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Weather Edge MCP Server

@RJW34

リポジトリ

基本情報

カテゴリ

メディアとデザイン

ライセンス

MIT

トランスポート

stdio

作者

RJW34

投稿者

RJW34

Weather Edge MCP Server について

MCP server for calibrated weather prediction market signals (Kalshi). Dual-model NWS + GFS ensemble forecasting.

Weather Edge MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "weather-edge": {
      "command": "python",
      "args": [
        "-m",
        "weather_edge_mcp"
      ]
    }
  }
}

Weather Edge MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Weather Edge MCP?

Weather Edge MCP is an MCP server that provides calibrated Kalshi weather‑market signals. It combines public National Weather Service forecasts and Kalshi market prices into a compact tool surface for AI agents.

How to use Weather Edge MCP?

Install via pip install weather-edge-mcp. Configure it in Claude Desktop by adding the command python -m weather_edge_mcp to your MCP server list. For other clients, run weather-edge-mcp or python -m weather_edge_mcp with optional transport flags (--transport stdio, --transport sse --port 8050, or --transport streamable-http --port 8050).

Key features of Weather Edge MCP

  • Calibrates NWS daily high‑temperature forecasts by city
  • Reads current Kalshi weather market prices
  • Estimates per‑bucket probability, edge, and net expected value
  • Exposes five MCP tools for AI agent consumption
  • Ships an optional FastAPI web app with health and dashboard routes
  • Supports multiple transports: stdio, SSE, and streamable HTTP

Use cases of Weather Edge MCP

  • An AI agent can fetch calibrated weather signals for a single city before making a market decision.
  • A dashboard can query all supported cities at once to view market opportunities.
  • Developers can retrieve bias‑adjusted forecast context to inform custom analyses.
  • Automated trading bots can integrate real‑time METAR observations and Kalshi prices.

よくある質問

1

What are the supported cities?

Weather Edge MCP currently supports five cities: nyc, chicago, denver, miami, and la.

2

How is Weather Edge MCP installed?

Install it with `pip install weather-edge-mcp`. No additional configuration is required for basic use.

3

What transport options are available?

The server can be run in stdio mode (default), SSE mode (`--transport sse --port 8050`), or streamable HTTP mode (`--transport streamable-http --port 8050`). The stdio mode stays clean and side‑effect free.

4

Does Weather Edge MCP require authentication?

MCP stdio mode requires no authentication. The optional FastAPI web app can be gated with the x402 stack if that module is installed and configured.

5

What data sources does Weather Edge MCP use?

It uses the National Weather Service forecast API, the Aviation Weather METAR API, and the Kalshi public market API. No data is stored locally.

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