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Topic

MCP Apps

All digests tagged MCP Apps

Rebuilding the web for agents — Liad Yosef, MCP Apps thumbnail

· 20:41

Rebuilding the web for agents — Liad Yosef, MCP Apps

The talk outlines the transition to the 'agentic web,' arguing that traditional websites and browser tabs are becoming obsolete as primary interfaces. The core shift involves breaking down complex UIs into atomic components that can be composed by personal AI assistants. The speaker, a co-creator of the MCP Apps specification, details how MCP Apps allows servers to hand real UI interfaces back into a chat context, solving the 'last mile of interaction.' Furthermore, the talk introduces the need for a standardized discovery layer, proposing the use of `AI catalog.json` to make websites 'agent ready' and accessible to autonomous agents.

Key takeaways

  1. MCP Apps Solves Last-Mile Interaction 1:42

    MCP Apps allows providers to send UI chunks into chats, ensuring that services retain their brand identity and functionality rather than being reduced to text or databases. This solves the 'last mile' problem for agents, enabling complex interactions like booking hotels or viewing 3D models within a unified chat context.

  2. The Agentic Web Paradigm Shift 5:40

    The web is shifting from being a collection of siloed websites (requiring multiple tabs and different UIs for the same intent) to being composed by personal assistants. Assistants become the primary entry point, making websites themselves less critical for task completion.

  3. Need for Agent-Specific Discovery 19:16

    Traditional standards like `llms.txt` are insufficient because agents often ignore them, preferring to navigate to docs or homepages. The solution requires a standardized, machine-readable directory, such as the proposed `AI catalog.json`, to expose a website's MCP and API servers directly to agents.

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MCP Apps: Give the Model Data, Give the User a UI — Dustin Mihalik, Indeed thumbnail

· 15:34

MCP Apps: Give the Model Data, Give the User a UI — Dustin Mihalik, Indeed

This talk details the architectural challenges of building Model-Composable Platform (MCP) applications for large language models (LLMs) like Claude and ChatGPT. The core thesis is that for a UI widget to function effectively, it must be treated as a data layer, not just a visual display. The speaker outlines three critical rules for developers: all displayed information must be provided as data to the model; the tool description must explicitly state that a UI exists; and, most importantly, data processing must be strictly separated from UI rendering to maintain model context and reasoning capability.

Key takeaways

  1. Data-First Design Principle

    When building MCP apps, developers must focus on defining the data the model needs to process before considering the UI. The UI should be viewed as a side effect or result of the model exploring the underlying data.

  2. Rule 1: Show the Model Everything 5:13

    Any information displayed to the user via the UI must also be provided as structured data to the model. Failing to do so creates a 'black box' that prevents the model from answering follow-up questions about the displayed content.

  3. Rule 2: Declare the UI in the Description 8:26

    The tool description must explicitly state that a UI exists. Otherwise, the model will attempt to narrate the results underneath the widget, leading to redundant and confusing output.

  4. Rule 3: Separate Data Processing from UI Rendering 13:39

    This rule supersedes the others. The architecture must split the job into two distinct tools: one for pure data retrieval (e.g., `search_jobs`) and a separate, dedicated tool for rendering the results (e.g., `render_jobs`). This allows the model to perform complex data exploration without being limited by the UI's single call.

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Evolving AI chat with MCP Apps - Phil Nash - NDC Copenhagen 2026 thumbnail

· 38:00

Evolving AI chat with MCP Apps - Phil Nash - NDC Copenhagen 2026

The talk introduces MCP Apps, a proposed open standard designed to evolve AI chat interfaces beyond plain text. By integrating rich, interactive web UIs (built with HTML/CSS/JavaScript) directly into the conversation flow, MCP Apps allow agents to render mini-applications for tasks like booking hotels or managing playlists. This approach moves interaction from boring 'walls of text' to engaging, visual experiences, making AI more useful for complex user workflows.

Key takeaways

  1. The Need for Interactive UIs in Chat 18:02

    Traditional chat interactions are limited to text (or code/tool calls), which is insufficient for tasks requiring visual exploration, configuration of multiple options, or viewing real-time data. MCP Apps solve this by bringing web-powered interfaces into the chat environment.

  2. MCP Apps as an Open Standard 22:40

    MCP Apps is a standard inspired by community efforts (like MCP-UI) and commercial SDKs (e.g., OpenAI's Apps SDK), aiming to provide a unified way for agents to render UIs across different model providers.

  3. Core Functionality: Sandboxed Web Views 26:00

    MCP Apps are implemented as sandboxed web applications (HTML, CSS, JavaScript) loaded within an iframe. This isolation keeps the UI safe while allowing it to interact with the agent host via tool calls and a JSON RPC mechanism.

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