chore: import upstream snapshot with attribution

dotnet/samples/02-agents/AgentProviders/foundry/Agent_Step23_LocalMCP/Agent_Step23_LocalMCP.csproj

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+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="ModelContextProtocol" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/AgentProviders/foundry/Agent_Step23_LocalMCP/Program.cs

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+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to wrap MCP tools with a DelegatingAIFunction to add custom behavior (e.g., logging).
+// Compare with Step09 which shows basic MCP tool usage without wrapping.
+// The LoggingMcpTool pattern is useful for diagnostics, metering, or adding approval logic around tool calls.
+
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using ModelContextProtocol.Client;
+using SampleApp;
+
+const string AgentInstructions = "You are a helpful assistant that can help with Microsoft documentation questions. Use the Microsoft Learn MCP tool to search for documentation.";
+const string AgentName = "DocsAgent-RAPI";
+
+// Connect to the MCP server locally via HTTP (Streamable HTTP transport).
+Console.WriteLine("Connecting to MCP server at https://learn.microsoft.com/api/mcp ...");
+
+await using McpClient mcpClient = await McpClient.CreateAsync(new HttpClientTransport(new()
+{
+    Endpoint = new Uri("https://learn.microsoft.com/api/mcp"),
+    Name = "Microsoft Learn MCP",
+}));
+
+// Retrieve the list of tools available on the MCP server (resolved locally).
+IList<McpClientTool> mcpTools = await mcpClient.ListToolsAsync();
+Console.WriteLine($"MCP tools available: {string.Join(", ", mcpTools.Select(t => t.Name))}");
+
+// Wrap each MCP tool with a DelegatingAIFunction to log local invocations.
+List<AITool> wrappedTools = mcpTools.Select(tool => (AITool)new LoggingMcpTool(tool)).ToList();
+
+string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
+string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+// Create a AIAgent with the locally-resolved MCP tools.
+AIAgent agent = aiProjectClient.AsAIAgent(deploymentName,
+    instructions: AgentInstructions,
+    name: AgentName,
+    tools: wrappedTools);
+
+Console.WriteLine($"Agent '{agent.Name}' created successfully.");
+
+// First query
+const string Prompt1 = "How does one create an Azure storage account using az cli?";
+Console.WriteLine($"\nUser: {Prompt1}\n");
+AgentResponse response1 = await agent.RunAsync(Prompt1);
+Console.WriteLine($"Agent: {response1}");
+
+Console.WriteLine("\n=======================================\n");
+
+// Second query
+const string Prompt2 = "What is Microsoft Agent Framework?";
+Console.WriteLine($"User: {Prompt2}\n");
+AgentResponse response2 = await agent.RunAsync(Prompt2);
+Console.WriteLine($"Agent: {response2}");
+
+namespace SampleApp
+{
+    /// <summary>
+    /// Wraps an MCP tool to log when it is invoked locally,
+    /// confirming that the MCP call is happening client-side.
+    /// </summary>
+    internal sealed class LoggingMcpTool(AIFunction innerFunction) : DelegatingAIFunction(innerFunction)
+    {
+        protected override ValueTask<object?> InvokeCoreAsync(AIFunctionArguments arguments, CancellationToken cancellationToken)
+        {
+            Console.WriteLine($"  >> [LOCAL MCP] Invoking tool '{this.Name}' locally...");
+            return base.InvokeCoreAsync(arguments, cancellationToken);
+        }
+    }
+}

dotnet/samples/02-agents/AgentProviders/foundry/Agent_Step23_LocalMCP/README.md

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+# Local MCP with the Responses API
+
+This sample demonstrates how to use a local MCP (Model Context Protocol) client with a `ChatClientAgent` using the Responses API directly.
+
+## What this sample demonstrates
+
+- Connecting to an MCP server via HTTP (Streamable HTTP transport)
+- Resolving MCP tools locally and wrapping them with logging
+- Using `DelegatingAIFunction` to add custom behavior to MCP tools
+- Passing locally-resolved MCP tools to `ChatClientAgent`
+
+## Prerequisites
+
+- .NET 10 SDK or later
+- Microsoft Foundry service endpoint and deployment configured
+- An authenticated Azure identity (for example, sign in with `az login`)
+
+Set the following environment variables:
+
+```powershell
+$env:FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project"
+$env:FOUNDRY_MODEL="gpt-5.4-mini"
+```
+
+## Run the sample
+
+```powershell
+dotnet run
+```
+