcp-airq export-air-quality-history --sensor co2 --device "Living Room" --last-hours 48

# Excel export for all devices at a location
mcp-airq export-air-quality-history --sensor radon --location "Home" \
  --output-format xlsx --output radon.xlsx

Querying raw JSON

get_air_quality_history returns column-oriented JSON, useful for programmatic analysis.

mcp-airq get-air-quality-history --device "Living Room" --last-hours 12 \
  --sensors co2 pm2_5 --max-points 150

Common parameters

| Parameter | Default | Description | |-----------|---------|-------------| | --last-hours | 1 (history) / 24 (plot) | Hours of data to retrieve | | --from-datetime / --to-datetime | — | ISO 8601 time range (overrides --last-hours) | | --max-points | 300 | Downsample to at most N evenly spaced points | | --timezone-name | UTC | IANA timezone for timestamps (e.g. Europe/Berlin) |

Example Prompts

  • "How is the air quality in the living room?" — queries all devices at that location
  • "What's the air quality at home?" — queries all devices in the "Home" group
  • "Show the CO₂ trend over the last 12 hours as SVG"
  • "Export the radon history from yesterday as Excel"
  • "Show me the radon level" — targets the air-Q Radon device by name
  • "Show CO₂ on the LEDs"
  • "Enable night mode from 10 PM to 7 AM"
  • "Set brightness to 50%"
  • "What's in the device log?"
  • "Make the air-Q blink"

Development

git clone https://github.com/CorantGmbH/mcp-airq.git
cd mcp-airq
uv sync --frozen --extra dev
uv run pre-commit install
uv run pytest

The repository uses a project-local .venv plus uv.lock for reproducible tooling. Run all developer commands through uv run, for example:

uv run ruff check .
uv run ruff format --check .
uv run pyright
uv run pre-commit run --all-files

Release Process

  1. Update version in pyproject.toml.
  2. Commit and create a matching Git tag like v0.1.1.
  3. Publish a GitHub Release from that tag.

The publish workflow validates that the release tag matches pyproject.toml, uploads the package to PyPI, and then publishes the same version to the MCP Registry.

License

Apache License 2.0 — see LICENSE.

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