Weather MCP Server

A complete Model Context Protocol (MCP) server that provides weather information through tools, resources, and prompts, designed for integration with Cursor IDE.

What is MCP (Model Context Protocol)?

MCP is a protocol that enables AI assistants (like Cursor) to connect to external data sources and tools. It allows AI models to:

• Call Tools: Execute functions to perform actions (e.g., fetch weather data, query databases)

• Read Resources: Access structured data from external sources (e.g., files, APIs, databases)

• Use Prompts: Leverage reusable prompt templates for consistent interactions

How MCP Works

The MCP server acts as a bridge between the AI assistant and external services, providing a standardized interface for accessing data and functionality.

Features

This Weather MCP Server provides:

Tools

• get_current_weather(location: str) - Fetch current weather conditions for a location

• get_weather_forecast(location: str, days: int) - Get multi-day weather forecast

• search_locations(query: str) - Search for location names

Resources

• weather://current/{location} - Current weather data as a readable resource

• weather://forecast/{location} - Forecast data as a readable resource

Prompts

• analyze_weather - Template for analyzing weather patterns and conditions

• compare_locations - Template for comparing weather between different locations

Setup

Prerequisites

• Python 3.12 or higher

• uv package manager (or pip)

Installation

1. Install dependencies:

2. Set up environment variables (optional, for real API):

   Create a .env file in the project root:

   # .env WEATHER_API_KEY=your_api_key_here

   Get a free API key from OpenWeatherMap

   Note: If no API key is provided, the server will use mock data for demonstration purposes.

Running the Server

The server will start and communicate via stdio (standard input/output), which is the standard transport for MCP servers in Cursor IDE.

Cursor IDE Integration

To use this MCP server in Cursor IDE:

1. Open Cursor IDE settings (Cmd/Ctrl + ,)

2. Navigate to Features → MCP Servers (or search for "MCP" in settings)

3. Click Add Server or edit the MCP servers configuration

4. Add the following configuration (update the path to match your project location):

Important: Replace /Users/pratik/weather/main.py with the absolute path to your main.py file.

5. Save the configuration

6. Restart Cursor IDE

7. The AI assistant can now use the weather tools, resources, and prompts!

Alternative: You can also copy the configuration from cursor_mcp_config.json and merge it into your Cursor settings.

Usage Examples

Once integrated with Cursor IDE, you can ask the AI assistant:

• "What's the weather in New York?"

• "Get a 5-day forecast for London"

• "Compare the weather in San Francisco and Seattle"

• "Search for locations matching 'Paris'"

The AI will automatically use the appropriate MCP tools, resources, or prompts to fulfill your request.

Example: Asking "What's the weather in New York?" in Cursor IDE with the Weather MCP Server

Architecture

Development

Project Structure

Adding New Features

• New Tools: Add functions to the tools list in main.py

• New Resources: Add URI patterns to the resources list in main.py

• New Prompts: Add prompt templates to the prompts list in main.py

License

MIT