Guest Blog: Build an AI App That Can Browse the Internet Using Microsoft’s Playwright MCP Server & Semantic Kernel — in Just 4 Steps

Blog Summary:

This blog provides a comprehensive guide on how to build an LLM app in .NET that can browse the internet, using Microsoft’s Playwright MCP Server and Semantic Kernel, in just 4 steps. The author explains the process of setting up Semantic Kernel, installing the official C# MCP in a .NET app, converting MCP functions to Kernel Functions, and references key resources for understanding MCP. The blog emphasizes the ease of integrating MCP server tools with Semantic Kernel, making AI app development more accessible and efficient.

Step 1: Setup Semantic Kernel

The first step involves setting up Semantic Kernel to prepare for integrating with the MCP server.

Step 2: Install official C# MCP & Setup MCP Client

Next, the blog outlines the process of installing the official C# MCP in a .NET app and setting up the MCP client to interact with the server. It also includes a verification step to ensure the client is correctly configured.

Step 3: Convert MCP Functions to Kernel Functions

To use MCP tools or plugins with Semantic Kernel, the blog explains the process of converting MCP functions into Kernel Functions. While initially an extra step, the blog mentions an extension provided by SK for this process.

Step 4: Building an AI App with MCP Server

The blog hints at further exploration by mentioning the possibility of building a custom MCP server from scratch in a future blog post, showcasing the evolving landscape of AI app development.

Finally, the blog wraps up by encouraging readers to stay tuned for upcoming content and provides references for additional learning about MCP, including a visual guide and comparison with API Model Context Protocol.

By following these steps, developers can harness the power of MCP server tools through Semantic Kernel integration, enhancing the capabilities of their AI applications.