agui-dotnet-server-tools

AG-UI .NET — server (backend) tools

Goal: let the model call a C# function that runs on your server, with the server executing the call and returning the result so the run continues to a final answer.

A server tool is an ordinary Microsoft.Extensions.AI AIFunction registered on the server's IChatClient. The FunctionInvokingChatClient executes it inside the run; the client sends no tools and needs no tool code, and receives the final answer. Tool-call and result events still cross the wire — the client just never executes anything.

Install

dotnet add package AGUI.Server
dotnet add package AGUI.Formatting

Microsoft.Extensions.AI supplies AIFunctionFactory, AddChatClient, and UseFunctionInvocation. Run dotnet package search AGUI.Server --exact-match for the current version.

Define and register a tool

Create the function with AIFunctionFactory.Create, add it to the chat client's tools, and enable function invocation:

using System.ComponentModel;
using Microsoft.Extensions.AI;

[Description("Search for restaurants in a location.")]
static RestaurantSearchResponse SearchRestaurants(
    [Description("Where to search and what cuisine.")] RestaurantSearchRequest request)
{
    // ... real lookup ...
}

var builder = WebApplication.CreateBuilder(args);

var searchRestaurants = AIFunctionFactory.Create(
    SearchRestaurants,
    serializerOptions: SampleJsonSerializerContext.Default.Options);

builder.Services.AddChatClient(
        new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
            .GetChatClient(deploymentName)
            .AsIChatClient())
    .ConfigureOptions(o => (o.Tools ??= []).Add(searchRestaurants))
    .UseFunctionInvocation(fic => fic.TerminateOnUnknownCalls = true);

The [Description] attributes become the tool and parameter schema the model sees. Any Microsoft.Extensions.AI provider works in place of Azure OpenAI.

AOT-safe tool arguments and results

When a tool takes or returns a complex type (anything beyond primitives), its schema and (de)serialization must be source-generated, not reflection-based. Put the parameter and result types in a JsonSerializerContext, register it on the host's JSON options, and pass it to AIFunctionFactory.Create: