How ChatGPT Apps Really Work: Inside the OpenAI Apps SDK

What Are ChatGPT Apps?

The OpenAI Apps SDK lets developers build interactive experiences that live directly inside ChatGPT.

Instead of opening a separate site, your app appears inline, as part of the chat itself.

Each app is essentially a mini web app running in a sandboxed iframe. Its frontend communicates with ChatGPT through the window.openai bridge, syncing data with your backend MCP server and the model’s reasoning in real time.

MCP and Widgets

Every ChatGPT app has two main parts:

• MCP server: hosts your tools and handles logic


• Widgets: the visual layer rendered inside ChatGPT

The Model Context Protocol (MCP) connects models to external data and tools, ensuring the UI, server, and model stay in sync.

Widgets are fetched from the MCP server and displayed inline — charts, tables, forms, anything interactive — all while staying inside the chat interface.

Because MCP supports streaming and SSE, Apps SDK experiences feel fast, real-time, and deeply conversational.

High-Level Workflow

Here’s the flow when a user says something like:

“Show my recently played songs on Spotify.”

1. Model triggers a tool → ChatGPT calls your MCP server (e.g., getRecentTracks).




2. MCP executes + returns metadata → Data + widget identifier.




3. Widget loads → React-based component is fetched.




4. ChatGPT renders it inline → Runs securely in a sandboxed iframe.

Through this sequence, model reasoning, backend logic, and frontend rendering work together seamlessly.

The window.openai Bridge

window.openai is what connects your widget (React component) to ChatGPT.

It gives your app access to theme, language, state, and even lets you invoke tools or send messages.

It’s a two-way bridge:

Your widget doesn’t just display data - it can also act inside the conversation.

This is what makes ChatGPT apps feel native rather than embedded.

User Experience Flow

1. *Discovery *- ChatGPT suggests or surfaces your app contextually (e.g., “Spotify, show my playlist”).




2. Inline interaction - The widget renders right in chat, matching ChatGPT’s layout and theme.




3. Context continuity - The app stays active across turns, preserving state and conversational flow.

Building Apps in Minutes with FastApps

The OpenAI Apps SDK provides the foundation, but you don’t have to start from scratch.

FastApps wraps the MCP server and SDK into a single Python-first framework.

pip install fastapps

fastapps init my-app

This spins up a ready-to-run ChatGPT app with:

• Server: Preconfigured MCP backend + auto-discovery


• Widgets: React components wired to window.openai


• Build & Dev: Live reload + ngrok tunnel built in

Then define your tool and UI:

# server/tools/my_widget_tool.py

class HelloTool(BaseWidget):

    async def execute(self, input):

        return {"message": f"Hello, {input.name}!"}

// widgets/my-widget/index.jsx

export default function HelloWidget() {

  const props = useWidgetProps();

  return <h1>{props.message}</h1>;

}

Run it locally:

npm run build

fastapps dev

Instantly live in ChatGPT. No config, no boilerplate.

Final Thoughts

The OpenAI Apps SDK feels like the early architecture of an agentic internet where models, tools, and humans coexist in one continuous conversational ecosystem. You can see the full article here.

If you want to build ChatGPT apps fast, FastApps makes it effortless.

Start today and deploy your first widget in minutes.