3 Things This Tutorial Covers
Dive into building your very own custom MCP server in Python—from setup to real-world AI agent integration—so you can effortlessly expose new tools, resources, and prompts to any LLM!
- ⚙️ Project Setup & SDK Initialization
Learn how to bootstrap a fresh Python project using the modern UV package manager, install the MCP Python SDK, and scaffold your firstmain.pyfile—getting you up and running in minutes without the boilerplate headaches. - 🛠️ Defining Custom Tools, Resources & Prompts
See how to craft Python functions as MCP “tools” (for actions like appending notes), “resources” (for retrieving the latest entry), and reusable “prompts” (for summarizing all your notes)—complete with clear documentation strings so AI agents know exactly when and how to call them. - 🤖 Seamless AI Agent Integration & Testing
Walk through installing your MCP server into an AI client (e.g., Claude Desktop), troubleshoot common configuration hiccups, and interact live—adding notes, reading back entries, and generating summaries—to prove end-to-end connectivity and unlock limitless automation possibilities.
