The Model Context Protocol (MCP) is redefining how large language models interact with the outside world, enabling them to securely call external tools and APIs. In this session, we’ll explore how Azure Functions — enhanced with the new mcpTool trigger — can act as scalable, cloud-hosted MCP servers.

You’ll learn how to:
• Deploy a Python-based Azure Functions MCP server in minutes using Microsoft’s public sample.
• Define custom MCP tools that allow AI clients (like VS Code Agent Mode) to take real-world actions.
• Implement a practical scenario where MCP tools interact with Azure DevOps to fetch data, automate workflows, and respond to natural language prompts.
• Extend the pattern to integrate with any API or service, from cloud management to enterprise systems.

We’ll cover both the technical setup and real-world use cases, showing how this approach unlocks a new generation of AI-driven automation. By the end, you’ll see how to turn Azure Functions into a powerful bridge between LLMs and the tools your business runs on.