Overview
This codelab guides you through understanding and implementing the Model Context Protocol (MCP) to extend Google's Gemini AI with custom functionalities. You'll learn what MCP is, why it's valuable for LLMs, and how to build your own Python-based MCP server. The tutorial details creating tools, such as an email sender (using smtplib) and an echo service, and making them available to Gemini. You'll then develop a client application that enables Gemini to intelligently invoke these MCP tools via its function calling feature. This hands-on example demonstrates the complete workflow: from user request to Gemini's decision to use a tool, tool execution on the MCP server, and Gemini formulating a response based on the tool's output. By completing this codelab, you'll gain practical skills in making LLMs more interactive and capable by integrating them with external systems, transforming them into powerful agents by leveraging context through MCP.
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