John Savill's Technical Training presents a step-by-step guide on using Azure Logic Apps as Model Context Protocol (MCP) servers for AI applications, highlighting actionable setup and integration strategies.

Using Logic Apps as Model Context Protocol (MCP) Servers for AI Applications

John Savill walks through the process of implementing Azure Logic App connectors and workflows as MCP servers for AI applications:

Introduction

• Overview of Logic Apps in Azure and their use in workflow automation
• Explanation of the MCP server concept for agent-based AI applications

Logic Apps and AI Integration

• Setup required for Logic Apps to act as tools in AI projects
• Details on using Logic App connectors to construct MCP-capable workflows

MCP Server Implementation

• Step-by-step Logic App instance creation for the Foundry environment
• Workflow creation and configuration required to support multiple MCP servers
• Authentication methods to secure MCP endpoints
• How MCP is utilized by AI agents to interact with Logic Apps

Using MCP Servers from Agents

• Example of calling MCP endpoints from an AI agent
• Considerations for workflow design to support agent integration

References and Resources

• Official Microsoft Documentation – Set up Model Context Protocol server (Standard)
• Whiteboard Diagram

Additional Learning

• Weekly Azure Updates and Master Classes for deeper dives
• Hands-on resources for certification and further technical training

Summary

This guide illustrates best practices for connecting AI applications to Azure workflows via MCP, enabling more dynamic and scalable agent-based integrations using Microsoft cloud technologies.