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agent-framework/dotnet/samples/02-agents/Agents/Agent_Step07_AsMcpTool/Program.cs
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Roger BarretoandGitHub b0613a8ceb .NET: Bump Azure.AI.Projects to 2.0.0 GA (#5060)
* Bump Azure.AI.Projects to 2.0.0 GA

- Update Azure.AI.Projects from 2.0.0-beta.2 to 2.0.0 in CPM
- Update Azure.Identity from 1.19.0 to 1.20.0 (transitive dep)
- Update System.ClientModel from 1.9.0 to 1.10.0 (transitive dep)
- Rename types per Azure.AI.Projects.Agents 2.0.0 breaking changes:
  - AgentVersion -> ProjectsAgentVersion
  - AgentRecord -> ProjectsAgentRecord
  - AgentDefinition -> ProjectsAgentDefinition
  - AgentVersionCreationOptions -> ProjectsAgentVersionCreationOptions
  - PromptAgentDefinition -> DeclarativeAgentDefinition
  - AgentTool -> ProjectsAgentTool
  - AgentsClient -> AgentAdministrationClient
  - .Agents property -> .AgentAdministrationClient
- Add using Azure.AI.Projects.Memory namespace (types moved)
- Update AGENTS.md with BOM and output capture conventions

* Address PR review feedback

- Rename AIProjectClient parameter to aiProjectClient in AsChatClientAgent overloads
- Fix XML doc: ProjectsAgentTool namespace from Azure.AI.Projects.OpenAI to Azure.AI.Projects.Agents
- Rename test method to reflect DeclarativeAgentDefinition terminology
2026-04-02 14:02:29 +00:00

46 lines
2.0 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to expose an AI agent as an MCP tool.
using Azure.AI.Projects;
using Azure.AI.Projects.Agents;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using ModelContextProtocol.Server;
var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-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.
var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());
// Create a server side agent and expose it as an AIAgent.
ProjectsAgentVersion agentVersion = await aiProjectClient.AgentAdministrationClient.CreateAgentVersionAsync(
"Joker",
new ProjectsAgentVersionCreationOptions(
new DeclarativeAgentDefinition(model: deploymentName)
{
Instructions = "You are good at telling jokes, and you always start each joke with 'Aye aye, captain!'.",
})
{
Description = "An agent that tells jokes.",
});
AIAgent agent = aiProjectClient.AsAIAgent(agentVersion);
// Convert the agent to an AIFunction and then to an MCP tool.
// The agent name and description will be used as the mcp tool name and description.
McpServerTool tool = McpServerTool.Create(agent.AsAIFunction());
// Register the MCP server with StdIO transport and expose the tool via the server.
HostApplicationBuilder builder = Host.CreateEmptyApplicationBuilder(settings: null);
builder.Services
.AddMcpServer()
.WithStdioServerTransport()
.WithTools([tool]);
await builder.Build().RunAsync();