Learn Together: Building an MCP Server with AI Toolkit

AI is evolving fast—but building real, useful AI applications still requires more than just a smart model. That’s where the Model Context Protocol (MCP) comes in.

MCP is an open standard that helps AI systems talk to tools, data, and services in a clean, reusable way. Think of it as the coordination layer that turns a smart model into an intelligent application. Whether you’re integrating APIs, calling scripts, or orchestrating multiple agents, MCP provides the structure that makes it all work together.

And thanks to the AI Toolkit for Visual Studio Code, working with MCP is now easier than ever. The toolkit gives you an intuitive playground, built-in server tools, model integration, and everything you need to go from idea to working prototype without leaving your editor.

📅 Join the Event: Learn Together – Building an MCP Server with AI Toolkit

In this live, hands-on workshop, we’ll walk through four practical modules designed to help you build, configure, and test your own MCP server from scratch. You’ll get to follow along step-by-step using the AI Toolkit extension for VS Code.

Whether you're building multi-agent workflows, enabling tools in a RAG app, or just looking for a smarter way to connect your models to real-world actions, this workshop is for you.

🧪 What You’ll Learn – Inside the Labs

Here’s a preview of the four modules we’ll cover during the livestream:

Module 1: Getting Started with AI Toolkit

In this lab, you’ll install and configure the AI Toolkit for Visual Studio Code, then dive into its key features—like the model catalog, interactive playground, and agent builder. You'll build your first functional agent, experiment with real-time model testing, and evaluate outputs using built-in metrics. Along the way, you’ll also explore batch processing and multimodal support. By the end, you’ll have a solid foundation in what the AI Toolkit can do.

Module 2: Integrating MCP with Your Agents

This lab introduces the Model Context Protocol (MCP) and shows you how to supercharge your AI agents with tool-using capabilities. You’ll connect to existing MCP servers, like the Playwright automation server, then integrate them into your agents using the AI Toolkit. From configuring tools to testing and deploying MCP-powered agents, you’ll see how external tools become part of your model’s workflow. This lab is your bridge between smart models and real-world actions.

Module 3: Building and Debugging Custom MCP Servers

Here, you’ll go beyond using prebuilt MCP servers and start creating your own. You’ll learn how to use the latest MCP Python SDK to configure and debug a custom server, including a weather tool example. The lab walks through setting up the MCP Inspector, testing tool calls, and running agents in a local dev environment. You’ll leave with a full understanding of how to build, test, and debug your own MCP endpoints.

Module 4: Real-World MCP Server – GitHub Clone Agent

In this final lab, you’ll build a GitHub clone MCP server that replicates real dev workflows. It features smart repo cloning, intelligent directory setup, error handling, and direct integration with VS Code. You’ll even enable GitHub Copilot’s Agent Mode to interact with your custom tools. This lab wraps everything together into a production-grade example of what’s possible with MCP.

💡 Why MCP + AI Toolkit?

The magic of MCP is in its modularity. It gives developers a structured way to define tools, link models, and control interactions, all in a language-agnostic, reusable way. And when paired with the AI Toolkit, you get a guided development experience with built-in tools for testing, telemetry, evaluation, and more.

Whether you're building an agent to automate tasks, assist users, or connect enterprise systems, MCP makes it possible. The AI Toolkit makes it easier!

📅 Save the Date!

Don’t miss your chance to build alongside us and see MCP in action. This is more than just a demo, it’s a full walkthrough of what modern, production-aware AI development looks like.

✅ Register now to join the Learn Together livestream on the 5th August and take your first step toward building smarter AI applications.

👉 Click here to register for the event!