wehub-resource-sync
74 lines
3.2 KiB
C#
74 lines
3.2 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Threading.Tasks;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Agents;
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using Microsoft.SemanticKernel.Connectors.OpenAI;
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using ModelContextProtocol.Client;
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namespace MCPClient.Samples;
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/// <summary>
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/// Demonstrates how to use <see cref="ChatCompletionAgent"/> with MCP tools represented as Kernel functions.
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/// </summary>
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internal sealed class ChatCompletionAgentWithMCPToolsSample : BaseSample
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{
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/// <summary>
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/// Demonstrates how to use <see cref="ChatCompletionAgent"/> with MCP tools represented as Kernel functions.
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/// The code in this method:
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/// 1. Creates an MCP client.
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/// 2. Retrieves the list of tools provided by the MCP server.
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/// 3. Creates a kernel and registers the MCP tools as Kernel functions.
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/// 4. Defines chat completion agent with instructions, name, kernel, and arguments.
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/// 5. Invokes the agent with a prompt.
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/// 6. The agent sends the prompt to the AI model, together with the MCP tools represented as Kernel functions.
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/// 7. The AI model calls DateTimeUtils-GetCurrentDateTimeInUtc function to get the current date time in UTC required as an argument for the next function.
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/// 8. The AI model calls WeatherUtils-GetWeatherForCity function with the current date time and the `Boston` arguments extracted from the prompt to get the weather information.
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/// 9. Having received the weather information from the function call, the AI model returns the answer to the agent and the agent returns the answer to the user.
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/// </summary>
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public static async Task RunAsync()
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{
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Console.WriteLine($"Running the {nameof(ChatCompletionAgentWithMCPToolsSample)} sample.");
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// Create an MCP client
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McpClient mcpClient = await CreateMcpClientAsync();
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// Retrieve and display the list provided by the MCP server
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IList<McpClientTool> tools = await mcpClient.ListToolsAsync();
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DisplayTools(tools);
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// Create a kernel and register the MCP tools as kernel functions
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Kernel kernel = CreateKernelWithChatCompletionService();
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kernel.Plugins.AddFromFunctions("Tools", tools.Select(aiFunction => aiFunction.AsKernelFunction()));
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// Enable automatic function calling
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OpenAIPromptExecutionSettings executionSettings = new()
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{
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FunctionChoiceBehavior = FunctionChoiceBehavior.Auto(options: new() { RetainArgumentTypes = true })
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};
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string prompt = "What is the likely color of the sky in Boston today?";
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Console.WriteLine(prompt);
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// Define the agent
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ChatCompletionAgent agent = new()
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{
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Instructions = "Answer questions about the weather.",
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Name = "WeatherAgent",
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Kernel = kernel,
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Arguments = new KernelArguments(executionSettings),
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};
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// Invokes agent with a prompt
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ChatMessageContent response = await agent.InvokeAsync(prompt).FirstAsync();
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Console.WriteLine(response);
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Console.WriteLine();
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// The expected output is: The sky in Boston today is likely gray due to rainy weather.
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}
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}
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