Create MCP Servers for AI Agents in Python and TypeScript

AI agents are powerful, but they need access to real-world tools and data to be truly useful. The Model Context Protocol (MCP) bridges this gap by standardizing how AI models interact with your local environment. In this text-based course, you will learn how to build your own MCP servers from the ground up using both Python and TypeScript. You will start with foundational concepts of agentic AI communication and progress to writing secure, typed, and asynchronous code that exposes your custom tools to AI assistants. What you will learn: • Understand the core architecture and terminology of the Model Context Protocol. • Build fully functional MCP servers using Python and TypeScript. • Apply modern programming practices like async/await, Python type hints, and TypeScript interfaces. • Configure secure access to local files, databases, and external APIs. • Practice integrating your custom servers with modern AI agent workflows. • Manage dependencies using modern packaging and virtual environments. The course flows logically from basic definitions and environment setup to hands-on, written coding exercises. Designed for beginner developers with basic Python or JavaScript knowledge who want to explore agentic AI, this guide requires no prior machine learning experience. Start reading today to give your AI agents the tools they need to interact with the real world.