Merge pull request #311087 from cephalin/pr-311085

Restructure AI integration docs into scenario-based articles (Fixes #311085)

Author: denrea

articles/app-service/overview-ai-integration.md

@@ -5,7 +5,7 @@ author: cephalin
 ms.author: cephalin
 ms.service: azure-app-service
 ms.topic: overview
-ms.date: 12/12/2025
+ms.date: 01/29/2026
 ms.custom:
   - build-2025
 ms.collection: ce-skilling-ai-copilot
@@ -14,128 +14,32 @@ ms.update-cycle: 180-days
 
 # Integrate AI into your Azure App Service applications
 
-
-This article guides you to language-specific tutorials and resources to help you build intelligent applications with App Service.
-
 Azure App Service makes it easy to integrate AI capabilities into your web applications across multiple programming languages and frameworks. Whether you want to use powerful Azure OpenAI models, deploy local small language models (SLMs) directly with your apps, build agentic web applications, expose your app as a tool for AI agents using OpenAPI, host Model Context Protocol (MCP) servers, or implement advanced patterns like retrieval augmented generation (RAG), App Service provides the flexible, secure platform you need for AI-powered applications.
 
+## Why App Service for AI applications?
+
 App Service offers several advantages for developing and deploying AI-powered applications:
 
 - **Native integration with Azure AI services** - Seamlessly connect to Azure OpenAI and other AI services using managed identities for secure, passwordless authentication
 - **Local SLM support** - Use sidecar extensions to deploy smaller language models directly with your application
 - **Enterprise-grade security** - Implement network isolation, end-to-end encryption, and role-based access control
 - **Simplified DevOps with GitHub integration** - Streamline CI/CD pipelines using GitHub Actions, leverage GitHub Codespaces with integrated GitHub Copilot for AI-assisted development, and create end-to-end workflows from development to production deployment
 
-## Build chatbots and RAG applications in App Service
-
-Build intelligent web apps that use Azure OpenAI for chat or retrieval augmented generation (RAG). These tutorials show you how to integrate Azure OpenAI and (optionally) Azure AI Search to create chatbots and RAG solutions in your preferred language, using managed identities for secure authentication.
-
-### [.NET](#tab/dotnet)
-- [Tutorial: Build a chatbot with Azure App Service and Azure OpenAI (.NET)](tutorial-ai-openai-chatbot-dotnet.md)
-- [Tutorial: Build a retrieval augmented generation app in Azure App Service with Azure OpenAI and Azure AI Search (.NET)](tutorial-ai-openai-search-dotnet.md)
-- [Deploy a .NET Blazor App Connected to Azure SQL and Azure OpenAI on Azure App Service](deploy-intelligent-apps-dotnet-to-azure-sql.md)
-
-### [Java](#tab/java)
-- [Tutorial: Build a chatbot with Azure App Service and Azure OpenAI (Spring Boot)](tutorial-ai-openai-chatbot-java.md)
-- [Tutorial: Build a retrieval augmented generation app in Azure App Service with Azure OpenAI and Azure AI Search (Spring Boot)](tutorial-ai-openai-search-java.md)
-- Sample: [SpringBoot-Petclinic-AI-Chat-on-App-Service](https://github.com/Azure-Samples/SpringBoot-Petclinic-AI-Chat-on-App-Service)
-
-### [Node.js](#tab/nodejs)
-- [Tutorial: Build a chatbot with Azure App Service and Azure OpenAI (Express.js)](tutorial-ai-openai-chatbot-node.md)
-- [Tutorial: Build a retrieval augmented generation app in Azure App Service with Azure OpenAI and Azure AI Search (Express.js)](tutorial-ai-openai-search-nodejs.md)
-
-### [Python](#tab/python)
-- [Tutorial: Build a chatbot with Azure App Service and Azure OpenAI (Flask)](tutorial-ai-openai-chatbot-python.md)
-- [Tutorial: Build a retrieval augmented generation app in Azure App Service with Azure OpenAI and Azure AI Search (FastAPI)](tutorial-ai-openai-search-python.md)
-- [Microsoft Foundry tutorial: Deploy an enterprise chat web app](/azure/ai-foundry/tutorials/deploy-chat-web-app?toc=/azure/app-service/toc.json&bc=/azure/bread/toc.json)
------
-
-## Build agentic web applications
-
-Transform your traditional CRUD web applications for the AI era by adding agentic capabilities with frameworks like Microsoft Semantic Kernel, LangGraph, or Foundry Agent Service. Instead of users navigating forms, textboxes, and dropdowns, you can offer a conversational interface that lets users "talk to an agent" that intelligently performs the same operations your app provides. This approach enables your web app to reason, plan, and take actions on behalf of users.
-
-### [.NET](#tab/dotnet)
-- [Tutorial: Build an agentic web app in Azure App Service with Microsoft Agent Framework or Foundry Agent Service (.NET)](tutorial-ai-agent-web-app-semantic-kernel-foundry-dotnet.md)
-- Blog series: Build long-running AI agents with Microsoft Agent Framework
-  - [Part 1: Build long-running AI agents on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/build-long-running-ai-agents-on-azure-app-service-with-microsoft-agent-framework/4463159)
-  - [Part 2: Build long-running AI agents on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/part-2-build-long-running-ai-agents-on-azure-app-service-with-microsoft-agent-fr/4465825)
-  - [Part 3: Client-side multi-agent orchestration on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/part-3-client-side-multi-agent-orchestration-on-azure-app-service-with-microsoft/4466728)
-
-### [Java](#tab/java)
-- [Tutorial: Build an agentic web app in Azure App Service with Microsoft Semantic Kernel or Foundry Agent Service (Spring Boot)](tutorial-ai-agent-web-app-semantic-kernel-java.md)
-
-### [Node.js](#tab/nodejs)
-- [Tutorial: Build an agentic web app in Azure App Service with LangGraph or Foundry Agent Service (Node.js)](tutorial-ai-agent-web-app-langgraph-foundry-node.md)
-
-### [Python](#tab/python)
-- [Tutorial: Build an agentic web app in Azure App Service with LangGraph or Foundry Agent Service (Python)](tutorial-ai-agent-web-app-langgraph-foundry-python.md)
------
-
-## App Service as OpenAPI tool in Microsoft Foundry agent
-
-Empower your existing web apps by exposing their capabilities to Foundry Agent Service using OpenAPI. Many web apps already provide REST APIs, making them ideal candidates for integration into agents that can call REST APIs as tools. By connecting Foundry Agent Service to these APIs, you can rapidly create powerful, feature-rich agents with little code.
-
-### [.NET](#tab/dotnet)
-- [Add an App Service app as a tool in Foundry Agent Service (.NET)](tutorial-ai-integrate-azure-ai-agent-dotnet.md)
-
-### [Java](#tab/java)
-- [Add an App Service app as a tool in Foundry Agent Service (Spring Boot)](tutorial-ai-integrate-azure-ai-agent-java.md)
-
-### [Node.js](#tab/nodejs)
-- [Add an App Service app as a tool in Foundry Agent Service (Node.js)](tutorial-ai-integrate-azure-ai-agent-node.md)
-
-### [Python](#tab/python)
-- [Add an App Service app as a tool in Foundry Agent Service (Python)](tutorial-ai-integrate-azure-ai-agent-python.md)
------
-
-## App Service as Model Context Protocol (MCP) servers
-
-Integrate your web app as a [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) server to extend the capabilities of leading personal AI agents such as GitHub Copilot Chat, Cursor, and Winsurf. By exposing your app's APIs through MCP, you can supercharge these agents with the unique features and business logic your web app already provides, without major development effort or rearchitecture.
-
-### [.NET](#tab/dotnet)
-- [Integrate an App Service app as an MCP Server for GitHub Copilot Chat (.NET)](tutorial-ai-model-context-protocol-server-dotnet.md)
-- Sample: [Host a .NET MCP server on Azure App Service](https://github.com/Azure-Samples/remote-mcp-webapp-dotnet)
-
-### [Java](#tab/java)
-- [Integrate an App Service app as an MCP Server for GitHub Copilot Chat (Spring Boot)](tutorial-ai-model-context-protocol-server-java.md)
-
-### [Node.js](#tab/nodejs)
-- [Integrate an App Service app as an MCP Server for GitHub Copilot Chat (Node.js)](tutorial-ai-model-context-protocol-server-node.md)
-- Sample: [Host a Node.js MCP server on Azure App Service](https://github.com/Azure-Samples/remote-mcp-webapp-node)
-
-### [Python](#tab/python)
-- [Integrate an App Service app as an MCP Server for GitHub Copilot Chat (Python)](tutorial-ai-model-context-protocol-server-python.md)
-- Sample: [Host a Python MCP server on Azure App Service](https://github.com/Azure-Samples/remote-mcp-webapp-python)
-- Sample: [Host a Python MCP server with key-based authorization on Azure App Service](https://github.com/Azure-Samples/remote-mcp-webapp-python-auth)
-- Sample: [Host a Python MCP server with OAuth 2.0 authorization on Azure App Service](https://github.com/Azure-Samples/remote-mcp-webapp-python-auth-oauth) - Deploy an MCP server with Python and [Open Authorization (OAuth) 2.0 authorization with Microsoft Entra ID](/entra/architecture/auth-oauth2).
------
-
-## Use a local SLM (sidecar container)
-
-Deploy a web app with a local small language model (SLM) as a sidecar container to run AI models entirely within your App Service environment. No outbound calls or external AI service dependencies required. This approach is ideal if you have strict data privacy or compliance requirements, as all AI processing and data remain local to your app. App Service offers high-performance, memory-optimized pricing tiers needed for running SLMs in sidecars.
-
-### [.NET](#tab/dotnet)
-- [Tutorial: Run chatbot in App Service with a Phi-4 sidecar extension (ASP.NET Core)](tutorial-ai-slm-dotnet.md)
-
-### [Java](#tab/java)
-- [Tutorial: Run chatbot in App Service with a Phi-4 sidecar extension (Spring Boot)](tutorial-ai-slm-spring-boot.md)
-
-### [Node.js](#tab/nodejs)
-- [Tutorial: Run chatbot in App Service with a Phi-4 sidecar extension (Express.js)](tutorial-ai-slm-expressjs.md)
-
-### [Python](#tab/python)
-- [Tutorial: Run chatbot in App Service with a Phi-4 sidecar extension (FastAPI)](tutorial-ai-slm-fastapi.md)
------
-
-## Authenticate tool calls to App Service
+## AI scenarios in App Service
 
-Secure your AI-powered applications with Microsoft Entra authentication and authorization. These guides show you how to protect your OpenAPI tools and MCP servers in Azure App Service so only authorized users and agents can access them.
+Explore these scenarios to find the right approach for your AI-powered application:
 
-- [Secure OpenAPI endpoints for Foundry Agent Service](configure-authentication-ai-foundry-openapi-tool.md) - Secure your App Service app when used as an OpenAPI tool in Foundry Agent Service with Microsoft Entra authentication
-- [Configure built-in MCP server authorization (Preview)](configure-authentication-mcp.md) - Overview of authentication methods for MCP servers
-- [Secure Model Context Protocol calls to Azure App Service from Visual Studio Code with Microsoft Entra authentication](configure-authentication-mcp-server-vscode.md) - Step-by-step guide to secure your MCP server for GitHub Copilot Chat in VS Code
+| Scenario | Description | Learn more |
+|----------|-------------|------------|
+| **Chatbots and RAG applications** | Build intelligent chatbots and RAG-powered web apps with Azure OpenAI (and optional Azure AI Search) for grounded, context-aware responses directly in App Service. | [Get started](scenario-ai-chatbot-retrieval-augmented-generation.md) |
+| **Agentic web applications** | Add autonomous, reasoning AI agents to your existing CRUD web apps using frameworks like Semantic Kernel, LangGraph, or Foundry Agent Service to enable planning, multi-step actions, and natural language interactions. | [Get started](scenario-ai-agentic-web-apps.md) |
+| **OpenAPI tools for Foundry agents** | Expose your App Service REST APIs as secure, callable tools via OpenAPI specs so Foundry Agent Service agents can discover and invoke them for real-world actions and data access. | [Get started](scenario-ai-openapi-tool.md) |
+| **Model Context Protocol servers** | Host your App Service app as an MCP server to extend AI coding assistants like GitHub Copilot Chat, Cursor, and Winsurf with your custom business logic, APIs, and data context via the Model Context Protocol. | [Get started](scenario-ai-model-context-protocol-server.md) |
+| **Local small language models** | Run small language models (e.g., Phi-3/Phi-4) entirely locally as sidecar containers in App Service for full data privacy, zero-latency inference, offline capability, and no external API calls or dependencies. | [Get started](scenario-ai-local-small-language-model.md) |
+| **Secure AI applications** | Secure your OpenAPI tools, MCP servers, and AI endpoints in App Service using Microsoft Entra ID authentication, managed identities, and built-in authorization to ensure only authorized users and agents can access them. | [Get started](scenario-ai-authentication.md) |
 
 ## More resources
 
 - [Azure OpenAI Service documentation](/azure/ai-services/openai/)
 - [Semantic Kernel documentation](/semantic-kernel/)
+- [Model Context Protocol](https://modelcontextprotocol.io/introduction)

articles/app-service/scenario-ai-agentic-web-apps.md

@@ -0,0 +1,77 @@
+---
+title: Build agentic web applications in Azure App Service
+description: Transform traditional CRUD web applications for the AI era by adding agentic capabilities with frameworks like Microsoft Semantic Kernel, LangGraph, or Foundry Agent Service.
+author: cephalin
+ms.author: cephalin
+ms.service: azure-app-service
+ms.topic: how-to
+ms.date: 01/29/2026
+ms.custom:
+  - build-2025
+ms.collection: ce-skilling-ai-copilot
+ms.update-cycle: 180-days
+---
+
+# Build agentic web applications
+
+Transform your traditional CRUD web applications for the AI era by adding agentic capabilities with frameworks like Microsoft Semantic Kernel, LangGraph, or Foundry Agent Service. Instead of users navigating forms, textboxes, and dropdowns, you can offer a conversational interface that lets users "talk to an agent" that intelligently performs the same operations your app provides. This approach enables your web app to reason, plan, and take actions on behalf of users.
+
+## Overview
+
+Agentic web applications represent a paradigm shift from traditional web interfaces. Rather than requiring users to understand and navigate your application's structure, agentic apps use AI to understand user intent, plan multi-step actions, and execute complex workflows autonomously.
+
+Key characteristics of agentic web applications include:
+
+- **Conversational interfaces**: Users express goals in natural language rather than clicking through forms
+- **Autonomous reasoning**: Agents break down complex requests into executable steps
+- **Multi-step planning**: Agents chain multiple operations to accomplish sophisticated tasks
+- **Tool usage**: Agents call your existing APIs and functions as needed to complete user requests
+- **Context awareness**: Agents maintain conversation history and application state across interactions
+- **Error handling**: Agents recover from failures and adapt their approach based on results
+
+Frameworks like Semantic Kernel, LangGraph, and Foundry Agent Service provide the orchestration layer that connects large language models with your application's business logic, enabling these agentic capabilities in your App Service applications.
+
+## When to build agentic web applications
+
+Consider adding agentic capabilities when:
+
+- **Complex workflows are common**: Users frequently need to perform multi-step operations that could be simplified through conversation
+- **Domain expertise is required**: Your application requires specialized knowledge that an AI agent can learn and apply
+- **User experience matters**: You want to reduce training time and make your application more intuitive
+- **Data exploration is important**: Users need to query, analyze, and visualize data in flexible ways
+- **Task automation is valuable**: Repetitive or time-consuming workflows could benefit from AI-assisted completion
+
+Agentic patterns work especially well for enterprise applications, data analysis tools, content management systems, and administrative interfaces where the combination of natural language understanding and automated workflows provides significant productivity gains.
+
+## Choosing an agent framework
+
+App Service supports any agent framework that runs on your chosen language stack. You have complete flexibility to use the tools and frameworks that best fit your needs. Popular options include:
+
+- **Semantic Kernel**: Microsoft's cross-platform SDK for .NET, Python, and Java, ideal for building custom agents with full control
+- **LangGraph**: Python and JavaScript framework for building stateful, multi-agent systems with complex workflows
+- **Foundry Agent Service**: Managed service for hosting production-ready agents with built-in monitoring and scalability
+- **Custom frameworks**: Any other agentic framework supported by your language (e.g., AutoGen, CrewAI, or proprietary solutions)
+
+## Get started with tutorials
+
+## [.NET](#tab/dotnet)
+- [Tutorial: Build an agentic web app in Azure App Service with Microsoft Semantic Kernel or Foundry Agent Service (.NET)](tutorial-ai-agent-web-app-semantic-kernel-foundry-dotnet.md)
+- Blog series: Build long-running AI agents with Microsoft Agent Framework
+  - [Part 1: Build long-running AI agents on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/build-long-running-ai-agents-on-azure-app-service-with-microsoft-agent-framework/4463159)
+  - [Part 2: Build long-running AI agents on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/part-2-build-long-running-ai-agents-on-azure-app-service-with-microsoft-agent-fr/4465825)
+  - [Part 3: Client-side multi-agent orchestration on Azure App Service with Microsoft Agent Framework](https://techcommunity.microsoft.com/blog/appsonazureblog/part-3-client-side-multi-agent-orchestration-on-azure-app-service-with-microsoft/4466728)
+
+## [Java](#tab/java)
+- [Tutorial: Build an agentic web app in Azure App Service with Microsoft Semantic Kernel (Spring Boot)](tutorial-ai-agent-web-app-semantic-kernel-java.md)
+
+## [Node.js](#tab/nodejs)
+- [Tutorial: Build an agentic web app in Azure App Service with LangGraph or Foundry Agent Service (Node.js)](tutorial-ai-agent-web-app-langgraph-foundry-node.md)
+
+## [Python](#tab/python)
+- [Tutorial: Build an agentic web app in Azure App Service with LangGraph or Foundry Agent Service (Python)](tutorial-ai-agent-web-app-langgraph-foundry-python.md)
+-----
+
+## Related content
+
+- [Integrate AI into your Azure App Service applications](overview-ai-integration.md)
+- [Semantic Kernel documentation](/semantic-kernel/)

articles/app-service/scenario-ai-authentication.md

@@ -0,0 +1,27 @@
+---
+title: Secure AI applications in Azure App Service
+description: Secure your AI-powered applications with Microsoft Entra authentication and authorization. Protect your OpenAPI tools and MCP servers in Azure App Service so only authorized users and agents can access them.
+author: cephalin
+ms.author: cephalin
+ms.service: azure-app-service
+ms.topic: how-to
+ms.date: 01/29/2026
+ms.custom:
+  - build-2025
+ms.collection: ce-skilling-ai-copilot
+ms.update-cycle: 180-days
+---
+
+# Authenticate tool calls to App Service
+
+Secure your AI-powered applications with Microsoft Entra authentication and authorization. These guides show you how to protect your OpenAPI tools and MCP servers in Azure App Service so only authorized users and agents can access them.
+
+## Authentication guides
+
+- [Authenticate Microsoft Foundry tool calls](configure-authentication-ai-foundry-openapi-tool.md) - Secure your App Service app when used as an OpenAPI tool in Foundry Agent Service with Microsoft Entra authentication
+- [Secure a Model Context Protocol server in Azure App Service](configure-authentication-mcp.md) - Overview of authentication methods for MCP servers
+- [Secure Model Context Protocol calls to Azure App Service from Visual Studio Code with Microsoft Entra authentication](configure-authentication-mcp-server-vscode.md) - Step-by-step guide to secure your MCP server for GitHub Copilot Chat in VS Code
+
+## Related content
+
+- [Integrate AI into your Azure App Service applications](overview-ai-integration.md)