AQICN MCP Server

AQICN MCP Server

By mattmarcin GitHub

An MCP server to get Air Quality Data using AQICN.org

aqicn air-quality
Overview

what is AQICN MCP Server?

AQICN MCP Server is a Model Context Protocol (MCP) server that provides air quality data tools from the World Air Quality Index (AQICN) project, allowing users to fetch real-time air quality data for cities and coordinates worldwide.

how to use AQICN MCP Server?

To use the AQICN MCP Server, install it via Smithery or manually set up your Python environment, configure your API key, and run the server to access air quality data.

key features of AQICN MCP Server?

  • Fetch air quality data for specific cities or coordinates.
  • Search for air quality monitoring stations by keyword.
  • Provides real-time air quality index (AQI) data.

use cases of AQICN MCP Server?

  1. Monitoring air quality in urban areas.
  2. Researching environmental data for academic purposes.
  3. Integrating air quality data into applications for public awareness.

FAQ from AQICN MCP Server?

  • What data can I retrieve using this server?

You can retrieve air quality data including AQI values, dominant pollutants, and station information.

  • Is there a cost to use the AQICN MCP Server?

The server is free to use, but you need to sign up for an API key from AQICN.org.

  • Can I use this server for commercial applications?

Yes, as long as you comply with the licensing terms.

Content

AQICN MCP Server

smithery badge

This is a Model Context Protocol (MCP) server that provides air quality data tools from the World Air Quality Index (AQICN) project. It allows LLMs to fetch real-time air quality data for cities and coordinates worldwide.

Installation

Installing via Smithery

To install AQICN MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @mattmarcin/aqicn-mcp --client claude

We recommend using uv to manage your Python environment:

# Install the package and dependencies
uv pip install -e .

Environment Setup

Create a .env file in the project root (you can copy from .env.example):

# .env
AQICN_API_KEY=your_api_key_here

Alternatively, you can set the environment variable directly:

# Linux/macOS
export AQICN_API_KEY=your_api_key_here

# Windows
set AQICN_API_KEY=your_api_key_here

Running the Server

Development Mode

The fastest way to test and debug your server is with the MCP Inspector:

mcp dev aqicn_server.py

Claude Desktop Integration

Once your server is ready, install it in Claude Desktop:

mcp install aqicn_server.py

Direct Execution

For testing or custom deployments:

python aqicn_server.py

Available Tools

1. city_aqi

Get air quality data for a specific city.

@mcp.tool()
def city_aqi(city: str) -> AQIData:
    """Get air quality data for a specific city."""

Input:

  • city: Name of the city to get air quality data for

Output: AQIData with:

  • aqi: Air Quality Index value
  • station: Station name
  • dominant_pollutant: Main pollutant (if available)
  • time: Timestamp of the measurement
  • coordinates: Latitude and longitude of the station

2. geo_aqi

Get air quality data for a specific location using coordinates.

@mcp.tool()
def geo_aqi(latitude: float, longitude: float) -> AQIData:
    """Get air quality data for a specific location using coordinates."""

Input:

  • latitude: Latitude of the location
  • longitude: Longitude of the location

Output: Same as city_aqi

3. search_station

Search for air quality monitoring stations by keyword.

@mcp.tool()
def search_station(keyword: str) -> list[StationInfo]:
    """Search for air quality monitoring stations by keyword."""

Input:

  • keyword: Keyword to search for stations (city name, station name, etc.)

Output: List of StationInfo with:

  • name: Station name
  • station_id: Unique station identifier
  • coordinates: Latitude and longitude of the station

Example Usage

Using the MCP Python client:

from mcp import Client

async with Client() as client:
    # Get air quality data for Beijing
    beijing_data = await client.city_aqi(city="beijing")
    print(f"Beijing AQI: {beijing_data.aqi}")

    # Get air quality data by coordinates (Tokyo)
    geo_data = await client.geo_aqi(latitude=35.6762, longitude=139.6503)
    print(f"Tokyo AQI: {geo_data.aqi}")

    # Search for stations
    stations = await client.search_station(keyword="london")
    for station in stations:
        print(f"Station: {station.name} ({station.coordinates})")

Contributing

Feel free to open issues and pull requests. Please ensure your changes include appropriate tests and documentation.

License

This project is licensed under the MIT License.

No tools information available.
No content found.