Merge branch 'main' into crickman/workflows-declarative-nocodegen

2026-06-16 21:04:09 +08:00 · 2026-03-25 12:57:37 -07:00
parent 6173f05936 23921c0f6e
commit bca42febe2
556 changed files with 15650 additions and 12859 deletions
@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,226 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how the ChatClientAgent persists chat history after each individual
+// call to the AI service.
+// When an agent uses tools, FunctionInvokingChatClient may loop multiple times
+// (service call → tool execution → service call), and intermediate messages (tool calls and
+// results) are persisted after each service call. This allows you to inspect or recover them
+// even if the process is interrupted mid-loop, but may also result in chat history that is not
+// yet finalized (e.g., tool calls without results) being persisted, which may be undesirable in some cases.
+//
+// To opt into end-of-run persistence instead (atomic run semantics), set
+// PersistChatHistoryAtEndOfRun = true on ChatClientAgentOptions.
+//
+// The sample runs two multi-turn conversations: one using non-streaming (RunAsync) and one
+// using streaming (RunStreamingAsync), to demonstrate correct behavior in both modes.
+
+using System.ComponentModel;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using OpenAI.Responses;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+var store = Environment.GetEnvironmentVariable("AZURE_OPENAI_RESPONSES_STORE") ?? "false";
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AzureOpenAIClient openAIClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Define multiple tools so the model makes several tool calls in a single run.
+[Description("Get the current weather for a city.")]
+static string GetWeather([Description("The city name.")] string city) =>
+    city.ToUpperInvariant() switch
+    {
+        "SEATTLE" => "Seattle: 55°F, cloudy with light rain.",
+        "NEW YORK" => "New York: 72°F, sunny and warm.",
+        "LONDON" => "London: 48°F, overcast with fog.",
+        "DUBLIN" => "Dublin: 43°F, overcast with fog.",
+        _ => $"{city}: weather data not available."
+    };
+
+[Description("Get the current time in a city.")]
+static string GetTime([Description("The city name.")] string city) =>
+    city.ToUpperInvariant() switch
+    {
+        "SEATTLE" => "Seattle: 9:00 AM PST",
+        "NEW YORK" => "New York: 12:00 PM EST",
+        "LONDON" => "London: 5:00 PM GMT",
+        "DUBLIN" => "Dublin: 5:00 PM GMT",
+        _ => $"{city}: time data not available."
+    };
+
+// Create the agent — per-service-call persistence is the default behavior.
+// The in-memory ChatHistoryProvider is used by default when the service does not require service stored chat
+// history, so for those cases, we can inspect the chat history via session.TryGetInMemoryChatHistory().
+IChatClient chatClient = string.Equals(store, "TRUE", StringComparison.OrdinalIgnoreCase) ?
+    openAIClient.GetResponsesClient().AsIChatClient(deploymentName) :
+    openAIClient.GetResponsesClient().AsIChatClientWithStoredOutputDisabled(deploymentName);
+AIAgent agent = chatClient.AsAIAgent(
+    new ChatClientAgentOptions
+    {
+        Name = "WeatherAssistant",
+        ChatOptions = new()
+        {
+            Instructions = "You are a helpful assistant. When asked about multiple cities, call the appropriate tool for each city.",
+            Tools = [AIFunctionFactory.Create(GetWeather), AIFunctionFactory.Create(GetTime)]
+        },
+    });
+
+await RunNonStreamingAsync();
+await RunStreamingAsync();
+
+async Task RunNonStreamingAsync()
+{
+    int lastChatHistorySize = 0;
+    string lastConversationId = string.Empty;
+
+    Console.ForegroundColor = ConsoleColor.Yellow;
+    Console.WriteLine("\n=== Non-Streaming Mode ===");
+    Console.ResetColor();
+
+    AgentSession session = await agent.CreateSessionAsync();
+
+    // First turn — ask about multiple cities so the model calls tools.
+    const string Prompt = "What's the weather and time in Seattle, New York, and London?";
+    PrintUserMessage(Prompt);
+
+    var response = await agent.RunAsync(Prompt, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Second turn — follow-up to verify chat history is correct.
+    const string FollowUp1 = "And Dublin?";
+    PrintUserMessage(FollowUp1);
+
+    response = await agent.RunAsync(FollowUp1, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After second run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Third turn — follow-up to verify chat history is correct.
+    const string FollowUp2 = "Which city is the warmest?";
+    PrintUserMessage(FollowUp2);
+
+    response = await agent.RunAsync(FollowUp2, session);
+    PrintAgentResponse(response.Text);
+    PrintChatHistory(session, "After third run", ref lastChatHistorySize, ref lastConversationId);
+}
+
+async Task RunStreamingAsync()
+{
+    int lastChatHistorySize = 0;
+    string lastConversationId = string.Empty;
+
+    Console.ForegroundColor = ConsoleColor.Yellow;
+    Console.WriteLine("\n=== Streaming Mode ===");
+    Console.ResetColor();
+
+    AgentSession session = await agent.CreateSessionAsync();
+
+    // First turn — ask about multiple cities so the model calls tools.
+    const string Prompt = "What's the weather and time in Seattle, New York, and London?";
+    PrintUserMessage(Prompt);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(Prompt, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Second turn — follow-up to verify chat history is correct.
+    const string FollowUp1 = "And Dublin?";
+    PrintUserMessage(FollowUp1);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(FollowUp1, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During second run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After second run", ref lastChatHistorySize, ref lastConversationId);
+
+    // Third turn — follow-up to verify chat history is correct.
+    const string FollowUp2 = "Which city is the warmest?";
+    PrintUserMessage(FollowUp2);
+
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+
+    await foreach (var update in agent.RunStreamingAsync(FollowUp2, session))
+    {
+        Console.Write(update);
+
+        // During streaming we should be able to see updates to the chat history
+        // before the full run completes, as each service call is made and persisted.
+        PrintChatHistory(session, "During third run", ref lastChatHistorySize, ref lastConversationId);
+    }
+
+    Console.WriteLine();
+    PrintChatHistory(session, "After third run", ref lastChatHistorySize, ref lastConversationId);
+}
+
+void PrintUserMessage(string message)
+{
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[User] ");
+    Console.ResetColor();
+    Console.WriteLine(message);
+}
+
+void PrintAgentResponse(string? text)
+{
+    Console.ForegroundColor = ConsoleColor.Cyan;
+    Console.Write("\n[Agent] ");
+    Console.ResetColor();
+    Console.WriteLine(text);
+}
+
+// Helper to print the current chat history from the session.
+void PrintChatHistory(AgentSession session, string label, ref int lastChatHistorySize, ref string lastConversationId)
+{
+    if (session.TryGetInMemoryChatHistory(out var history) && history.Count != lastChatHistorySize)
+    {
+        Console.ForegroundColor = ConsoleColor.DarkGray;
+        Console.WriteLine($"\n  [{label} — Chat history: {history.Count} message(s)]");
+        foreach (var msg in history)
+        {
+            var preview = msg.Text?.Length > 80 ? msg.Text[..80] + "…" : msg.Text;
+            var contentTypes = string.Join(", ", msg.Contents.Select(c => c.GetType().Name));
+            Console.WriteLine($"    {msg.Role,-12} | {(string.IsNullOrWhiteSpace(preview) ? $"[{contentTypes}]" : preview)}");
+        }
+
+        Console.ResetColor();
+
+        lastChatHistorySize = history.Count;
+    }
+
+    if (session is ChatClientAgentSession ccaSession && ccaSession.ConversationId is not null && ccaSession.ConversationId != lastConversationId)
+    {
+        Console.ForegroundColor = ConsoleColor.DarkGray;
+        Console.WriteLine($"  [{label} — Conversation ID: {ccaSession.ConversationId}]");
+        Console.ResetColor();
+        lastConversationId = ccaSession.ConversationId;
+    }
+}
@@ -0,0 +1,63 @@
+# In-Function-Loop Checkpointing
+
+This sample demonstrates how `ChatClientAgent` persists chat history after each individual call to the AI service by default. This per-service-call persistence ensures intermediate progress is saved during the function invocation loop.
+
+## What This Sample Shows
+
+When an agent uses tools, the `FunctionInvokingChatClient` loops multiple times (service call → tool execution → service call → …). By default, chat history is persisted after each service call via the `ChatHistoryPersistingChatClient` decorator:
+
+- A `ChatHistoryPersistingChatClient` decorator is automatically inserted into the chat client pipeline
+- After each service call, the decorator notifies the `ChatHistoryProvider` (and any `AIContextProvider` instances) with the new messages
+- Only **new** messages are sent to providers on each notification — messages that were already persisted in an earlier call within the same run are deduplicated automatically
+
+To opt into end-of-run persistence instead (atomic run semantics), set `PersistChatHistoryAtEndOfRun = true` on `ChatClientAgentOptions`. In that mode, the decorator marks messages with metadata rather than persisting them immediately, and `ChatClientAgent` persists only the marked messages at the end of the run.
+
+Per-service-call persistence is useful for:
+- **Crash recovery** — if the process is interrupted mid-loop, the intermediate tool calls and results are already persisted
+- **Observability** — you can inspect the chat history while the agent is still running (e.g., during streaming)
+- **Long-running tool loops** — agents with many sequential tool calls benefit from incremental persistence
+
+## How It Works
+
+The sample asks the agent about the weather and time in three cities. The model calls the `GetWeather` and `GetTime` tools for each city, resulting in multiple service calls within a single `RunStreamingAsync` invocation. After the run completes, the sample prints the full chat history to show all the intermediate messages that were persisted along the way.
+
+### Pipeline Architecture
+
+```
+ChatClientAgent
+  └─ FunctionInvokingChatClient    (handles tool call loop)
+       └─ ChatHistoryPersistingChatClient  (persists after each service call)
+            └─ Leaf IChatClient            (Azure OpenAI)
+```
+
+## Prerequisites
+
+- .NET 10 SDK or later
+- Azure OpenAI service endpoint and model deployment
+- Azure CLI installed and authenticated
+
+**Note**: This sample uses `DefaultAzureCredential`. Sign in with `az login` before running. For production, prefer a specific credential such as `ManagedIdentityCredential`. For more information, see the [Azure CLI authentication documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Environment Variables
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"  # Required
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"                       # Optional, defaults to gpt-4o-mini
+```
+
+## Running the Sample
+
+```powershell
+cd dotnet/samples/02-agents/Agents/Agent_Step19_InFunctionLoopCheckpointing
+dotnet run
+```
+
+## Expected Behavior
+
+The sample runs two conversation turns:
+
+1. **First turn** — asks about weather and time in three cities. The model calls `GetWeather` and `GetTime` tools (potentially in parallel or sequentially), then provides a summary. The chat history dump after the run shows all the intermediate tool call and result messages.
+
+2. **Second turn** — asks a follow-up question ("Which city is the warmest?") that uses the persisted conversation context. The chat history dump shows the full accumulated conversation.
+
+The chat history printout uses `session.TryGetInMemoryChatHistory()` to inspect the in-memory storage.
@@ -45,6 +45,7 @@ Before you begin, ensure you have the following prerequisites:
 |[Declarative agent](./Agent_Step16_Declarative/)|This sample demonstrates how to declaratively define an agent.|
 |[Providing additional AI Context to an agent using multiple AIContextProviders](./Agent_Step17_AdditionalAIContext/)|This sample demonstrates how to inject additional AI context into a ChatClientAgent using multiple custom AIContextProvider components that are attached to the agent.|
 |[Using compaction pipeline with an agent](./Agent_Step18_CompactionPipeline/)|This sample demonstrates how to use a compaction pipeline to efficiently limit the size of the conversation history for an agent.|
+|[In-function-loop checkpointing](./Agent_Step19_InFunctionLoopCheckpointing/)|This sample demonstrates how to persist chat history after each service call during a tool-calling loop, enabling crash recovery and mid-run observability.|

 ## Running the samples from the console

@@ -9,7 +9,7 @@ using Microsoft.Extensions.AI;
 namespace WorkflowAsAnAgentSample;

 /// <summary>
-/// This sample introduces the concepts workflows as agents, where a workflow can be
+/// This sample introduces the concept of workflows as agents, where a workflow can be
 /// treated as an <see cref="AIAgent"/>. This allows you to interact with a workflow
 /// as if it were a single agent.
 ///
@@ -18,6 +18,14 @@ namespace WorkflowAsAnAgentSample;
 ///
 /// You will interact with the workflow in an interactive loop, sending messages and receiving
 /// streaming responses from the workflow as if it were an agent who responds in both languages.
+///
+/// This sample also demonstrates <see cref="IResettableExecutor"/>, which is required
+/// for stateful executors that are shared across multiple workflow runs. Each iteration
+/// of the interactive loop triggers a new workflow run against the same workflow instance.
+/// Between runs, the framework automatically calls <see cref="IResettableExecutor.ResetAsync"/>
+/// on shared executors so that accumulated state (e.g., collected messages) is cleared
+/// before the next run begins. See <c>WorkflowFactory.ConcurrentAggregationExecutor</c>
+/// for the implementation.
 /// </summary>
 /// <remarks>
 /// Pre-requisites:
@@ -39,7 +47,10 @@ public static class Program
        var agent = workflow.AsAIAgent("workflow-agent", "Workflow Agent");
        var session = await agent.CreateSessionAsync();

-        // Start an interactive loop to interact with the workflow as if it were an agent
+        // Start an interactive loop to interact with the workflow as if it were an agent.
+        // Each iteration runs the workflow again on the same workflow instance. Between runs,
+        // the framework calls IResettableExecutor.ResetAsync() on shared stateful executors
+        // (like ConcurrentAggregationExecutor) to clear accumulated state from the previous run.
        while (true)
        {
            Console.WriteLine();
@@ -10,6 +10,14 @@ internal static class WorkflowFactory
 {
    /// <summary>
    /// Creates a workflow that uses two language agents to process input concurrently.
+    ///
+    /// In this workflow, the <c>Start</c> <see cref="ChatForwardingExecutor"/> and the
+    /// <see cref="ConcurrentAggregationExecutor"/> are provided as shared instances, meaning
+    /// the same executor objects are reused across multiple workflow runs. The language agents
+    /// (French and English) are created via a factory and instantiated per workflow run.
+    /// Stateful shared executors must implement <see cref="IResettableExecutor"/> so the
+    /// framework can clear their state between runs. Framework-provided executors like
+    /// <see cref="ChatForwardingExecutor"/> already implement this interface.
    /// </summary>
    /// <param name="chatClient">The chat client to use for the agents</param>
    /// <returns>A workflow that processes input using two language agents</returns>
@@ -40,6 +48,16 @@ internal static class WorkflowFactory

    /// <summary>
    /// Executor that aggregates the results from the concurrent agents.
+    ///
+    /// This executor is stateful — it accumulates messages in <see cref="_messages"/>
+    /// as they arrive from each agent. Because it is provided as a shared instance
+    /// (not via a factory), the same object is reused across workflow runs. Implementing
+    /// <see cref="IResettableExecutor"/> allows the framework to call <see cref="ResetAsync"/>
+    /// between runs, clearing accumulated state so each run starts fresh.
+    ///
+    /// Without <see cref="IResettableExecutor"/>, attempting to reuse a workflow containing
+    /// shared executor instances that do not implement this interface would throw an
+    /// <see cref="InvalidOperationException"/>.
    /// </summary>
    [YieldsOutput(typeof(string))]
    private sealed class ConcurrentAggregationExecutor() :
@@ -65,7 +83,11 @@ internal static class WorkflowFactory
            }
        }

-        /// <inheritdoc/>
+        /// <summary>
+        /// Resets the executor state between workflow runs by clearing accumulated messages.
+        /// The framework calls this automatically when a workflow run completes, before the
+        /// workflow can be used for another run.
+        /// </summary>
        public ValueTask ResetAsync()
        {
            this._messages.Clear();
@@ -0,0 +1,35 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>WorkflowMcpTool</AssemblyName>
+    <RootNamespace>WorkflowMcpTool</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,59 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace WorkflowMcpTool;
+
+internal sealed class TranslateText() : Executor<string, TranslationResult>("TranslateText")
+{
+    public override ValueTask<TranslationResult> HandleAsync(
+        string message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine($"[Activity] TranslateText: '{message}'");
+        return ValueTask.FromResult(new TranslationResult(message, message.ToUpperInvariant()));
+    }
+}
+
+internal sealed class FormatOutput() : Executor<TranslationResult, string>("FormatOutput")
+{
+    public override ValueTask<string> HandleAsync(
+        TranslationResult message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine("[Activity] FormatOutput: Formatting result");
+        return ValueTask.FromResult($"Original: {message.Original} => Translated: {message.Translated}");
+    }
+}
+
+internal sealed class LookupOrder() : Executor<string, OrderInfo>("LookupOrder")
+{
+    public override ValueTask<OrderInfo> HandleAsync(
+        string message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine($"[Activity] LookupOrder: '{message}'");
+        return ValueTask.FromResult(new OrderInfo(message, "Alice Johnson", "Wireless Headphones", Quantity: 2, UnitPrice: 49.99m));
+    }
+}
+
+internal sealed class EnrichOrder() : Executor<OrderInfo, OrderSummary>("EnrichOrder")
+{
+    public override ValueTask<OrderSummary> HandleAsync(
+        OrderInfo message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine($"[Activity] EnrichOrder: '{message.OrderId}'");
+        return ValueTask.FromResult(new OrderSummary(message, TotalPrice: message.Quantity * message.UnitPrice, Status: "Confirmed"));
+    }
+}
+
+internal sealed record TranslationResult(string Original, string Translated);
+
+internal sealed record OrderInfo(string OrderId, string CustomerName, string Product, int Quantity, decimal UnitPrice);
+
+internal sealed record OrderSummary(OrderInfo Order, decimal TotalPrice, string Status);
@@ -0,0 +1,44 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to expose a durable workflow as an MCP (Model Context Protocol) tool.
+// When using AddWorkflow with exposeMcpToolTrigger: true, the Functions host will automatically
+// generate a remote MCP endpoint for the app at /runtime/webhooks/mcp with a workflow-specific
+// tool name. MCP-compatible clients can then invoke the workflow as a tool.
+
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.Hosting;
+using WorkflowMcpTool;
+
+// Define executors
+TranslateText translateText = new();
+FormatOutput formatOutput = new();
+LookupOrder lookupOrder = new();
+EnrichOrder enrichOrder = new();
+
+// Build a simple workflow: TranslateText -> FormatOutput
+Workflow translateWorkflow = new WorkflowBuilder(translateText)
+    .WithName("Translate")
+    .WithDescription("Translate text to uppercase and format the result")
+    .AddEdge(translateText, formatOutput)
+    .Build();
+
+// Build a workflow that returns a POCO: LookupOrder -> EnrichOrder
+Workflow orderLookupWorkflow = new WorkflowBuilder(lookupOrder)
+    .WithName("OrderLookup")
+    .WithDescription("Look up an order by ID and return enriched order details")
+    .AddEdge(lookupOrder, enrichOrder)
+    .Build();
+
+using IHost app = FunctionsApplication
+    .CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableWorkflows(workflows =>
+    {
+        // Expose both workflows as MCP tool triggers.
+        workflows.AddWorkflow(translateWorkflow, exposeStatusEndpoint: false, exposeMcpToolTrigger: true);
+        workflows.AddWorkflow(orderLookupWorkflow, exposeStatusEndpoint: false, exposeMcpToolTrigger: true);
+    })
+    .Build();
+app.Run();
@@ -0,0 +1,81 @@
+# Workflow as MCP Tool Sample
+
+This sample demonstrates how to expose durable workflows as [MCP (Model Context Protocol)](https://modelcontextprotocol.io/) tools, enabling MCP-compatible clients to invoke workflows directly.
+
+## Key Concepts Demonstrated
+
+- **Workflow as MCP Tool**: Expose workflows as callable MCP tools using `exposeMcpToolTrigger: true`
+- **MCP Server Hosting**: The Azure Functions host automatically generates a remote MCP endpoint at `/runtime/webhooks/mcp`
+- **String and POCO Results**: Shows workflows returning both plain strings and structured JSON objects
+
+## Sample Architecture
+
+The sample creates two workflows exposed as MCP tools:
+
+### Translate Workflow (returns a string)
+
+| Executor | Input | Output | Description |
+|----------|-------|--------|-------------|
+| **TranslateText** | `string` | `TranslationResult` | Converts input text to uppercase |
+| **FormatOutput** | `TranslationResult` | `string` | Formats the result into a readable string |
+
+### OrderLookup Workflow (returns a POCO)
+
+| Executor | Input | Output | Description |
+|----------|-------|--------|-------------|
+| **LookupOrder** | `string` | `OrderInfo` | Looks up an order by ID |
+| **EnrichOrder** | `OrderInfo` | `OrderSummary` | Adds computed fields (total price, status) |
+
+## Environment Setup
+
+See the [README.md](../../README.md) file in the parent directory for complete setup instructions, including:
+
+- Prerequisites installation
+- Durable Task Scheduler setup
+- Storage emulator configuration
+
+For this sample, you'll also need [Node.js](https://nodejs.org/en/download) to use the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector).
+
+## Running the Sample
+
+1. **Start the Function App**:
+
+   ```bash
+   cd dotnet/samples/04-hosting/DurableWorkflows/AzureFunctions/04_WorkflowMcpTool
+   func start
+   ```
+
+2. **Note the MCP Server Endpoint**: When the app starts, you'll see the MCP server endpoint in the terminal output:
+
+   ```text
+   MCP server endpoint:  http://localhost:7071/runtime/webhooks/mcp
+   ```
+
+## Invoking Workflows via MCP Inspector
+
+1. Install and run the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector):
+
+   ```bash
+   npx @modelcontextprotocol/inspector
+   ```
+
+2. Connect to the MCP server endpoint:
+   - For **Transport Type**, select **"Streamable HTTP"**
+   - For **URL**, enter `http://localhost:7071/runtime/webhooks/mcp`
+   - Click the **Connect** button
+
+3. Click the **List Tools** button. You should see two tools: `Translate` and `OrderLookup`.
+
+4. Test the **Translate** tool (returns a plain string):
+   - Select the `Translate` tool
+   - Set `hello world` as the `input` parameter
+   - Click **Run Tool**
+   - Expected result: `Original: hello world => Translated: HELLO WORLD`
+
+5. Test the **OrderLookup** tool (returns a JSON object):
+   - Select the `OrderLookup` tool
+   - Set `ORD-2025-42` as the `input` parameter
+   - Click **Run Tool**
+   - Expected result: A JSON object containing order details such as `OrderId`, `CustomerName`, `Product`, `TotalPrice`, and `Status`
+
+You'll see the workflow executor activities logged in the terminal where you ran `func start`.
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,8 @@
+{
+  "IsEncrypted": false,
+  "Values": {
+    "FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
+    "AzureWebJobsStorage": "UseDevelopmentStorage=true",
+    "DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None"
+  }
+}
@@ -0,0 +1,42 @@
+<Project Sdk="Microsoft.NET.Sdk">
+  <PropertyGroup>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+    <AzureFunctionsVersion>v4</AzureFunctionsVersion>
+    <OutputType>Exe</OutputType>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <!-- The Functions build tools don't like namespaces that start with a number -->
+    <AssemblyName>WorkflowAndAgents</AssemblyName>
+    <RootNamespace>WorkflowAndAgents</RootNamespace>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <FrameworkReference Include="Microsoft.AspNetCore.App" />
+  </ItemGroup>
+
+  <!-- Azure Functions packages -->
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Azure.Functions.Worker" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.DurableTask.AzureManaged" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Extensions.Http.AspNetCore" />
+    <PackageReference Include="Microsoft.Azure.Functions.Worker.Sdk" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <!-- Local projects that should be switched to package references when using the sample outside of this MAF repo -->
+  <!--
+  <ItemGroup>
+    <PackageReference Include="Microsoft.Agents.AI.Hosting.AzureFunctions" />
+    <PackageReference Include="Microsoft.Agents.AI.OpenAI" />
+  </ItemGroup>
+  -->
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Hosting.AzureFunctions\Microsoft.Agents.AI.Hosting.AzureFunctions.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
+  </ItemGroup>
+</Project>
@@ -0,0 +1,31 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Agents.AI.Workflows;
+
+namespace WorkflowAndAgents;
+
+internal sealed class TranslateText() : Executor<string, TranslationResult>("TranslateText")
+{
+    public override ValueTask<TranslationResult> HandleAsync(
+        string message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine($"[Activity] TranslateText: '{message}'");
+        return ValueTask.FromResult(new TranslationResult(message, message.ToUpperInvariant()));
+    }
+}
+
+internal sealed class FormatOutput() : Executor<TranslationResult, string>("FormatOutput")
+{
+    public override ValueTask<string> HandleAsync(
+        TranslationResult message,
+        IWorkflowContext context,
+        CancellationToken cancellationToken = default)
+    {
+        Console.WriteLine("[Activity] FormatOutput: Formatting result");
+        return ValueTask.FromResult($"Original: {message.Original} => Translated: {message.Translated}");
+    }
+}
+
+internal sealed record TranslationResult(string Original, string Translated);
@@ -0,0 +1,64 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates using ConfigureDurableOptions to register BOTH agents AND workflows
+// in a single Azure Functions app. It uses a workflow to translate text and a standalone AI agent
+// accessible via HTTP and MCP tool triggers.
+
+#pragma warning disable IDE0002 // Simplify Member Access
+
+using Azure;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Hosting.AzureFunctions;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Azure.Functions.Worker.Builder;
+using Microsoft.Extensions.Hosting;
+using OpenAI.Chat;
+using WorkflowAndAgents;
+
+// Get the Azure OpenAI endpoint and deployment name from environment variables.
+string endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
+    ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME")
+    ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");
+
+// Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
+string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_API_KEY");
+AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
+    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());
+
+ChatClient chatClient = client.GetChatClient(deploymentName);
+
+// Define a standalone AI agent
+AIAgent assistant = chatClient.AsAIAgent(
+    "You are a helpful assistant. Answer questions clearly and concisely.",
+    "Assistant",
+    description: "A general-purpose helpful assistant.");
+
+// Define workflow executors
+TranslateText translateText = new();
+FormatOutput formatOutput = new();
+
+// Build a workflow: TranslateText -> FormatOutput
+Workflow translateWorkflow = new WorkflowBuilder(translateText)
+    .WithName("Translate")
+    .WithDescription("Translate text to uppercase and format the result")
+    .AddEdge(translateText, formatOutput)
+    .Build();
+
+// Use ConfigureDurableOptions to register both agents and workflows together
+using IHost app = FunctionsApplication
+    .CreateBuilder(args)
+    .ConfigureFunctionsWebApplication()
+    .ConfigureDurableOptions(options =>
+    {
+        // Register the standalone agent with HTTP and MCP tool triggers
+        options.Agents.AddAIAgent(assistant, enableHttpTrigger: true, enableMcpToolTrigger: true);
+
+        // Register the workflow with an HTTP endpoint and MCP tool trigger
+        options.Workflows.AddWorkflow(translateWorkflow, exposeStatusEndpoint: false, exposeMcpToolTrigger: true);
+    })
+    .Build();
+app.Run();
@@ -0,0 +1,76 @@
+# Workflow and Agents Sample
+
+This sample demonstrates how to use `ConfigureDurableOptions` to register **both** AI agents **and** workflows in a single Azure Functions app. This is the recommended approach when your application needs both standalone agents and orchestrated workflows.
+
+## Key Concepts Demonstrated
+
+- **Unified Configuration**: Use `ConfigureDurableOptions` to register agents and workflows together
+- **Standalone Agent**: An AI agent accessible via HTTP and MCP tool triggers
+- **Workflow**: A simple text translation workflow also exposed as an MCP tool
+- **Mixed Triggers**: Both agents and workflows coexist in the same Functions host
+
+## Sample Architecture
+
+### Standalone Agent
+
+| Agent | Description |
+|-------|-------------|
+| **Assistant** | A general-purpose AI assistant accessible via HTTP (`/agents/Assistant/run`) and as an MCP tool |
+
+### Translate Workflow
+
+| Executor | Input | Output | Description |
+|----------|-------|--------|-------------|
+| **TranslateText** | `string` | `TranslationResult` | Converts input text to uppercase |
+| **FormatOutput** | `TranslationResult` | `string` | Formats the result into a readable string |
+
+## Environment Setup
+
+See the [README.md](../../README.md) file in the parent directory for complete setup instructions, including:
+
+- Prerequisites installation
+- Durable Task Scheduler setup
+- Storage emulator configuration
+
+This sample also requires Azure OpenAI credentials. Set the following in `local.settings.json`:
+
+- `AZURE_OPENAI_ENDPOINT`: Your Azure OpenAI endpoint URL
+- `AZURE_OPENAI_DEPLOYMENT_NAME`: Your chat model deployment name
+- `AZURE_OPENAI_API_KEY` (optional): If not set, Azure CLI credential is used
+
+## Running the Sample
+
+1. **Start the Function App**:
+
+   ```bash
+   cd dotnet/samples/04-hosting/DurableWorkflows/AzureFunctions/05_WorkflowAndAgents
+   func start
+   ```
+
+2. **Expected Functions**: When the app starts, you should see functions for both the agent and the workflow:
+
+   - `dafx-Assistant` (entity trigger for the agent)
+   - `http-Assistant` (HTTP trigger for the agent)
+   - `mcptool-Assistant` (MCP tool trigger for the agent)
+   - `wf-Translate` (orchestration trigger for the workflow)
+   - `mcptool-wf-Translate` (MCP tool trigger for the workflow)
+
+## Invoking the Agent via HTTP
+
+```bash
+curl -X POST http://localhost:7071/agents/Assistant/run \
+  -H "Content-Type: application/json" \
+  -d '{"query": "What is the capital of France?"}'
+```
+
+## Invoking via MCP Inspector
+
+1. Install and run the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector):
+
+   ```bash
+   npx @modelcontextprotocol/inspector
+   ```
+
+2. Connect to `http://localhost:7071/runtime/webhooks/mcp` using **Streamable HTTP** transport.
+
+3. Click **List Tools** to see both the `Assistant` agent tool and the `Translate` workflow tool.
@@ -0,0 +1,20 @@
+{
+  "version": "2.0",
+  "logging": {
+    "logLevel": {
+      "Microsoft.Agents.AI.DurableTask": "Information",
+      "Microsoft.Agents.AI.Hosting.AzureFunctions": "Information",
+      "DurableTask": "Information",
+      "Microsoft.DurableTask": "Information"
+    }
+  },
+  "extensions": {
+    "durableTask": {
+      "hubName": "default",
+      "storageProvider": {
+        "type": "AzureManaged",
+        "connectionStringName": "DURABLE_TASK_SCHEDULER_CONNECTION_STRING"
+      }
+    }
+  }
+}
@@ -0,0 +1,10 @@
+{
+  "IsEncrypted": false,
+  "Values": {
+    "FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
+    "AzureWebJobsStorage": "UseDevelopmentStorage=true",
+    "DURABLE_TASK_SCHEDULER_CONNECTION_STRING": "Endpoint=http://localhost:8080;TaskHub=default;Authentication=None",
+    "AZURE_OPENAI_ENDPOINT": "<AZURE_OPENAI_ENDPOINT>",
+    "AZURE_OPENAI_DEPLOYMENT_NAME": "<AZURE_OPENAI_DEPLOYMENT_NAME>"
+  }
+}
@@ -48,3 +48,4 @@ $env:DURABLE_TASK_SCHEDULER_CONNECTION_STRING = "AccountEndpoint=http://localhos
 | [01_SequentialWorkflow](AzureFunctions/01_SequentialWorkflow/) | Sequential workflow hosted in Azure Functions |
 | [02_ConcurrentWorkflow](AzureFunctions/02_ConcurrentWorkflow/) | Concurrent workflow hosted in Azure Functions |
 | [03_WorkflowHITL](AzureFunctions/03_WorkflowHITL/) | Human-in-the-loop workflow hosted in Azure Functions |
+| [04_WorkflowMcpTool](AzureFunctions/04_WorkflowMcpTool/) | Workflow exposed as an MCP tool |