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Weather-Prediction MCP Server

by gabrieljba

Day 3 Homework: Weather-Prediction MCP Server

A FastMCP server that exposes weather-forecast tools over the Model Context Protocol, designed to be consumed by a Databricks Agent Bricks agent.

Architecture

Agent Bricks agent  --(MCP tool calls)-->  weather_mcp_server.py  --(HTTP)-->  NWS API (free, no key)
                                                    |
                                                    +--> weather_broker.py (adapter: all HTTP/parsing logic)

Related MCP server: Weather MCP Server

MCP Tools Exposed

Tool

Description

get_current_weather(location)

Real-time temperature, humidity, wind, conditions from nearest NWS station

get_forecast(location, days)

Multi-day forecast (up to 7 days) with temp, wind, precip chance, conditions

get_weather_alerts(location)

Active warnings, watches, and advisories for the location

get_travel_recommendation(location, days)

Derived recommendations with threshold logic (umbrella, jacket, heat, outdoors)

Weather API

Files

File

Role

weather_mcp_server.py

FastMCP server with @mcp.tool decorators (thin wrappers)

weather_broker.py

Adapter module — all HTTP calls, parsing, and recommendation logic

lakebase.py

Lakebase connection helper (same pattern as Day 2/3, for extensibility)

app.yaml

Databricks App configuration

requirements.txt

Python dependencies

Secrets Required in Databricks

Secret Scope

Secret Key

Value

Required For

database

lakebase-url

Base64-encoded Postgres connection URL

Lakebase (optional, for future use)

Note: The NWS API requires NO API key. No weather-related secrets needed.

Deploy as Databricks App

  1. Upload this entire folder (day3-homework-mcpserver-weather/) to your Databricks workspace

  2. Create a new Databricks App pointing to this folder

  3. The app will start via python weather_mcp_server.py (as defined in app.yaml)

  4. Register the app URL as an external MCP server in Agent Bricks

Register as External MCP in Agent Bricks

  1. Go to your Databricks workspace → Agent Bricks

  2. Add a new external MCP tool connection

  3. Set the URL to your deployed app's endpoint (e.g. https://<your-app-url>/mcp)

  4. The 4 tools will be auto-discovered by the agent

Suggested Agent System Prompt

You are a weather assistant that helps users understand weather conditions
and make plans based on forecasts. You have access to real-time weather
data for US locations via the National Weather Service.

Rules:
- ALWAYS use the weather tools to get data. NEVER guess or hallucinate weather information.
- Use get_current_weather() for "what's the weather now?" questions.
- Use get_forecast() for "what will the weather be like?" questions.
- Use get_weather_alerts() when users ask about severe weather or safety.
- Use get_travel_recommendation() for planning questions ("should I bring an umbrella?", "is it a good day for hiking?").
- If a location cannot be resolved, ask the user to clarify with "City, State" format.
- Only US locations are supported. If asked about international locations, explain this limitation.
- If the API returns an error, tell the user honestly rather than making up data.
- When presenting forecasts, summarize the key points rather than dumping raw data.

Local Development

pip install -r requirements.txt
python weather_mcp_server.py
# Server starts on http://0.0.0.0:8000
F
license - not found
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

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