Umbraco CMS is a .NET content management platform used by individuals and large enterprise for everything from personal blogs to global SaaS products. It's powerful, extensible, easy to use, and open source. And it's evolving to embrace AI in ways that genuinely improve developer and content author experiences.
The new features and capabilities are foundational, based on real world needs, taking advantage of the technical opportunities large language models (LLMs) provide, targeting discreet areas in the platform. There are official Umbraco blog posts that talk about philosophy, areas of focus, primers on the individual AI technologies, and more. The goal of this post is to provide a high-level summary of the changes and who they affect.
Umbraco is constantly evolving, most notably relating a new major version each year just after Microsoft likewise releases a new major version of .NET. This is a blessing and a curse. On one hand, Umbraco developers get to take advantage of new .NET performance, security, and other features. But supporting a sprawling ecosystem of Umbraco versions is a challenge, especially when the breaking changes and development patterns change so frequently and vary so much between major releases.
To address this, the Umbraco CMS team has added integrations to your AI agent platform of choice. These integrations provide more Umbraco CMS technical information to the agents, including best practices, as well as giving them controlled access to your schema and data through official Umbraco CMS APIs.
The MCP standard allows the hosting of very specific tools that can be used by AI agents to get things done in a more simple, direct way. Umbraco supports this by providing a separate MCP host application that developers can run to give their agents this extra functionality. It talks directly to Umbraco through the Management API and gives your agent deep access to your Umbraco schema and data.
Originally a Claude Code-only feature, but not available in other AI agent platforms like OpenAI Codex, agent skills are a way to tell the AI coding environment about a given technology, which speeds development and ensures that the correct development patterns (best practices) are followed.
There's usually more to the story so if you have questions or comments about this post let us know!
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