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ChatGPT app with Next.js

Ship a ChatGPT app on Vercel with Next.js and Model Context Protocol (MCP).

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ChatGPT Apps SDK Next.js Starter

A minimal Next.js application demonstrating how to build an OpenAI Apps SDK compatible MCP server with widget rendering in ChatGPT.

Overview

This project shows how to integrate a Next.js application with the ChatGPT Apps SDK using the Model Context Protocol (MCP). It includes a working MCP server that exposes tools and resources that can be called from ChatGPT, with responses rendered natively in ChatGPT.

Key Components

1. MCP Server Route (app/mcp/route.ts)

The core MCP server implementation that exposes tools and resources to ChatGPT.

Key features:

  • Tool registration with OpenAI-specific metadata
  • Resource registration that serves HTML content for iframe rendering
  • Cross-linking between tools and resources via templateUri

OpenAI-specific metadata:

{
"openai/outputTemplate": widget.templateUri, // Links to resource
"openai/toolInvocation/invoking": "Loading...", // Loading state text
"openai/toolInvocation/invoked": "Loaded", // Completion state text
"openai/widgetAccessible": false, // Widget visibility
"openai/resultCanProduceWidget": true // Enable widget rendering
}

Full configuration options: OpenAI Apps SDK MCP Documentation

2. Asset Configuration (next.config.ts)

Critical: Set assetPrefix to ensure /_next/ static assets are fetched from the correct origin:

const nextConfig: NextConfig = {
assetPrefix: baseURL, // Prevents 404s on /_next/ files in iframe
};

Without this, Next.js will attempt to load assets from the iframe's URL, causing 404 errors.

3. CORS Middleware (middleware.ts)

Handles browser OPTIONS preflight requests required for cross-origin RSC (React Server Components) fetching during client-side navigation:

export function middleware(request: NextRequest) {
if (request.method === "OPTIONS") {
// Return 204 with CORS headers
}
// Add CORS headers to all responses
}

4. SDK Bootstrap (app/layout.tsx)

The <NextChatSDKBootstrap> component patches browser APIs to work correctly within the ChatGPT iframe:

What it patches:

  • history.pushState / history.replaceState - Prevents full-origin URLs in history
  • window.fetch - Rewrites same-origin requests to use the correct base URL
  • <html> attribute observer - Prevents ChatGPT from modifying the root element

Required configuration:

<html lang="en" suppressHydrationWarning>
<head>
<NextChatSDKBootstrap baseUrl={baseURL} />
</head>
<body>{children}</body>
</html>

Note: suppressHydrationWarning is currently required because ChatGPT modifies the initial HTML before the Next.js app hydrates, causing hydration mismatches.

Getting Started

Installation

npm install
# or
pnpm install

Development

npm run dev
# or
pnpm dev

Open http://localhost:3000 to see the app.

Testing the MCP Server

The MCP server is available at:

http://localhost:3000/mcp

Connecting from ChatGPT

  1. Deploy your app to Vercel
  2. In ChatGPT, navigate to Settings → Connectors → Create and add your MCP server URL with the /mcp path (e.g., https://your-app.vercel.app/mcp)

Note: Connecting MCP servers to ChatGPT requires developer mode access. See the connection guide for setup instructions.

Project Structure

app/
├── mcp/
│ └── route.ts # MCP server with tool/resource registration
├── layout.tsx # Root layout with SDK bootstrap
├── page.tsx # Homepage content
└── globals.css # Global styles
middleware.ts # CORS handling for RSC
next.config.ts # Asset prefix configuration

How It Works

  1. Tool Invocation: ChatGPT calls a tool registered in app/mcp/route.ts
  2. Resource Reference: Tool response includes templateUri pointing to a registered resource
  3. Widget Rendering: ChatGPT fetches the resource HTML and renders it in an iframe
  4. Client Hydration: Next.js hydrates the app inside the iframe with patched APIs
  5. Navigation: Client-side navigation uses patched fetch to load RSC payloads

Learn More

  • OpenAI Apps SDK Documentation
  • OpenAI Apps SDK - MCP Server Guide
  • Model Context Protocol
  • Next.js Documentation

Deployment

This project is designed to work seamlessly with Vercel deployment. The baseUrl.ts configuration automatically detects Vercel environment variables and sets the correct asset URLs.

The configuration automatically handles:

  • Production URLs via VERCEL_PROJECT_PRODUCTION_URL
  • Preview/branch URLs via VERCEL_BRANCH_URL
  • Asset prefixing for correct resource loading in iframes
GitHub
Ownervercel-labs
Repositorychatgpt-apps-sdk-nextjs-starter
Use Cases
Starter
AI
Stack
Next.js
None

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