Agent Skills: ChatGPT Apps SDK Best Practices

WHEN building ChatGPT apps using the OpenAI Apps SDK and MCP; create conversational, composable experiences with proper UX, UI, state management, and server patterns.

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Skill Metadata

Name
chatgpt-app-sdk
Description
WHEN building ChatGPT apps using the OpenAI Apps SDK and MCP; create conversational, composable experiences with proper UX, UI, state management, and server patterns.

ChatGPT Apps SDK Best Practices

Build ChatGPT apps using the OpenAI Apps SDK, Model Context Protocol (MCP), and component-based UI patterns.

Quick Reference

| Topic | Guide | | ----------------------------------------------- | ----------------------------------------------------------- | | Display modes, visual design, accessibility | ui-guidelines.md | | MCP architecture, tools, and server patterns | mcp-server.md | | React patterns and window.openai API | ui-components.md | | React hooks (useOpenAiGlobal, useWidgetState) | react-integration.md | | Three-tier state architecture and best practice | state-management.md |

Critical Setup Requirements

| Issue | Prevention | | ------------------- | ----------------------------------------------------- | | CORS blocking | Enable https://chatgpt.com origin on endpoints | | Widget 404s | Use ui://widget/ prefix format for widget resources | | Plain text display | Set MIME type to text/html+skybridge for widgets | | Tool not suggested | Use action-oriented descriptions in tool definitions | | Missing widget data | Pass initial data via _meta.initialData field | | CSP script blocking | Reference external scripts from allowed CDN origins |

Decision Trees

What display mode should I use?

Is this a multi-step workflow or deep exploration?
├── Yes → Fullscreen
└── No → Is this a parallel activity (game, live session)?
    ├── Yes → Picture-in-Picture (PiP)
    └── No → Inline
        ├── Single item with quick action → Inline Card
        └── 3-8 similar items → Inline Carousel

Where should state live?

Is this data from your API/database?
├── Yes → MCP Server (Business Data)
│   Return in structuredContent from tool calls
└── No → Is it user preference/cross-session data?
    ├── Yes → Backend Storage (via OAuth)
    └── No → Widget State (UI-scoped)
        Use window.openai.widgetState / useWidgetState

Should this be a separate tool?

Is this action:
- Atomic and standalone?
- Invokable by the model via natural language?
- Returning structured data?
├── Yes → Create public tool (model-accessible)
└── No → Is it only for widget interactions?
    ├── Yes → Use private tool ("openai/visibility": "private")
    └── No → Handle within existing tool logic

What should go in structuredContent vs _meta?

Does the model need this data to:
- Understand results?
- Generate follow-ups?
- Reason about next steps?
├── Yes → structuredContent (concise, model-readable)
└── No → _meta (large datasets, widget-only data)

Should I use custom UI or just text?

Does this require:
- User input beyond text?
- Structured data visualization?
- Interactive selection/filtering?
├── Yes → Custom UI component
└── No → Return plain text/markdown in content

Official Documentation

  • MCP Specification: https://modelcontextprotocol.io
  • TypeScript MCP SDK: https://github.com/modelcontextprotocol/typescript-sdk
  • OpenAI Apps SDK: https://developers.openai.com/apps-sdk
  • MCP Apps Extension: http://blog.modelcontextprotocol.io/posts/2025-11-21-mcp-apps
  • ChatGPT Component Library: https://openai.github.io/apps-sdk-ui