They say the Model Context Protocol (MCP) is the "USB-C for AI"—a standard to connect models to data. But if you treat MCP like a simple REST API, you are missing 80% of its potential.

A standard API is passive; it waits to be called. An MCP Server is active—it is like a robotic arm plugged into the AI's nervous system. It doesn't just execute commands; it can "borrow" the AI's brain to reason, plan, and adapt on the fly.

In this advanced, code-heavy session, we will skip the "Hello World" demos and go straight into the IDE to architect a production-grade Windows Diagnostic Agent using C# and the .NET MCP SDK.

We will live-code the implementation of Advanced MCP Capabilities:

• The Bi-Directional Architecture: Moving beyond simple tools to build servers that can query the host, requesting user confirmation or additional context via Elicitation.
• The "Brain Borrowing" Pattern: A deep dive into Sampling—the killer feature that allows your C# tool to send a prompt back to the LLM to generate dynamic code or queries on the fly (e.g., writing a custom PowerShell script to solve an unforeseen error).
• Security & Feedback: Implementing Roots to define filesystem boundaries and Notifications for real-time agent feedback.
• Scalable Transport: Switching from Studio to Streamable HTTP (SSE) to prepare your agent for cloud deployment.

This session is for architects and senior C# developers who have completed the theory and want to see the actual code required to build autonomous, state-aware agents.

You will learn:

• What the Model Context Protocol (MCP) is, when to use it, and how to build an MCP server using C#.
• How to implement bi-directional communication and the Sampling pattern to actively borrow the AI's reasoning.
• How to implement real-time agent notifications and request user confirmation via Elicitation.