Introduction to AI Agents and Model Context Protocol (MCP)

As AI-assisted engineering evolves, understanding how autonomous agents interact with external data is becoming a core skill for modern developers. The Model Context Protocol (MCP) provides an open standard to securely connect LLMs to data sources, development environments, and APIs. This written course guides you from foundational AI concepts to the mechanics of agentic workflows. You will discover how to leverage MCP to build smarter, context-aware systems that go beyond basic text generation. What you'll learn: - Understand the foundational architecture of AI agents, including planning, memory, and tool usage - Explore the Model Context Protocol (MCP) and how it standardizes LLM-to-data communication - Analyze how agents securely access local files, databases, and remote development environments - Evaluate the capabilities and current limitations of AI-assisted engineering tools - Learn how to design scalable agentic workflows that integrate with existing codebases The course begins with essential terminology and the evolution of AI agents before examining the technical specifications of MCP. You will read through clear conceptual explanations and structured text-based implementation examples to understand how to apply these patterns in your own projects. This course is designed for software developers and tech enthusiasts who are new to AI agents and want a clear, conceptual foundation without complex prerequisites. Start reading today to master the next frontier of AI-assisted development.