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AI Platform Development

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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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