MCP Weather Server

A simple MCP (Model Context Protocol) server built during an Agentic AI Internship. This server demonstrates how MCP can be used to provide tools, resources, and prompts to AI applications.

Features

MCP servers can provide the following functionalities:

Resources

File-like data that can be read by clients, such as API responses or file contents.

Tools

Functions that can be called by Large Language Models (LLMs) with user approval.

Prompts

Pre-written templates that help users accomplish specific tasks efficiently.

Requirements

• Python 3.10 or higher

• uv package manager

• Python MCP SDK 1.2.0 or higher

• httpx

Project Setup

1. Install uv

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Initialize the Project

uv init .

3. Install Dependencies

uv add "mcp[cli]" httpx

4. Create the Server File

Create a file named weather.py and add the MCP server implementation.

5. Run the Server

uv run weather.py

Project Structure

.
├── weather.py
├── pyproject.toml
├── uv.lock
├── README.md
└── .gitignore

Learning Outcomes

• Understanding MCP architecture

• Building custom MCP tools

• Integrating APIs using Python

• Running MCP servers with uv

• Working with Agentic AI applications

Author

Vishal M K B.E. CSE (AI & ML)