Infrastructure diagrams are essential but tedious to maintain. Imagine an agentic AI that listens to your description (“.NET app on a Windows VM connecting to Azure SQL”) and autonomously produces an editable architecture diagram – not just a static image, but a fully editable .drawio file you can refine.

In this session, you’ll build exactly that. We’ll move beyond simple chatbots and create an autonomous agent powered by the Microsoft Agent Framework (in .NET). The agent uses Azure OpenAI (or local LLMs) to understand intent, then orchestrates a series of actions: it calls a Model Context Protocol (MCP) server to generate a Draw.io diagram, and can even open the editor for further tweaks. You’ll see how agentic AI plans, uses tools, and iterates – all locally first to save cloud costs, then deployed to Azure AI Foundry.

Tools & Technologies:

.NET 8 / C# – Microsoft Agent Framework (for building autonomous agents)
Azure OpenAI (or local alternatives like Ollama) – natural language understanding
Model Context Protocol (MCP) – connecting to a Draw.io diagram server as a tool
Draw.io – open‑source diagram editor (embedded or self‑hosted)
Docker – local MCP server containerisation
Azure AI Foundry – production deployment and monitoring

What You’ll Learn:
How to build an agentic AI that plans and uses tools, not just responds
Integrating LLMs with the Microsoft Agent Framework for intent extraction and multi‑step reasoning
Using MCP servers to extend agent capabilities (diagram generation, file I/O)
Generating editable .drawio files and embedding the Draw.io editor
A local‑first development approach (Ollama/LM Studio + Docker) to iterate without cloud spend
The seamless path from local prototype to production on Azure AI Foundry

Audience: .NET developers, cloud architects, and AI enthusiasts eager to move from chatbots to real‑world agentic automation. Basic C# and Azure knowledge helpful but not required.