This course path introduces the Model Context Protocol (MCP) as a practical way to connect AI agents with external tools, data sources, and actions. You will start by building agents in Python, understanding how they manage conversations, and adding tools they can use to complete tasks. You will then design and run your own MCP servers, implementing tools, resources, and prompts that agents can call. The path covers different transport methods and shows how to connect Python agents to MCP servers for real application workflows. In the advanced portion, you will improve agent-server interactions with tool caching, connect agents to multiple MCP servers, integrate servers with web frameworks, and add authentication middleware. This path is intended for intermediate Python developers who want to build more capable agentic applications.
