Automatic report generation using advanced MCP features

The Model Context Protocol specification has the goal of standardizing the way that Large Language Models (LLM) connect to your data sources and tools - like a USB-C for AI.

Foundry Local, the new OpenAI models and the Harmony response format

About a week ago (prior to the release of the highly anticipated GPT-5 model), OpenAI released its first open weights model since GPT-2, the gpt-oss-20b and gpt-oss-120b models.

I tried out gpt-oss-20b (the 20 billion parameter model) using LM Studio, and recorded a video showing how well the model handles tool-calling, using the Dataverse MCP Server.

The anatomy of FetchXML Builder with AI

Jonas Rapp has just released an update to FetchXML Builder that makes it possible to use AI to construct FetchXml queries - see the release notes and his post on LinkedIn.

As I have mentioned, I have had the pleasure of helping Jonas to implement this functionality, which has been fun in all kinds of ways.

Semantic Kernel - what it is and how to use it for MCP

The Semantic Kernel from Microsoft is an AI orchestration framework designed to simplify the development of applications powered by Large Language Models (LLMs). It serves a similar purpose as frameworks like LangChain, providing tools and abstractions to integrate LLMs, connect to external data sources like Model Context Protocol (MCP) Servers, and to orchestrate AI agents.

Evaluation of large language models with Dataverse MCP Server

In a number of posts on LinkedIn I have demonstrated various ways of using the Dataverse MCP Server from Microsoft, which allows access to data in Dataverse from your AI tool of choice