AQICN MCP Server
An MCP server to get Air Quality Data using AQICN.org
Installation
Installing for Claude Desktop
Manual Configuration Required
This MCP server requires manual configuration. Run the command below to open your configuration file:
npx mcpbar@latest edit -c claude
This will open your configuration file where you can add the AQICN MCP Server MCP server manually.
AQICN MCP Server
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
Installing via recommended uv (manual)
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 valuestation
: Station namedominant_pollutant
: Main pollutant (if available)time
: Timestamp of the measurementcoordinates
: 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 locationlongitude
: 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 namestation_id
: Unique station identifiercoordinates
: 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.
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