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.NET: Response & foundry agent hosted MCP sample (#1568)

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* Adding sample demonstrating hosted MCP with Responses

* Add mcp readme.md to slnx

* Update FoundryAgent sample to use MCP types from abstraction and to show how to do approval

* Fix param name after package update.

* Fix environment variable name for consistency

* Apply suggestion from @Copilot

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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westey
2025-11-04 15:54:20 +00:00
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parent 50d9b13bfc
commit 64fc3f381f
6 changed files with 220 additions and 31 deletions
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dotnet/samples/GettingStarted/ModelContextProtocol/ResponseAgent_Hosted_MCP/Program.cs
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// Copyright (c) Microsoft. All rights reserved.
// This sample shows how to create and use a simple AI agent with OpenAI Responses as the backend, that uses a Hosted MCP Tool.
// In this case the OpenAI responses service will invoke any MCP tools as required. MCP tools are not invoked by the Agent Framework.
// The sample first shows how to use MCP tools with auto approval, and then how to set up a tool that requires approval before it can be invoked and how to approve such a tool.
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
// **** MCP Tool with Auto Approval ****
// *************************************
// Create an MCP tool definition that the agent can use.
// In this case we allow the tool to always be called without approval.
var mcpTool = new HostedMcpServerTool(
serverName: "microsoft_learn",
serverAddress: "https://learn.microsoft.com/api/mcp")
{
AllowedTools = ["microsoft_docs_search"],
ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire
};
// Create an agent based on Azure OpenAI Responses as the backend.
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
.GetOpenAIResponseClient(deploymentName)
.CreateAIAgent(
instructions: "You answer questions by searching the Microsoft Learn content only.",
name: "MicrosoftLearnAgent",
tools: [mcpTool]);
// You can then invoke the agent like any other AIAgent.
AgentThread thread = agent.GetNewThread();
Console.WriteLine(await agent.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", thread));
// **** MCP Tool with Approval Required ****
// *****************************************
// Create an MCP tool definition that the agent can use.
// In this case we require approval before the tool can be called.
var mcpToolWithApproval = new HostedMcpServerTool(
serverName: "microsoft_learn",
serverAddress: "https://learn.microsoft.com/api/mcp")
{
AllowedTools = ["microsoft_docs_search"],
ApprovalMode = HostedMcpServerToolApprovalMode.AlwaysRequire
};
// Create an agent based on Azure OpenAI Responses as the backend.
AIAgent agentWithRequiredApproval = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
.GetOpenAIResponseClient(deploymentName)
.CreateAIAgent(
instructions: "You answer questions by searching the Microsoft Learn content only.",
name: "MicrosoftLearnAgentWithApproval",
tools: [mcpToolWithApproval]);
// You can then invoke the agent like any other AIAgent.
var threadWithRequiredApproval = agentWithRequiredApproval.GetNewThread();
var response = await agentWithRequiredApproval.RunAsync("Please summarize the Azure AI Agent documentation related to MCP Tool calling?", threadWithRequiredApproval);
var userInputRequests = response.UserInputRequests.ToList();
while (userInputRequests.Count > 0)
{
// Ask the user to approve each MCP call request.
// For simplicity, we are assuming here that only MCP approval requests are being made.
var userInputResponses = userInputRequests
.OfType<McpServerToolApprovalRequestContent>()
.Select(approvalRequest =>
{
Console.WriteLine($"""
The agent would like to invoke the following MCP Tool, please reply Y to approve.
ServerName: {approvalRequest.ToolCall.ServerName}
Name: {approvalRequest.ToolCall.ToolName}
Arguments: {string.Join(", ", approvalRequest.ToolCall.Arguments?.Select(x => $"{x.Key}: {x.Value}") ?? [])}
""");
return new ChatMessage(ChatRole.User, [approvalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
})
.ToList();
// Pass the user input responses back to the agent for further processing.
response = await agentWithRequiredApproval.RunAsync(userInputResponses, threadWithRequiredApproval);
userInputRequests = response.UserInputRequests.ToList();
}
Console.WriteLine($"\nAgent: {response}");