chore: import upstream snapshot with attribution

2026-07-13 13:39:25 +08:00
commit db620d33df
5151 changed files with 925932 additions and 0 deletions
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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\Microsoft.Agents.AI.csproj" />
+    <ProjectReference Include="..\..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
+  </ItemGroup>
+
+</Project>
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+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to use MCP client tools with an agent.
+// It connects to the Microsoft Learn MCP server via HTTP and uses its tools.
+
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using ModelContextProtocol.Client;
+
+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";
+
+// Connect to the Microsoft Learn MCP server 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.
+IList<McpClientTool> mcpTools = await mcpClient.ListToolsAsync();
+Console.WriteLine($"MCP tools available: {string.Join(", ", mcpTools.Select(t => t.Name))}");
+
+List<AITool> agentTools = [.. mcpTools.Cast<AITool>()];
+
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+AIAgent agent = aiProjectClient.AsAIAgent(deploymentName,
+    instructions: "You are a helpful assistant that can help with Microsoft documentation questions. Use the Microsoft Learn MCP tool to search for documentation. In the output, indicate which tool you used if any.",
+    name: "DocsAgent",
+    tools: agentTools);
+
+Console.WriteLine($"Agent '{agent.Name}' created. Asking a question...\n");
+
+const string Prompt = "How does one create an Azure storage account using az cli?";
+Console.WriteLine($"User: {Prompt}\n");
+Console.WriteLine($"Agent: {await agent.RunAsync(Prompt)}");
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+# Using MCP Client as Tools with the Responses API
+
+This sample shows how to use MCP (Model Context Protocol) client tools with a `ChatClientAgent` using the Responses API directly.
+
+## What this sample demonstrates
+
+- Connecting to an MCP server via HTTP client transport
+- Retrieving MCP tools and passing them to a `ChatClientAgent`
+- Using MCP tools for agent interactions without server-side agent creation
+
+## Prerequisites
+
+- .NET 10 SDK or later
+- Microsoft Foundry service endpoint and deployment configured
+- An authenticated Azure identity (for example, sign in with `az login`)
+- Node.js installed (for npx/MCP server)
+
+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
+```
+