Weather Edge MCP
Tín hiệu xác suất thời tiết đã hiệu chuẩn cho thị trường dự đoán Kalshi. Mô hình kép: dự báo NWS + tập hợp 31 thành viên GFS. METAR thời gian thực từ các trạm thanh toán.
Tài liệu
Weather Edge MCP Server
Weather Edge is an MCP server for calibrated Kalshi weather-market signals. It turns public forecast and market data into a compact tool surface for AI agents.
What it does
- calibrates NWS daily high-temperature forecasts by city
- reads current Kalshi weather market prices
- estimates per-bucket probability, edge, and net expected value
- exposes the results through MCP tools and an optional FastAPI surface
Install
pip install weather-edge-mcp
MCP usage
Claude Desktop
{
"mcpServers": {
"weather-edge": {
"command": "python",
"args": ["-m", "weather_edge_mcp"]
}
}
}
Other MCP clients
Use either of these commands:
weather-edge-mcp
python -m weather_edge_mcp
Transport options
weather-edge-mcp --transport stdio
weather-edge-mcp --transport sse --port 8050
weather-edge-mcp --transport streamable-http --port 8050
Tools
| Tool | Description |
|---|---|
get_weather_signals(city) | Calibrated signals for one city's Kalshi weather markets |
get_all_signals() | Full scan across all supported cities |
get_forecast(city) | Bias-adjusted forecast context for one supported city |
get_station_observation(city) | Latest METAR observation from the settlement station |
list_cities() | Supported cities and calibration parameters |
Supported cities: nyc, chicago, denver, miami, la
Optional web API
Weather Edge also ships an optional FastAPI app:
python -m uvicorn weather_edge_mcp.web_app:app --host 0.0.0.0 --port 8080
Routes:
/api/health/api/signals?city=nyc/api/all-signals/dashboard/subscribe
If the optional x402 stack is installed and configured, the paid routes can be gated there. MCP stdio mode stays clean and side-effect free.
Docker
The repo includes a Dockerfile for Glama/container builds.
docker build -t weather-edge-mcp .
docker run --rm weather-edge-mcp --help
Architecture
src/weather_edge_mcp/
core.py # forecasting, market fetches, calibration, formatting
mcp_server.py # MCP tools
web_app.py # optional FastAPI surface
cli.py # command-line entrypoint
Data sources
- National Weather Service forecast API
- Aviation Weather METAR API
- Kalshi public market API
Development
python -m unittest discover -s tests -v
python -m build
License
MIT