Congratulations!

1. Congratulations!

Congratulations! You made it to the end of the course! Let's recap everything you've learned.

2. Chapter 1

In Chapter 1, you discovered MCP — the Model Context Protocol — a standardized way for AI applications to connect with external tools, data, and services. Think of it as the USB-C for AI. You built your first MCP server using the mcp Python library, defined tools with docstrings and type hints, and connected a Python client to the server over stdio transport.

3. Chapter 2

In Chapter 2, you expanded your MCP servers with resources for read-only data and prompts for reusable instruction templates. You then wired everything to an LLM using OpenAI's Responses API, letting the model discover and call your MCP tools in real time, and used resources and prompts for richer, context-aware responses.

4. Chapter 3

Finally, in Chapter 3, you took your MCP servers to production. You hardened API integrations with timeouts, error handling, and secure authentication, then connected servers to databases with parameterized queries to prevent injection attacks. You wrapped up by discovering third-party MCP servers, and how to plug them in using the same client code you've been writing all along.

5. Let's practice!

Congratulations, again! Best of luck on the rest of your journey!

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