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87 lines
3.9 KiB
C#
87 lines
3.9 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates how to use a local MCP (Model Context Protocol) client with Azure Foundry Agents.
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// The MCP tools are resolved locally by connecting directly to the MCP server via HTTP,
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// and then passed to the Foundry agent as client-side tools.
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// This sample uses the Microsoft Learn MCP endpoint to search documentation.
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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using ModelContextProtocol.Client;
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string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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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.";
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const string AgentName = "DocsAgent";
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// Connect to the MCP server locally via HTTP (Streamable HTTP transport).
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// The MCP server is hosted at Microsoft Learn and provides documentation search capabilities.
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Console.WriteLine("Connecting to MCP server at https://learn.microsoft.com/api/mcp ...");
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await using McpClient mcpClient = await McpClient.CreateAsync(new HttpClientTransport(new()
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{
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Endpoint = new Uri("https://learn.microsoft.com/api/mcp"),
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Name = "Microsoft Learn MCP",
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}));
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// Retrieve the list of tools available on the MCP server (resolved locally).
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IList<McpClientTool> mcpTools = await mcpClient.ListToolsAsync();
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Console.WriteLine($"MCP tools available: {string.Join(", ", mcpTools.Select(t => t.Name))}");
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// Wrap each MCP tool with a DelegatingAIFunction to log local invocations.
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List<AITool> wrappedTools = mcpTools.Select(tool => (AITool)new LoggingMcpTool(tool)).ToList();
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// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
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// Create the agent with the locally-resolved MCP tools.
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AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
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model: deploymentName,
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name: AgentName,
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instructions: AgentInstructions,
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tools: wrappedTools);
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Console.WriteLine($"Agent '{agent.Name}' created successfully.");
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try
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{
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// First query
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const string Prompt1 = "How does one create an Azure storage account using az cli?";
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Console.WriteLine($"\nUser: {Prompt1}\n");
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AgentResponse response1 = await agent.RunAsync(Prompt1);
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Console.WriteLine($"Agent: {response1}");
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Console.WriteLine("\n=======================================\n");
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// Second query
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const string Prompt2 = "What is Microsoft Agent Framework?";
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Console.WriteLine($"User: {Prompt2}\n");
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AgentResponse response2 = await agent.RunAsync(Prompt2);
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Console.WriteLine($"Agent: {response2}");
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}
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finally
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{
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// Cleanup by removing the agent when done
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await aiProjectClient.Agents.DeleteAgentAsync(agent.Name);
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Console.WriteLine($"\nAgent '{agent.Name}' deleted.");
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}
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/// <summary>
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/// Wraps an MCP tool to log when it is invoked locally,
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/// confirming that the MCP call is happening client-side.
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/// </summary>
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internal sealed class LoggingMcpTool(AIFunction innerFunction) : DelegatingAIFunction(innerFunction)
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{
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protected override ValueTask<object?> InvokeCoreAsync(AIFunctionArguments arguments, CancellationToken cancellationToken)
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{
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Console.WriteLine($" >> [LOCAL MCP] Invoking tool '{this.Name}' locally...");
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return base.InvokeCoreAsync(arguments, cancellationToken);
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}
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}
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