How do I use ChatGPT Apps MCP Starter?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@ChatGPT Apps MCP Starter open the starter widget" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

ChatGPT Apps MCP Starter

by vikiival

Overview Schema Related Servers Score Discussions

TypeScript

Remote

ChatGPT Apps SDK Next.js Starter

A compact starter for building ChatGPT apps with Next.js, MCP tools, iframe widgets, and @openai/apps-sdk-ui.

This template is intentionally generic. It does not include auth, database, billing, or product-specific integrations. It focuses on the reusable foundation every ChatGPT app needs:

A Next.js app that can render in a normal browser and inside ChatGPT.
An MCP endpoint at /mcp.
MCP tools that return content, structuredContent, and widget metadata.
Widget resources served as text/html;profile=mcp-app for MCP Apps hosts.
A parallel text/html+skybridge resource for ChatGPT Apps SDK compatibility.
MCP Apps metadata plus OpenAI Apps SDK compatibility metadata.
A unified host bridge (HostProvider) that auto-detects ChatGPT's skybridge (window.openai) or a standards-based MCP Apps host (via @modelcontextprotocol/ext-apps and the ui/* postMessage protocol).
React hooks that work identically in ChatGPT, MCP Apps hosts (Claude, Goose, VS Code, ...), and a plain browser.
A sample widget built with @openai/apps-sdk-ui.

Quick Start

pnpm install
pnpm dev

Open:

http://localhost:3000

The MCP server is available at:

http://localhost:3000/mcp

Related MCP server: ChatGPT Apps SDK Next.js Starter

Scripts

pnpm dev          # Start local Next.js development server
pnpm run build   # Build the production app
pnpm start       # Start the production server after building
pnpm tsc --noEmit

Project Structure

app/
  apps-sdk-ui-provider.tsx  Client wrapper for AppsSDKUIProvider
  custom-page/page.tsx      Route/navigation example
  globals.css               Tailwind and Apps SDK UI CSS imports
  hooks/                    ChatGPT Apps SDK and MCP Apps bridge hooks
  layout.tsx                Root layout and iframe bootstrap
  mcp/route.ts              MCP server, widget resource, and tool registration
  page.tsx                  Main sample widget UI
baseUrl.ts                  App origin detection for local and Vercel deploys
next.config.ts              Asset prefix for iframe-safe Next.js assets
proxy.ts                    CORS headers for iframe/RSC requests

Architecture

The app has two halves:

MCP server: app/mcp/route.ts registers resources and tools. ChatGPT connects to this endpoint.
Widget UI: app/page.tsx is a normal Next.js route that is also returned as an MCP widget resource.

The flow is:

ChatGPT connects to /mcp.
The MCP server registers ui://widget/starter-widget.html.
ChatGPT calls a tool such as template_echo.
The tool returns structuredContent and metadata pointing to the widget resource.
ChatGPT fetches the widget HTML and renders it in an iframe.
The React widget reads tool output, display state, and host actions through the Apps SDK bridge.

MCP Apps Support

MCP Apps use a two-part registration:

A tool declares a UI resource in _meta.ui.resourceUri.
A ui:// resource returns HTML with the MCP Apps MIME type.

The standard MCP Apps resource in this template is:

{
  uri: "ui://widget/starter-widget.html",
  mimeType: "text/html;profile=mcp-app"
}

Tools point to it with nested MCP Apps metadata:

_meta: {
  ui: {
    resourceUri: "ui://widget/starter-widget.html",
    visibility: ["model", "app"],
  },
}

The template keeps the deprecated flat ui/resourceUri value as a migration aid, but new hosts should use _meta.ui.resourceUri.

Client-side host bridge

app/hooks/host-provider.tsx makes the widget work in every host. On mount it detects the environment:

window.openai exists → ChatGPT skybridge; hooks read window.openai.
Embedded in an iframe without window.openai → it connects through the official @modelcontextprotocol/ext-apps App class: the ui/initialize handshake, ui/notifications/tool-input / tool-result data push, host-context updates (theme, display mode, dimensions), and automatic ui/notifications/size-changed reporting.
Otherwise → standalone browser mode with graceful fallbacks.

The host theme is mirrored onto <html data-theme> in both host types, and useHost() exposes the detected flavor plus the raw App instance.

The MCP Apps ui.domain field is intentionally omitted. Hosts such as Claude assign their own sandbox content domain, and they can reject arbitrary app domains in this field. The app origin belongs in CSP allowlists and, for ChatGPT compatibility, in openai/widgetDomain.

ChatGPT Apps SDK Compatibility

ChatGPT Apps SDK compatibility is kept through a parallel Skybridge resource:

{
  uri: "ui://widget/starter-widget.skybridge.html",
  mimeType: "text/html+skybridge"
}

The same tool metadata also includes OpenAI compatibility fields:

"openai/outputTemplate": "ui://widget/starter-widget.skybridge.html"
"openai/toolInvocation/invoking": "Preparing the starter widget"
"openai/toolInvocation/invoked": "Starter widget ready"
"openai/widgetAccessible": true

This lets MCP Apps hosts render the standards-based resource while ChatGPT Apps SDK hosts can continue using the Skybridge resource.

Registered MCP Tools

`template_echo`

Renders the sample widget with structured content.

Input:

{
  name?: string;
  mode?: "overview" | "hooks" | "bridge";
}

Output:

{
  name: string;
  mode: "overview" | "hooks" | "bridge";
  message: string;
  timestamp: string;
}

This is the primary example tool. It demonstrates how a tool can return data that the iframe reads through useWidgetProps.

`template_update_preferences`

Demonstrates a widget-callable MCP tool.

Input:

{
  density?: "comfortable" | "compact";
  showBridgeHints?: boolean;
}

Output:

{
  preferences: {
    density: "comfortable" | "compact";
    showBridgeHints: boolean;
  };
  updatedAt: string;
}

The sample UI calls this from the Call sample tool button.

UI Kit Setup

The app imports the Apps SDK UI styles in app/globals.css:

@import "@openai/apps-sdk-ui/css";
@source "../node_modules/@openai/apps-sdk-ui";

The root layout wraps the app with AppsSDKUIProvider through app/apps-sdk-ui-provider.tsx, so package components work with Next.js routing.

Example imports:

import { Button } from "@openai/apps-sdk-ui/components/Button";
import { Badge } from "@openai/apps-sdk-ui/components/Badge";
import { Select } from "@openai/apps-sdk-ui/components/Select";

The visible UI in app/page.tsx is a demo of common Apps SDK host interactions.

Fullscreen Button

The icon button in the top-right asks ChatGPT to render the widget in fullscreen:

requestDisplayMode("fullscreen")

If the widget is already fullscreen, the button is hidden.

Name Input

The Name input updates local React state.

It does not call an MCP tool by itself. The current name is used by the Update context button when it sends context to the host.

Mode Select

The Mode select lets you choose:

Overview
Hooks
Bridge

Changing it updates local state and persists the selected mode through widget state:

setWidgetState({
  notes,
  localMode: nextMode,
})

The selected mode is used by Send follow-up and Update context.

Call Sample Tool

The Call sample tool button calls another MCP tool from inside the widget:

window.openai.callTool("template_update_preferences", {
  density: "compact",
  showBridgeHints: true,
})

It demonstrates widget-to-tool workflows. After the call, the widget updates the Last action line.

Send Follow-Up

The Send follow-up button sends a message into the ChatGPT conversation:

window.openai.sendFollowUpMessage({
  prompt: `Show me how to customize ${mode} mode.`
})

This behaves like the user typed a follow-up prompt.

Update Context

The Update context button sends model context through the MCP Apps bridge:

{
  method: "ui/update-model-context",
  params: {
    content: [{ type: "text", text: "..." }]
  }
}

The demo sends:

The starter widget is showing {mode} mode for {name}.

This is useful when the model should know about UI state without requiring a user message.

The Widget state textarea persists notes through:

window.openai.setWidgetState(...)

When the host bridge is available, widget state can survive widget lifecycle changes. Outside ChatGPT, the app still renders normally, but host persistence is unavailable.

Open Route Example

The Open route example button navigates to /custom-page.

This demonstrates that Next.js routing can work inside the widget iframe when the bootstrap and asset configuration are set correctly.

Open Docs

The Open docs button opens:

https://developers.openai.com/apps-sdk

It uses window.openai.openExternal when available so ChatGPT can handle external navigation correctly.

Hooks

The template exposes hooks from app/hooks.

Common hooks (all host-aware — they use window.openai in ChatGPT and the MCP Apps ui/* bridge elsewhere):

useHost exposes the detected host flavor, pushed tool data, host context, and the raw ext-apps App.
useWidgetProps reads tool structuredContent from the host.
useWidgetState reads and writes host-persisted widget state (ChatGPT only; local elsewhere).
useDisplayMode reads whether the widget is inline, fullscreen, or PiP.
useRequestDisplayMode asks the host to change display mode.
useCallTool calls MCP tools from the widget.
useSendMessage sends follow-up messages into the conversation.
useOpenExternal opens external URLs through the host.
useMcpBridge exposes raw MCP Apps methods such as ui/update-model-context.

Iframe Bootstrap

app/layout.tsx includes a small bootstrap script that helps Next.js behave inside the ChatGPT iframe.

It handles:

Setting a <base> tag for the app origin.
Detecting whether window.openai exists.
Rewriting client-side navigation history to avoid full-origin URLs.
Rewriting same-origin iframe fetches back to the app origin.
Opening external links through window.openai.openExternal when available.

Customizing The Template

Start with app/mcp/route.ts.

To add a new widget:

Add a new WidgetDefinition.
Create a Next.js page for the widget UI.
Register a resource with a stable URI such as ui://widget/orders.html.
Return mimeType: "text/html;profile=mcp-app" for MCP Apps hosts.
Optionally register a parallel text/html+skybridge resource for ChatGPT Apps SDK compatibility.
Register one or more tools that point to both resources through metadata.

To add a new tool:

Add server.registerTool(...).
Define a Zod inputSchema.
Return user-visible content.
Return machine-readable structuredContent.
Include tool metadata that points to the widget resource.

Keep tool outputs structured and typed. The widget should read data through useWidgetProps rather than parsing text.

Connecting To ChatGPT

Deploy the app to a public HTTPS URL, for example Vercel.
In ChatGPT, enable Developer Mode for apps.
Create an app.
Set the MCP server URL to:

https://your-domain.example/mcp

Call template_echo to render the starter widget.

baseUrl.ts derives the app origin in local development and Vercel deployments. If you deploy somewhere else, adapt that file to your hosting environment.

Verification

Run:

pnpm tsc --noEmit
pnpm run build

Useful local MCP smoke checks:

curl -i http://localhost:3000/mcp

Expected result: 405 Method Not Allowed. That means the MCP route exists, but a plain GET is not a valid MCP call.

List tools:

curl -i -X POST http://localhost:3000/mcp \
  -H 'Content-Type: application/json' \
  -H 'Accept: application/json, text/event-stream' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'

You should see template_echo and template_update_preferences.

Notes

The sample UI renders outside ChatGPT for local development.
Host actions such as callTool, sendFollowUpMessage, and setWidgetState require the ChatGPT/App host bridge.
The template keeps both MCP Apps metadata and OpenAI Apps SDK compatibility metadata so it can work across standards-based MCP Apps hosts and current ChatGPT app rendering behavior.

This server cannot be installed

license - not found

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

Need Help?

Related Servers

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly
Lightport: Open-Sourcing Glama's AI Gateway
By punkpeye on April 27, 2026.
OpenAI
open source
Tool Definition Quality Score (TDQS)
By punkpeye on April 3, 2026.
mcp

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vikiival/ai-sdk-mcp-app-starter'

If you have feedback or need assistance with the MCP directory API, please join our Discord server