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Weather Server — Demo

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Demo MCP server that provides weather data for cities, with tools to get weather and list available cities.

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Описание

Demo MCP server that provides weather data for cities, with tools to get weather and list available cities.

README

Demo project from the YouTube video: "What is MCP? Model Context Protocol Explained (2026)"

MCP Tutorial: Connect Claude to Any Tool (2026)

Watch the MCP Tutorial

Click the image to watch the MCP guide on YouTube

This is a minimal Model Context Protocol (MCP) server written in Python. It exposes two tools that an AI assistant can call:

Tool Description
get_weather Returns weather data for a given city
list_cities Lists all cities with available data

Prerequisites

  • Python 3.10 or higher
  • pip

Setup & Run

# 1. Clone or download this folder
cd demo/

# 2. (Optional) Create a virtual environment
python -m venv .venv
source .venv/bin/activate        # macOS / Linux
.venv\Scripts\activate           # Windows

# 3. Install the MCP SDK
pip install -r requirements.txt

# 4. Run the server
python weather_server.py

The server starts and listens on stdio — it's ready for an MCP host (like Claude Desktop or a custom client) to connect.


Connect to Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "weather": {
      "command": "python",
      "args": ["/full/path/to/demo/weather_server.py"]
    }
  }
}

Restart Claude Desktop. Then ask it:

"What's the weather in Tokyo?"

Claude will automatically call the get_weather tool and return:

🌍 Weather in Tokyo:
🌡️  Temperature: 18°C
☁️  Condition:   Clear
💧 Humidity:    55%
💨 Wind:        10 km/h NE

Extend to a Real Weather API

Replace the WEATHER_DATA dict with a live API call:

import httpx

async def fetch_live_weather(city: str) -> dict:
    url = f"https://api.openweathermap.org/data/2.5/weather"
    params = {"q": city, "appid": "YOUR_API_KEY", "units": "metric"}
    async with httpx.AsyncClient() as client:
        resp = await client.get(url, params=params)
        data = resp.json()
        return {
            "temp": data["main"]["temp"],
            "condition": data["weather"][0]["description"].title(),
            "humidity": data["main"]["humidity"],
            "wind": f"{data['wind']['speed']} m/s"
        }

Project Structure

demo/
├── weather_server.py   # MCP server — all logic here
├── requirements.txt    # pip install mcp
└── README.md           # This file

How MCP Works (Quick Recap)

Claude Desktop (Host)
    └── MCP Client (built into host)
            └── MCP Protocol (JSON-RPC 2.0 over stdio)
                    └── weather_server.py (YOUR server)
                            └── Returns weather data

The AI model never calls your server directly — the MCP client handles discovery, schema validation, and communication. You just implement the logic.


Next Steps

  • Add more tools: get_forecast, get_air_quality
  • Switch transport from stdio to HTTP + SSE for a remote server
  • Publish your server to the MCP community registry

Official MCP Resources

📖 Documentation

Resource Link
Official Docs https://modelcontextprotocol.io/docs
Getting Started https://modelcontextprotocol.io/introduction
All Examples https://modelcontextprotocol.io/examples
GitHub Organization https://github.com/modelcontextprotocol
All Official Servers https://github.com/modelcontextprotocol/servers

🔌 Official MCP Server Examples (from the video)

These are production-ready servers maintained by Anthropic — install and use them today:

Server What it does GitHub
🐙 GitHub Browse repos, read files, manage PRs and issues via AI https://github.com/modelcontextprotocol/servers/tree/main/src/github
🗄️ PostgreSQL Query your database with natural language https://github.com/modelcontextprotocol/servers/tree/main/src/postgres
📁 Filesystem Read and write local files directly from AI https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem
🔍 Brave Search Real-time web search inside any AI chat https://github.com/modelcontextprotocol/servers/tree/main/src/brave-search
💬 Slack Read channels, summarize threads, post messages https://github.com/modelcontextprotocol/servers/tree/main/src/slack
🧠 Memory Persistent AI memory via a knowledge graph https://github.com/modelcontextprotocol/servers/tree/main/src/memory

📦 SDKs

Language Install GitHub
Python pip install mcp https://github.com/modelcontextprotocol/python-sdk
TypeScript / Node.js npm install @modelcontextprotocol/sdk https://github.com/modelcontextprotocol/typescript-sdk

from github.com/shazforiot/MCP-Explained

Установка Weather Server — Demo

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/shazforiot/MCP-Explained

FAQ

Weather Server — Demo MCP бесплатный?

Да, Weather Server — Demo MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Weather Server — Demo?

Нет, Weather Server — Demo работает без API-ключей и переменных окружения.

Weather Server — Demo — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Weather Server — Demo в Claude Desktop, Claude Code или Cursor?

Открой Weather Server — Demo на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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