Introduction

So far, you have interacted with MCP servers using “Host” applications like the MCP Inspector or Claude Desktop. These tools are excellent for testing and manual chat, but the real power of the Model Context Protocol is automation.

In this lesson, you will step behind the curtain and become the Host yourself. You will write code that acts as an MCP Client, giving you full programmatic control over Tools, Resources, and Prompts.

You will start by building a unified “Travel Planner” server and writing a Python script to drive it manually. Then, you will take a significant leap forward: you will connect a cloud-based Large Language Model (Claude) to your local machine. Using the Anthropic API and HTTP tunneling, you will empower the LLM to discover your local tools and execute them autonomously to answer questions.

By the end of this lesson, you will be able to:

• Construct a custom MCP Client in Python to interact with servers programmatically.
• Implement a unified server architecture that combines Tools, Resources, and Prompts in a single application.
• Configure an HTTP-based MCP server and expose it securely to the internet using tunneling tools.
• Integrate the Anthropic API with the MCP Connector to build an AI agent that executes local code.

You are about to move from simply using MCP tools to engineering the systems that drive them.