[Webinar] Build and Ship Your Own MCP Server and Client

Description

Want to connect AI models like Claude, Gemini, or ChatGPT directly to real-world tools and data? 🚀 In this session, I will show you how to build and deploy your own Model Context Protocol (MCP) server and client — the emerging open standard that makes AI integration seamless, modular, and production-ready. The Model Context Protocol (MCP) lets AI models securely access APIs, databases, files, and other resources — all through a consistent interface. Using FastMCP, a Pythonic SDK, you’ll learn how to design, build, and ship your own MCP server that works with AI assistants like Claude Desktop, ChatGPT, and Gemini CLI. 💡 In this video, you’ll learn: • What the Model Context Protocol (MCP) is and why it matters for AI development. • The architecture of MCP — Host, Client, and Server explained. • How AI agents communicate using standardized message and transport protocols (stdio, HTTP/SSE). • How to use the FastMCP SDK to create MCP servers and clients in Python. • Real-world MCP use cases — from automating business workflows to enhancing developer productivity. • How to deploy MCP servers locally or to the cloud (Google Cloud Run, AWS Lambda). • How to integrate your MCP server with AI assistants and debug it using MCP Inspector. • Live demo and walkthrough of building and running your own MCP application. 🔥 Why you should watch: MCP is revolutionizing how LLMs connect to the world — it’s the REST API for AI. Whether you’re building a personal AI assistant, an enterprise automation agent, or experimenting with multi-agent systems, understanding MCP is key to the next generation of AI application development. 🔗 Resources from the video: • Connect with the speaker, Poo Kuan Hoong: https://www.linkedin.com/in/kuanhoong/ • MCP demo codes on GitHub: https://github.com/kuanhoong/mcp • Slides: https://drive.google.com/file/d/1DlcttZ4VLkdVhXceaoE49dkNmNLEoA5d/view?usp=sharing