WebMCP: A Browser-Native Execution Model for AI Agents

On February 13, Google announced the Early Preview of WebMCP , introducing a browser-native way for AI agents to interact with websites. To understand why this matters, consider how agents operate today. AI agents interpret interfaces by parsing the DOM, inspecting accessibility trees, analyzing rendered pages, and then simulating clicks or inputs. Each action depends on inference over presentation layers. This increases token usage, adds latency, and often leads to brittle execution. The limitation is structural. The web was designed for people navigating interfaces. Agents, however, require clearly defined capabilities they can invoke programmatically. WebMCP addresses this gap by allowing websites to register structured JavaScript functions that agents can call directly within the browser runtime. These tools execute under existing session state and same-origin constraints, exposing only what the site explicitly defines. The result is a more direct model of interaction that aligns f