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46 lines
2.0 KiB
C#
46 lines
2.0 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to expose an AI agent as an MCP tool.
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using Azure.AI.Projects;
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using Azure.AI.Projects.Agents;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.DependencyInjection;
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using Microsoft.Extensions.Hosting;
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using ModelContextProtocol.Server;
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var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
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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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var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());
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// Create a server side agent and expose it as an AIAgent.
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ProjectsAgentVersion agentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(
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"Joker",
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new ProjectsAgentVersionCreationOptions(
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new DeclarativeAgentDefinition(model: deploymentName)
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{
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Instructions = "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.",
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})
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{
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Description = "An agent that tells jokes.",
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});
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AIAgent agent = aiProjectClient.AsAIAgent(agentVersion);
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// Convert the agent to an AIFunction and then to an MCP tool.
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// The agent name and description will be used as the mcp tool name and description.
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McpServerTool tool = McpServerTool.Create(agent.AsAIFunction());
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// Register the MCP server with StdIO transport and expose the tool via the server.
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HostApplicationBuilder builder = Host.CreateEmptyApplicationBuilder(settings: null);
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builder.Services
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.AddMcpServer()
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.WithStdioServerTransport()
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.WithTools([tool]);
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await builder.Build().RunAsync();
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