A2UI

A2UI is a framework-agnostic standard for declaring AI-generated UI intent so agents can drive client interfaces using the client's existing component catalog.

Key points

  • Google frames A2UI v0.9 as a production-oriented answer to generative UI's separation-of-concerns problem: agents declare UI intent, while clients render through their own design systems and frameworks [src-038].
  • A2UI is meant to work across web, mobile, and other user surfaces, supporting local or remote agents that communicate with client applications through a common UI language [src-038].
  • Version 0.9 renames the optional component set from "Standard" to "Basic" to clarify that frontend teams can bring their own components rather than adopt a new component system [src-038].
  • The release adds a shared web-core library, official React renderer, updated Flutter/Lit/Angular/React renderers, and a space for community renderers [src-038].
  • The Agent SDK helps agents generate A2UI JSON, manage spec versions, produce system prompts, parse and repair model output, validate against catalogs, and stream UI parts [src-038].
  • A2UI supports simplified transports, including MCP, WebSockets, REST, AG-UI, and A2A [src-038].
  • Production features include version negotiation, dynamic catalogs, resilient streaming, client-defined functions, client-to-server data syncing, improved errors, and a modular schema [src-038].
  • Google's A2UI + MCP Apps article adds three integration patterns: A2UI over MCP servers, MCP Apps inside A2UI components, and A2UI inside MCP Apps [src-115].
  • The practical design choice is now more granular: use A2UI when the host app should render familiar components, and use MCP Apps when the workflow needs a custom sandboxed UI [src-115].

Related entities

Related concepts

Source references

  • [src-038] Google A2UI Team — "A2UI v0.9: The New Standard for Portable, Framework-Agnostic Generative UI" (2026-04-17)
  • [src-115] Google A2UI Team, Ido Salomon, Liad Yosef – "A2UI + MCP Apps: Combining the best of declarative and custom agentic UIs" (2026-06-17)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

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