Practice MCP JS
A Model Context Protocol (MCP) server implementation in TypeScript that provides weather information tools for AI assistants.
Description
This project demonstrates how to create an MCP server that exposes weather-related tools to Large Language Models (LLMs). The server provides a fetch-weather tool that retrieves current weather data and forecasts for any city using the Open-Meteo API.
Features
- Weather Tool: Fetch current weather conditions and forecasts for any city
- Input Validation: Uses Zod for robust input/output validation
- MCP Protocol: Compatible with AI assistants that support the Model Context Protocol
- TypeScript: Fully typed implementation for better development experience
Prerequisites
- Node.js (version 14 or higher)
- npm or yarn package manager
Installation
- Clone the repository:
- Install dependencies:
Usage
Running the Server
To start the MCP server:
The server will start and listen for MCP connections via stdio transport.
Available Tools
fetch-weather
Retrieves weather information for a specified city.
Parameters:
city(string): Name of the city to get weather information for
Example Response: The tool returns current weather conditions including:
- Temperature
- Precipitation
- Day/night status
- Rain information
- Hourly forecast data
Project Structure
Dependencies
- @modelcontextprotocol/sdk: Core MCP SDK for server implementation
- zod: Schema validation library for input/output validation
API Integration
This project integrates with the following external APIs:
- Open-Meteo Geocoding API: For converting city names to coordinates
- Open-Meteo Weather API: For retrieving weather data and forecasts
How It Works
- The server creates an MCP server instance with the name "PRO INDUSTRIAL MCP SERVER"
- It defines a
fetch-weathertool that:- Accepts a city name as input
- Geocodes the city name to get coordinates
- Fetches weather data using the coordinates
- Returns formatted weather information
- The server connects via stdio transport for communication with AI assistants
Development
The main server logic is implemented in main.ts:7-55. Key components include:
- Server initialization (
main.ts:7-10) - Tool definition (
main.ts:13-50) - Transport setup (
main.ts:54-55)
Error Handling
The weather tool includes error handling for:
- Cities that cannot be found
- API request failures
- Invalid input parameters (via Zod validation)
License
ISC
Contributing
This is a practice project for learning MCP server development. Feel free to fork and experiment with additional tools and features.
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables AI assistants to fetch current weather conditions and forecasts for any city using the Open-Meteo API. Provides temperature, precipitation, and hourly forecast data through natural language queries.