Model Context Protocol (MCP) is changing how AI agents connect to real-world capabilities, data, and workflows. Instead of building one-off integrations for every application, developers can create structured connections that allow agents to discover and use tools, access resources, and interact with external systems through a consistent protocol. This course gives you a practical path from understanding MCP fundamentals to integrating it into reliable AI-powered applications. You will learn how MCP works at the architectural level, including the relationship between hosts, clients, and servers. You will then configure an MCP environment, expose tools and resources, connect an AI agent to MCP capabilities, and design workflows that let agents select and invoke the right functionality. The course also covers input validation, permissions, error handling, observability, and practical security considerations for production-oriented integrations. This course is designed for software developers, AI engineers, and technical product builders who already understand basic programming and want to build more capable agent applications. Familiarity with APIs, JSON, and large language model concepts will help, but you do not need advanced machine learning expertise. By the end, you will have the knowledge to evaluate MCP use cases, build a functional MCP server, connect it to an AI agent, and assemble a complete application workflow around it. Start building AI systems that can interact with the tools and information your users actually need.