Add MCP for vertex

Add support for Vertex AI Gemini chat completions and expose location on Mcp. Mcp.cs: introduce a new Location property with default "us-central1". McpService.cs: refactor InitializeChatCompletions to accept the Mcp config (and derive backend and model from it), add a using for LLMService.Auth, and wire up a Vertex backend case that creates a Google service-account token provider, builds a bearer token delegate, normalizes the model name, and registers the VertexAIGemini chat completion with the kernel using config.Location and the project ID. Also adjust the promptSettings call site to pass the config. Includes an auth presence check that throws if Vertex credentials are not configured.

Author: Madzionator

src/MaIN.Domain/Entities/Mcp.cs

@@ -8,6 +8,7 @@ public class Mcp
     public required List<string> Arguments { get; init; }
     public required string Command { get; init; }
     public required string Model { get; init; }
+    public string Location { get; set; } = "us-central1";
     public Dictionary<string, string> Properties { get; set; } = [];
     public BackendType? Backend { get; set; }
     public Dictionary<string, string> EnvironmentVariables { get; set; } = [];

src/MaIN.Services/Services/McpService.cs

@@ -2,6 +2,7 @@
 using MaIN.Domain.Entities;
 using MaIN.Domain.Models.Concrete;
 using MaIN.Services.Services.Abstract;
+using MaIN.Services.Services.LLMService.Auth;
 using MaIN.Services.Services.LLMService.Utils;
 using MaIN.Services.Services.Models;
 using Microsoft.SemanticKernel;
@@ -30,7 +31,7 @@ public async Task<McpResult> Prompt(Mcp config, List<Message> messageHistory)
         );
 
         var builder = Kernel.CreateBuilder();
-        var promptSettings = InitializeChatCompletions(builder, config.Backend ?? settings.BackendType, config.Model);
+        var promptSettings = InitializeChatCompletions(builder, config);
         var kernel = builder.Build();
         var tools = await mcpClient.ListToolsAsync();
         kernel.Plugins.AddFromFunctions("Tools", tools.Select(x => x.AsKernelFunction()));
@@ -49,10 +50,10 @@ public async Task<McpResult> Prompt(Mcp config, List<Message> messageHistory)
         }
 
         var chatService = kernel.GetRequiredService<IChatCompletionService>();
-    
+
         var result = await chatService.GetChatMessageContentsAsync(
-            chatHistory, 
-            promptSettings, 
+            chatHistory,
+            promptSettings,
             kernel);
 
         return new McpResult
@@ -68,8 +69,11 @@ public async Task<McpResult> Prompt(Mcp config, List<Message> messageHistory)
         };
     }
 
-    private PromptExecutionSettings InitializeChatCompletions(IKernelBuilder kernelBuilder, BackendType backendType, string model)
+    private PromptExecutionSettings InitializeChatCompletions(IKernelBuilder kernelBuilder, Mcp config)
     {
+        var backendType = config.Backend ?? settings.BackendType;
+        var model = config.Model;
+
         switch (backendType)
         {
             case BackendType.OpenAi:
@@ -118,6 +122,24 @@ private PromptExecutionSettings InitializeChatCompletions(IKernelBuilder kernelB
                     FunctionChoiceBehavior = FunctionChoiceBehavior.Auto(options: new() { RetainArgumentTypes = true })
                 };
 
+            case BackendType.Vertex:
+                var auth = settings.GoogleServiceAccountAuth
+                           ?? throw new InvalidOperationException("Vertex AI service account is not configured.");
+                var tokenProvider = new GoogleServiceAccountTokenProvider(auth);
+                var httpClient = new HttpClient();
+                Func<ValueTask<string>> bearerTokenProvider = async ()
+                    => await tokenProvider.GetAccessTokenAsync(httpClient);
+
+                var modelName = model.StartsWith("google/", StringComparison.OrdinalIgnoreCase)
+                    ? model["google/".Length..]
+                    : model;
+
+                kernelBuilder.Services.AddVertexAIGeminiChatCompletion(modelName, bearerTokenProvider, config.Location, auth.ProjectId);
+                return new GeminiPromptExecutionSettings
+                {
+                    FunctionChoiceBehavior = FunctionChoiceBehavior.Auto(options: new() { RetainArgumentTypes = true })
+                };
+
             case BackendType.Ollama:
                 throw new NotSupportedException("Ollama models does not support MCP integration.");