Becoming a Web AI Practitioner: A Map of the Emerging Stack
March 6, 2026
I quickly became fascinated with all the latest “Web AI” technologies, such as WebMCP, MCP Apps, MCP-UI, OpenAI’s Apps SDK, Google’s A2UI, and more. You’ll notice that MCP — the Model Context Protocol — is part of the name for some of these new technologies. That’s because MCP is a key connective protocol between AI agents and the Web. It allows agents to access web content, tools and services in a structured way.
I’ve also become extremely interested in on-device AI, using web browser technologies like LiteRT.js (a JavaScript runtime for running AI models in the browser using WebGPU) and Chrome’s built-in AI APIs, which provide access to on-device models like Gemini Nano.
When we think of AI and LLMs, we essentially think of very large systems running in the cloud that perhaps we access via APIs.
But there’s a whole slew of AI technologies that run in the browser, that run on devices. Broadly speaking these have come to be known as WebAI. here, Richard McManus gives an overview of the landscape of Web AI.
