Tutorial: Build an agentic web app in Azure App Service with Microsoft Agent Framework or Foundry Agent Service (.NET)

This tutorial demonstrates how to add agentic capability to an existing data-driven ASP.NET Core CRUD application. It does this using two different approaches: Microsoft Agent Framework and Foundry Agent Service.

If your web application already has useful features, like shopping, hotel booking, or data management, it's relatively straightforward to add agent functionality to your web application by wrapping those functionalities as tools (for Microsoft Agent Framework) or as an OpenAPI endpoint (for Foundry Agent Service). In this tutorial, you start with a simple to-do list app. By the end, you'll be able to create, update, and manage tasks with an agent in an App Service app.

Microsoft Agent Framework

Foundry Agent Service

Both Microsoft Agent Framework and Foundry Agent Service enable you to build agentic web applications with AI-driven capabilities. The following table shows some of the considerations and trade-offs:

Consideration	Microsoft Agent Framework	Foundry Agent Service
Performance	Fast (runs locally)	Slower (managed, remote service)
Development	Full code, maximum control	Low code, rapid integration
Testing	Manual/unit tests in code	Built-in playground for quick testing
Scalability	App-managed	Azure-managed, autoscaled
Security guardrails	Custom implementation required	Built-in content safety and moderation
Identity	Custom implementation required	Built-in agent ID and authentication
Enterprise	Custom integration required	Built-in Microsoft 365/Teams deployment and Microsoft 365 integrated tool calls.

In this tutorial, you learn how to:

• Convert existing app functionality into tools for Microsoft Agent Framework.
• Add the tools to a Microsoft Agent Framework agent and use it in a web app.
• Convert existing app functionality into an OpenAPI endpoint for Foundry Agent Service.
• Call a Foundry agent in a web app.
• Assign the required permissions for managed identity connectivity.

Prerequisites

• An Azure account with an active subscription - Create an account for free.
• GitHub account to use GitHub Codespaces - Learn more about GitHub Codespaces.

Open the sample with Codespaces

The easiest way to get started is by using GitHub Codespaces, which provides a complete development environment with all required tools preinstalled.

1. Navigate to the GitHub repository at https://github.com/Azure-Samples/app-service-agentic-semantic-kernel-ai-foundry-agent.

2. Select the Code button, select the Codespaces tab, and select Create codespace on main.

3. Wait a few moments for your Codespace to initialize. When ready, you'll see a fully configured development environment in your browser.

4. Run the application locally:

   dotnet run
   

5. When you see Your application running on port 5280 is available, select Open in Browser and add a few tasks.

Review the agent code

Both approaches use the same implementation pattern, where the agent is initialized as a service (in Program.cs) in a provider and injected into the respective Blazor component.

Microsoft Agent Framework

The AgentFrameworkProvider is initialized in Services/AgentFrameworkProvider.cs. The initialization code does the following:

• Creates an IChatClient from Azure OpenAI using the AzureOpenAIClient.
• Gets the TaskCrudTool instance that encapsulates the functionality of the CRUD application (in Tools/TaskCrudTool.cs). The Description attributes on the tool methods help the agent determine how to call them.
• Creates an AI agent using CreateAIAgent() with instructions and tools registered via AIFunctionFactory.Create().
• Creates a thread for the agent to persist conversation across navigation.

// Create IChatClient
IChatClient chatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
    .GetChatClient(deployment)
    .AsIChatClient();

// Get TaskCrudTool instance from service provider
var taskCrudTool = sp.GetRequiredService<TaskCrudTool>();

// Create agent with tools
var agent = chatClient.CreateAIAgent(
    instructions: @"You are an agent that manages tasks using CRUD operations. 
        Use the provided functions to create, read, update, and delete tasks. 
        Always call the appropriate function for any task management request.
        Don't try to handle any requests that are not related to task management.
        When handling requests, if you're missing any information, don't make it up but prompt the user for it instead.",
    tools:
    [
        AIFunctionFactory.Create(taskCrudTool.CreateTaskAsync),
        AIFunctionFactory.Create(taskCrudTool.ReadTasksAsync),
        AIFunctionFactory.Create(taskCrudTool.UpdateTaskAsync),
        AIFunctionFactory.Create(taskCrudTool.DeleteTaskAsync)
    ]);

// Create thread for this scoped instance (persists across navigation)
var thread = agent.GetNewThread();

return (agent, thread);

Each time the user sends a message, the Blazor component (in Components/Pages/AgentFrameworkAgent.razor) calls Agent.RunAsync() with the user input and the agent thread. The agent thread keeps track of the chat history.

var response = await this.Agent.RunAsync(sentInput, this.agentThread);

Foundry Agent Service

The FoundryAgentProvider provider is initialized in Services/FoundryAgentProvider.cs. The initialization code does the following:

• Creates an AIProjectClient using the Foundry project endpoint.
• Gets an existing agent from Microsoft Foundry by name.
• Creates a conversation for the browser session.
• Gets a ProjectResponsesClient for the agent and conversation.

// Create project client
var projectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());

// Get an existing agent from Microsoft Foundry
var agent = projectClient.Agents.GetAgent(agentName);

// Get conversations client for retrieving history
var conversationsClient = projectClient.OpenAI.Conversations;

// Create conversation for this browser session
var conversation = conversationsClient.CreateProjectConversation().Value;

// Get response client for this agent and conversation
var responseClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(agentName, conversation.Id);

return (responseClient, conversation, conversationsClient);

This initialization code doesn't define any functionality for the agent, because you would typically build the agent in the Foundry portal. As part of the example scenario, it also follows the OpenAPI pattern shown in Add an App Service app as a tool in Foundry Agent Service (.NET), and makes its CRUD functionality available as an OpenAPI endpoint. This lets you add it to the agent later as a callable tool.

The OpenAPI code is defined in Program.cs. For example, the "get tasks" API defines the operation ID with WithName(), as required by the OpenAPI spec tool in Microsoft Foundry, and WithDescription() helps the agent determine how to call the API:

app.MapOpenApi();

app.MapGet("/api/tasks", async (TaskService taskService) =>
{
    return Results.Ok(await taskService.GetAllTasksAsync());
})
.WithDescription("Gets all tasks.")
.WithName("GetAllTasks");

Each time the user sends a message, the Blazor component (in Components/Pages/FoundryAgent.razor) calls ResponseClient.CreateResponseAsync() with the user input. The response client uses the conversation ID to keep track of the chat history.

#pragma warning disable OPENAI001
var response = await FoundryProvider.ResponseClient.CreateResponseAsync(sentInput);
#pragma warning restore OPENAI001

Deploy the sample application

The sample repository contains an Azure Developer CLI (AZD) template, which creates an App Service app with managed identity and deploys your sample application.

1. In the terminal, log into Azure using Azure Developer CLI:

   azd auth login
   

   Follow the instructions to complete the authentication process.

2. Deploy the Azure App Service app with the AZD template:

   azd up
   

3. When prompted, give the following answers:

   Question	Answer
   Enter a new environment name:	Type a unique name.
   Select an Azure Subscription to use:	Select the subscription.
   Pick a resource group to use:	Select Create a new resource group.
   Select a location to create the resource group in:	Select Sweden Central.
   Enter a name for the new resource group:	Type Enter.

4. In the AZD output, find the URL of your app and navigate to it in the browser. The URL looks like this in the AZD output:

    Deploying services (azd deploy)
   
      (✓) Done: Deploying service web
      - Endpoint: <URL>
    

5. Select the OpenAPI schema item to open the autogenerated OpenAPI schema at the default /openapi/v1.json path. You need this schema later.

6. After successful deployment, you'll see a URL for your deployed application.

   You now have an App Service app with a system-assigned managed identity.

Create and configure the Microsoft Foundry resource

Microsoft Agent Framework

1. In the Foundry portal, make sure the top New Foundry radio button is set to active and create a project.

2. Deploy a model of your choice (see Microsoft Foundry Quickstart: Create resources).

3. From top of the model playground, copy the model name.

4. The easiest way to get the Azure OpenAI endpoint is still from the classic portal. Select the New Foundry radio button, then Azure OpenAI, and then copy the URL in Azure OpenAI endpoint for later.

   

Foundry Agent Service

1. In the Foundry portal, make sure the top New Foundry radio button is set to active and create a project.

2. In the home page, copy the Project endpoint for later.

3. Select Start building > Create agent and follow the prompt.

4. In the new agent's playground, create an OpenAPI tool to call your web app by selecting Tools > Add > Custom > OpenAPI tool > Create. In the Setup pane, add an action with the OpenAPI spec tool. Use the OpenAPI schema that you get from the deployed web app and anonymous authentication. For detailed steps, see How to use the OpenAPI spec tool.

   Your application code is already configured to include the server's url and operationId, which are needed by the agent. For more information, see Connect to OpenAPI Specification.

5. Be sure to select Save.

6. Select Try in playground and test your Foundry agent with prompts like "Show me all the tasks" and "Please add a task."

   If you get a valid response, the agent is making tool calls to the OpenAPI endpoint on your deployed web app.

Assign required permissions

Microsoft Agent Framework

1. From the top menu of the new Foundry portal, select Operate, then select Admin. In the row for your Foundry project, you should see two links. The one in the Name column is the Foundry project resource, and the one in the Parent resource column is the Foundry resource.

   

2. Select the Foundry resource in the Parent resource and then select Manage this resource in the Azure portal. From the Azure portal, you can assign role-based access for the resource to the deployed web app.

3. Add the following role for the App Service app's managed identity:

   Target resource	Required role	Needed for
   Foundry	Cognitive Services OpenAI User	The chat completion service in Microsoft Agent Framework.

   For instructions, see Assign Azure roles using the Azure portal.

Foundry Agent Service

1. From the top menu of the new Foundry portal, select Operate, then select Admin. In the row for your Foundry project, you should see two links. The one in the Name column is the Foundry project resource, and the one in the Parent resource column is the Foundry resource.

   

2. Select the Foundry project resource in the Name column and then select Manage this resource in the Azure portal. From the Azure portal, you can assign role-based access for the resource to the deployed web app.

3. Add the following role for the App Service app's managed identity:

   Target resource	Required role	Needed for
   Foundry Project	Azure AI User	Reading and calling the Foundry agent.

   For instructions, see Assign Azure roles using the Azure portal.

Configure connection variables in your sample application

1. Open appsettings.json. Using the values you copied earlier from the Foundry portal, configure the following variables:

   Microsoft Agent Framework

   Variable	Description
   AzureOpenAIEndpoint	Azure OpenAI endpoint (copied from the classic Foundry portal).
   ModelDeployment	Model name in the deployment (copied from the model playground in the new Foundry portal).

   Note

   To keep the tutorial simple, you'll use these variables in appsettings.json instead of overwriting them with app settings in App Service.

   Foundry Agent Service

   Variable	Description
   FoundryProjectEndpoint	Microsoft Foundry project endpoint from the new Foundry portal.
   FoundryAgentName	Agent name (from the agent playground in the Foundry portal).

   Note

   To keep the tutorial simple, you'll use these variables in appsettings.json instead of overwriting them with app settings in App Service.

2. Sign in to Azure with the Azure CLI:

   az login
   

   This allows the Azure Identity client library in the sample code to receive an authentication token for the logged in user. Remember that you added the required role for this user earlier.

3. Run the application locally:

   dotnet run
   

4. When you see Your application running on port 5280 is available, select Open in Browser.

5. Select the Microsoft Agent Framework Agent link and the Foundry Agent Service link to try out the chat interface. If you get a response, your application is connecting successfully to the Microsoft Foundry resource.

6. Back in the GitHub codespace, deploy your app changes.

   azd up
   

7. Navigate to the deployed application again and test the chat agents.

Microsoft Agent Framework

Foundry Agent Service

Clean up resources

When you're done with the application, you can delete the App Service resources to avoid incurring further costs:

azd down --purge

Since the AZD template doesn't include the Microsoft Foundry resources, you need to delete them manually if you want.

More resources

• Integrate AI into your Azure App Service applications
• What is Foundry Agent Service?
• Microsoft Agent Framework documentation