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Weather Prediction Server

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Provides current weather, multi-day forecasts, and umbrella recommendations through natural language queries, backed by the Open-Meteo API.

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About

Provides current weather, multi-day forecasts, and umbrella recommendations through natural language queries, backed by the Open-Meteo API.

README

An MCP server deployed on Databricks Apps backed by the Open-Meteo REST API, integrated with Databricks Agent Bricks to answer natural language weather queries.

File Structure

  • weather_adapter.py: HTTP request and geocoding adapter module.
  • weather_mcp_server.py: FastMCP tool definitions (get_current_weather, get_forecast, predict_umbrella_needed).
  • app.yaml: Databricks Apps deployment runtime config.
  • requirements.txt: Python package requirements.
  • .gitignore: Git exclusion file.

Setup & Deployment Instructions

  1. Git Folder Setup:

    • Push this directory to your GitHub repository.
    • In Databricks, navigate to Workspace > Users > <your_user>, click Create > Git Folder, and clone your repository URL.
  2. Deploy Databricks App:

    • In Databricks sidebar, go to Compute > Apps > Create App.
    • Name the app mcp-weather-server (must start with mcp-).
    • Set the source code path to your cloned Git folder location.
    • Deploy the app and copy its runtime URL.
  3. Register MCP Server & Connect Agent Bricks:

    • In Workspace Settings / External Connections, register the app SSE URL (https://<app-url>/sse).
    • In Agent Bricks, create a new agent, attach WeatherPredictionServer as a tool, and paste the system prompt below.

Agent System Prompt

You are WeatherBot, an expert weather advisor assistant deployed on Databricks.

GUIDELINES & GUARDRAILS:
1. Rely EXCLUSIVELY on information returned by your weather tools. Never invent weather metrics.
2. For real-time queries, call `get_current_weather`.
3. For multi-day queries, call `get_forecast`.
4. For recommendation queries, call `predict_umbrella_needed`.
5. If a tool returns an error status, notify the user clearly and request location clarification.

Proof of Functionality (Sample Agent Execution Traces)

Query 1: Current Weather

  • Prompt: "What is the current weather in Chicago right now?"
  • Tool Called: get_current_weather(location="Chicago")
  • Response: "Currently in Chicago, United States, it is 22.5°C (feels like 22.1°C) with 58% humidity and no precipitation."

Query 2: Multi-day Forecast

  • Prompt: "Give me a 3-day forecast for Austin, TX."
  • Tool Called: get_forecast(location="Austin, TX", days=3)
  • Response: "3-Day Forecast for Austin, TX:\n- Aug 8: High 36.1°C, Low 24.2°C (10% rain chance)\n- Aug 9: High 37.0°C, Low 25.0°C (5% rain chance)\n- Aug 10: High 35.8°C, Low 24.5°C (45% rain chance)"

Query 3: Recommendation Logic

  • Prompt: "Should I bring an umbrella to Austin tomorrow?"
  • Tool Called: predict_umbrella_needed(location="Austin, TX", target_date_offset=1)
  • Response: "You do not need an umbrella in Austin tomorrow. The rain probability is 5% with expected precipitation of 0.0 mm."

from github.com/sri-25/weather-mcp-agent

Installing Weather Prediction Server

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/sri-25/weather-mcp-agent

FAQ

Is Weather Prediction Server MCP free?

Yes, Weather Prediction Server MCP is free — one-click install via Unyly at no cost.

Does Weather Prediction Server need an API key?

No, Weather Prediction Server runs without API keys or environment variables.

Is Weather Prediction Server hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install Weather Prediction Server in Claude Desktop, Claude Code or Cursor?

Open Weather Prediction Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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