AQICN MCP Server
Enables interaction with the World Air Quality Index to fetch real-time air quality data for cities and coordinates worldwide via Model Context Protocol (MCP).
mattmarcin
README
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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