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MCP Client Example ☀️

MCP Client Example ☀️

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redandgreen.co.ukDeveloper Tools26Updated 86w ago
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About MCP Client Example ☀️

A Python example project showing how to build an MCP server with tools and call them from an MCP client. It is intended for developers who are learning the MCP Python SDK.

Key features

  1. 01Connects to the server over stdio
  2. 02Provides a BMI calculation tool
  3. 03Provides an async weather lookup tool
  4. 04Lists and calls server tools

Use cases

  1. 01Learning basic MCP client and server implementation
  2. 02Referencing tool calls in the MCP Python SDK

MCP support

This project contains both an MCP client and an MCP server, with the client connecting over stdio and calling the server's tools.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Client Example ☀️

This project demonstrates a simple client-server implementation using the Model Context Protocol (MCP), which is a standardized way to connect large language models with tools and data.

Overview

This example shows how to:

  • Create an MCP server with custom tools
  • Connect to the server using an MCP client
  • Call tools and get responses from the server

Tutorial Video

MCP Tutorial Video

Click the image above to watch a tutorial on MCP implementation.

Project Structure

.
├── pyproject.toml
├── README.md
├── src
│   ├── client
│   │   └── mcp_client.py      # MCP client implementation
│   └── server
│       └── example_server.py  # MCP server with tools
└── uv.lock

Server Implementation

The server exposes two tools:

  1. calculate_bmi - A simple calculator that computes Body Mass Index
  2. fetch_weather - An async tool that retrieves weather data from an external API

Client Implementation

The client connects to the server via stdio, initializes a session, and calls the server's tools.

Getting Started

Prerequisites
  • Python 3.9+
  • uv (Python package manager)
Installation
# Install dependencies
uv install -e .
Running the Example
  1. Start the client (which will automatically start the server):
uv run src/client/mcp_client.py

Usage

The client will:

  1. Connect to the server
  2. List available tools
  3. Call the BMI calculator with sample data
  4. Call the weather tool with sample coordinates

Example Response

Available tools: meta=None nextCursor=None tools=[...]
BMI calculation result: 22.857142857142858
Weather data: {"current_weather":{"temperature":14.2,"windspeed":12.6, ...}}

Test with MCP Inspector

( run command below and then visit http://localhost:5173 )

  ❯ mcp dev src/server/example_server.py
Starting MCP inspector...
Proxy server listening on port 3000

🔍 MCP Inspector is up and running at http://localhost:5173 🚀
New SSE connection
Query parameters: {
  transportType: 'stdio',
  command: 'uv',
  args: 'run --with mcp mcp run src/server/example_server.py',

Resources

This project uses:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.