Malaysian Weather MCP Server

🌦️ Malaysian Weather MCP Server

A production-ready MCP (Model Context Protocol) server that brings real-time Malaysian weather forecasts to your favorite AI assistant.

This project implements a local MCP server that fetches live weather data from MET Malaysia's API and integrates it seamlessly with any MCP-compatible client (Claude Desktop, Cursor, Cline, etc.). Users can ask their AI assistant about Malaysian weather in natural language, and it will use this server to fetch accurate, up-to-date forecasts.

What is MCP?

Model Context Protocol (MCP) is a standard that allows AI assistants to interact with external tools and services. By integrating this MCP server with your AI assistant, you enable it to:

• Query real-time weather data
• Access current and future forecasts for any Malaysian location
• Provide weather information in natural conversation
• Use weather data to inform responses and recommendations

What This Project Does

1. Fetches Weather Data: Automatically updates Malaysian weather forecasts from MET Malaysia every 15 minutes
2. Exposes MCP Tools: Provides two tools (check_weather_today, check_7day_forecast) that your AI assistant can call
3. Manages Data: Stores forecasts in a local MySQL database with automatic cleanup
4. Runs Locally: Everything runs on your machine - no cloud dependencies
5. Works with Any MCP Client: Add a simple config to your favorite AI tool and start asking about weather!

Quick Overview

┌─────────────────────────────────────────────────────┐
│          Your Local Machine                          │
├─────────────────────────────────────────────────────┤
│  Your MCP Client (Claude, Cursor, Cline, etc)       │
│  ↓                                                   │
│  MCP Server (weather-by-met)  ← This Project        │
│  ├─ server.py    (MCP server)                       │
│  ├─ scheduler.py (Updates weather data)             │
│  └─ MySQL DB     (Stores forecasts)                 │
│  ↓                                                   │
│  MET Malaysia API (weather data source)             │
└─────────────────────────────────────────────────────┘

User: "What's the weather in Kuala Lumpur?"
  ↓
AI asks MCP Server → MCP queries database → AI responds

🎯 Features

• Real-time Weather Data: Automatically fetches weather forecasts every 15 minutes
• 7-Day Forecasts: Access forecasts for up to 7 days ahead
• Multi-Location Support: Query weather for states, districts, towns, recreation centres, and divisions across Malaysia
• AI-Friendly Format: Returns structured data that works with any AI assistant
• Optimized Database: Efficient MySQL storage with automatic cleanup of old records
• Telegram Alerts: Error notifications sent to your Telegram channel for immediate awareness
• Production-Ready: Comprehensive error handling and logging

🚀 Quick Start

Get up and running in 5 minutes! This will set everything up locally on your machine.

Prerequisites

Before starting, ensure you have:

• Python 3.8+ - Install from python.org
• MySQL 8.0+ - Install from mysql.com (or use Homebrew: brew install mysql)
• An MCP Client - One of: Claude Desktop, Cursor IDE, Cline VSCode extension, or any MCP-compatible client
• Git - For cloning this repository

Installation Steps

Step 1: Clone the Repository

git clone https://github.com/zhenkai-dev/weather-by-met.git
cd weather-by-met

Step 2: Install Python Dependencies

pip install -r requirements.txt

This installs:

• fastmcp - MCP server framework
• mysql-connector-python - MySQL database driver
• pydantic - Input validation
• requests - For API calls
• And other utilities

Step 3: Set Up MySQL Database

# Create a .env file from the template
cp .env.example .env

Now edit .env with your MySQL credentials:

# macOS/Linux
nano .env

# Windows - use Notepad or your editor

Content of .env:

DB_HOST=localhost
DB_USER=root
DB_PASSWORD=your_mysql_password_here
DB_NAME=weather_by_met

Then initialize the database:

python init_db.py

This creates the weather_by_met database and weather_forecasts table automatically.

Step 4: Start the Scheduler (Keep Running)

In one terminal, start the scheduler to fetch weather data:

python scheduler.py

You'll see output like:

[2025-11-10 10:30:00] Starting scheduler...
[2025-11-10 10:30:05] ✓ Fetched weather for 38 locations
[2025-11-10 10:30:07] ✓ Scheduler ready - will update every 15 minutes

Keep this terminal running in the background. It will:

• Fetch weather data immediately
• Update every 15 minutes automatically
• Clean old records daily at 12:05 AM (Malaysia Time)

Step 5: Configure Your MCP Client

Choose your MCP client below and follow the configuration steps.

Option A: Claude Desktop

Step 5.1: Open config file

macOS/Linux: ```b