MCP Apps vs A2UI: UI as a Resource vs UI as a Protocol

The world of Agentic UI is evolving at a breakneck pace. Following the massive, industry-wide success of the Model Context Protocol (MCP) originally spearheaded by Anthropic for data retrieval and tool-calling, the recent introduction of MCP Apps expanded the protocol’s ambitions to handle actual user interfaces.

At the exact same time, Google’s open-source A2UI is gaining immense traction as the definitive standard for “Agent-Driven Interfaces.”

Both protocols ultimately allow an AI agent to “show” a visual UI to the end user instead of just spitting out plain text. However, they take fundamentally different—and often opposing—architectural approaches to achieve this goal. In this deep dive, our engineering team compares MCP Apps (UI as a Resource) against A2UI (UI as a Protocol) across four critical dimensions to help you choose the right paradigm for your Next.js, Flutter, or React Native stack.

1. The Core Architecture: Sandboxes vs Blueprints

MCP Apps: The Iframe Sandbox

The MCP Apps mental model treats the UI as an opaque, external resource. When an agent determines it needs to show a custom interface, it requests a UI resource via a specialized ui:// URI. The responding MCP server generates and returns a complete bundle of pre-rendered HTML, CSS, and potentially executable JavaScript.

The host application (your chat interface) then takes this bundle and renders it blindly, typically by isolating it within a highly restricted <iframe>. The host app does not know—or care—what the HTML consists of; it simply acts as a dumb display container.

A2UI: The Native Blueprint

A2UI takes entirely the opposite approach. When an AI agent utilizes A2UI, it sends a streaming, strongly-typed JSON payload across the wire. This JSON contains absolutely no executable code. It is simply a declarative, mathematical blueprint (e.g., {"type": "Card", "children": [{"type": "Button", "label": "Click Me"}]}).

The host application receives this raw data structure and uses its own native, local components (like your custom React components or Flutter widgets) to securely draw the interface pixel-by-pixel.

2. Platform Portability

Winner: A2UI

If you are strictly building a web browser application, MCP Apps work brilliantly. Browsers possess decades of optimized engineering built specifically to render HTML via isolated iframes.

However, the moment you step outside the browser, the facade crumbles. If you are building a cross-platform product—say, a mobile app in Flutter or React Native, or a native desktop app utilizing Tauri or Electron—forcing those native engines to spin up off-screen webviews just to render arbitrary HTML iframes feels clunky, incredibly slow, and distinctly non-native.

Because A2UI relies on a dumb data protocol, the exact same JSON payload streamed from the agent will elegantly render as a native iOS UIButton on an iPhone, a Material Button on an Android device, and a React <Button> on the web.

3. Styling and Design Continuity

Winner: A2UI

Have you ever embedded a third-party weather widget or a stock ticker on your beautiful, carefully crafted website, only to find that its font, border radius, and clashing colors completely ruined your brand’s aesthetic? That is the exact risk you assume with MCP Apps.

Because the MCP App developer dictates the HTML and CSS bundle on their server, forcing that remote UI to perfectly match your host application’s highly specific design system (like your custom Tailwind config) is exceedingly difficult and often requires messy CSS overrides.

With A2UI’s upcoming advanced theming engine in v0.9, the AI agent never decides what the UI visually looks like; the agent only dictates what information is semantically shown. The host application’s local renderer retains absolute, dictatorial control over the styling cascade. A “primary button” generated by an agent via A2UI will look algorithmically identical to every other primary button in your app, automatically inheriting your dark mode status and exact design tokens.

4. Security and Trust Boundaries

Winner: A2UI (for deep embedding), Tie (for isolated full-screen tools)

Security is the single biggest selling point of A2UI. By physically refusing to transmit executable HTML or JavaScript code over the wire, A2UI makes UX injection attacks mathematically impossible. The LLM agent only has permissions to reference a pre-approved, strictly typed “catalog” of safe components that already live on the client.

MCP Apps, conversely, rely heavily on browser-level iframe sandboxing architectures for their security. While generally robust, an escaped iframe sandbox is a well-documented and historically lucrative attack vector in cybersecurity, especially when the generated HTML is hallucinated by an unpredictable LLM.

The Verdict: When to Use Which?

The reality of 2026 is that you will likely use both, and you will frequently use them in the exact same application. Leading orchestration layers like CopilotKit natively support both protocols today.

Use MCP Apps when: You need to present a highly complex, self-contained, and isolated monolithic tool (like a full-blown interactive 3D WebGL model viewer, a legacy internal dashboard, or a complex third-party terminal emulator) that an agent summons as a full-page modal popup. In these scenarios, the UI is too bespoke to map to a standard JSON schema.
Use A2UI when: You want the agent to embed rich, native, contextual widgets inline within a chat stream or a dynamic dashboard. If it needs to perfectly match your brand’s meticulous design system, feel indistinguishable from your hardcoded React components, and guarantee absolute zero code-injection risk across both Web and Mobile platforms, A2UI is unmatched.