In the previous post “Leveraging Microsoft.Extensions.AI for Tool Calling in C#“, we explored how to create custom tools that enhance the capabilities of Large Language Models (LLMs). We demonstrated how integrating these technologies enables developers to build applications with advanced AI capabilities, facilitating more complex interactions.

In this post, we’ll take a step further and explore how to leverage Model Context Protocol (MCP) servers to utilize external Tools and AI models in C# applications. We’ll continue using Ollama to run local AI models.

.NET Aspire 9.1 was just released on February 25th, 2025. It comes with great new dashboard features, and there is more! One feature I am particularly interested in is the ability to use Dev Containers.

In this post, I will show you how to use the new .NET Aspire 9.1 with a Dev Container and JetBrains Rider. You could also use Visual Studio Code.

In my previous post, we saw how to build the simplest Semantic Kernel local AI agent using Semantic Kernel and Ollama in C#. In this short post, we will see how simple it is to extend the capabilities of the Semantic Kernel local AI agent by adding function calling.

The recent release of Microsoft’s Semantic Kernel Agents Framework RC1 provides an excellent opportunity to explore its capabilities with C#. In this post, we’ll walk through creating a simple agent using this framework and running it locally with Ollama.

Let’s dive in!

In my earlier posts, I’ve demonstrated how to install Ollama using the Windows installer. However, for developers, there’s a more streamlined method to set up Ollama on your machine.

In this blog post, we’ll explore how to run DeepSeek-R1 by harnessing the capabilities of .NET Aspire alongside Ollama on your local environment.

In the previous post “Learning AI function calling in C# with Llama 3.2 SLM and Ollama running on your machine“, we wrapped our head around the concept of tool calling and implemented a C# source generator enabling our functions to be called by Llama 3.2 SLM using Ollama.

In this post, we will explore how to use Microsoft Extensions AI for tool calling in a simple .NET CLI application. We will leverage the power of Ollama and Llama 3.2 SLM to call functions and interact with the AI model using C#.