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openai-apps-mcp

by @jezwebv
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Specializes in AI engineering skills for OpenAI applications and MCP, supporting full-stack development with Claude Code CLI, especially skilled in Cloudflare integration to build and deploy intelligent applications.

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Installation
npx skills add jezweb/claude-skills --skill openai-apps-mcp
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Before / After Comparison

1 组
Before

When directly calling the OpenAI API, developers might only focus on core functionalities, overlooking production-grade considerations such as error handling, retry mechanisms, rate limiting, and cost management. This can lead to unstable applications or uncontrolled costs in actual operation.

After

With OpenAI Apps MCP skills, you can gain best practices for building production-grade OpenAI applications. This includes using appropriate client libraries, implementing elegant error handling and retry logic, managing API key security, and monitoring token usage, ensuring applications are both reliable and efficient.

SKILL.md

openai-apps-mcp

Building OpenAI Apps with Stateless MCP Servers

Status: Production Ready Last Updated: 2026-01-21 Dependencies: cloudflare-worker-base, hono-routing (optional) Latest Versions: @modelcontextprotocol/sdk@1.25.3, hono@4.11.3, zod@4.3.5, wrangler@4.58.0

Overview

Build ChatGPT Apps using MCP (Model Context Protocol) servers on Cloudflare Workers. Extends ChatGPT with custom tools and interactive widgets (HTML/JS UI rendered in iframe).

Architecture: ChatGPT → MCP endpoint (JSON-RPC 2.0) → Tool handlers → Widget resources (HTML)

Status: Apps available to Business/Enterprise/Edu (GA Nov 13, 2025). MCP Apps Extension (SEP-1865) formalized Nov 21, 2025.

Quick Start

1. Scaffold & Install

npm create cloudflare@latest my-openai-app -- --type hello-world --ts --git --deploy false
cd my-openai-app
npm install @modelcontextprotocol/sdk@1.25.3 hono@4.11.3 zod@4.3.5
npm install -D @cloudflare/vite-plugin@1.17.1 vite@7.2.4

2. Configure wrangler.jsonc

{
  "name": "my-openai-app",
  "main": "dist/index.js",
  "compatibility_flags": ["nodejs_compat"],  // Required for MCP SDK
  "assets": {
    "directory": "dist/client",
    "binding": "ASSETS"  // Must match TypeScript
  }
}

3. Create MCP Server (src/index.ts)

import { Hono } from 'hono';
import { cors } from 'hono/cors';
import { Server } from '@modelcontextprotocol/sdk/server/index.js';
import { ListToolsRequestSchema, CallToolRequestSchema } from '@modelcontextprotocol/sdk/types.js';

const app = new Hono<{ Bindings: { ASSETS: Fetcher } }>();

// CRITICAL: Must allow chatgpt.com
app.use('/mcp/*', cors({ origin: 'https://chatgpt.com' }));

const mcpServer = new Server(
  { name: 'my-app', version: '1.0.0' },
  { capabilities: { tools: {}, resources: {} } }
);

// Tool registration
mcpServer.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [{
    name: 'hello',
    description: 'Use this when user wants to see a greeting',
    inputSchema: {
      type: 'object',
      properties: { name: { type: 'string' } },
      required: ['name']
    },
    annotations: {
      openai: { outputTemplate: 'ui://widget/hello.html' }  // Widget URI
    }
  }]
}));

// Tool execution
mcpServer.setRequestHandler(CallToolRequestSchema, async (request) => {
  if (request.params.name === 'hello') {
    const { name } = request.params.arguments as { name: string };
    return {
      content: [{ type: 'text', text: `Hello, ${name}!` }],
      _meta: { initialData: { name } }  // Passed to widget
    };
  }
  throw new Error(`Unknown tool: ${request.params.name}`);
});

app.post('/mcp', async (c) => {
  const body = await c.req.json();
  const response = await mcpServer.handleRequest(body);
  return c.json(response);
});

app.get('/widgets/*', async (c) => c.env.ASSETS.fetch(c.req.raw));

export default app;

4. Create Widget (src/widgets/hello.html)

<!DOCTYPE html>
<html>
<head>
  <style>
    body { margin: 0; padding: 20px; font-family: system-ui; }
  </style>
</head>
<body>
  <div id="greeting">Loading...</div>
  <script>
    if (window.openai && window.openai.getInitialData) {
      const data = window.openai.getInitialData();
      document.getElementById('greeting').textContent = `Hello, ${data.name}! 👋`;
    }
  </script>
</body>
</html>

5. Deploy

npm run build
npx wrangler deploy
npx @modelcontextprotocol/inspector https://my-app.workers.dev/mcp

Critical Requirements

CORS: Must allow https://chatgpt.com on /mcp/* routes Widget URI: Must use ui://widget/ prefix (e.g., ui://widget/map.html) MIME Type: Must be text/html+skybridge for HTML resources Widget Data: Pass via _meta.initialData (accessed via window.openai.getInitialData()) Tool Descriptions: Action-oriented ("Use this when user wants to...") ASSETS Binding: Serve widgets from ASSETS, not bundled in worker code SSE: Send heartbeat every 30s (100s timeout on Workers)

Known Issues Prevention

This skill prevents 14 documented issues:

Issue #1: CORS Policy Blocks MCP Endpoint

Error: Access to fetch blocked by CORS policy Fix: app.use('/mcp/*', cors({ origin: 'https://chatgpt.com' }))

Issue #2: Widget Returns 404 Not Found

Error: 404 (Not Found) for widget URL Fix: Use ui://widget/ prefix (not resource:// or /widgets/)

annotations: { openai: { outputTemplate: 'ui://widget/map.html' } }

Issue #3: Widget Displays as Plain Text

Error: HTML source code visible instead of rendered widget Fix: MIME type must be text/html+skybridge (not text/html)

server.setRequestHandler(ListResourcesRequestSchema, async () => ({
  resources: [{ uri: 'ui://widget/map.html', mimeType: 'text/html+skybridge' }]
}));

Issue #4: ASSETS Binding Undefined

Error: TypeError: Cannot read property 'fetch' of undefined Fix: Binding name in wrangler.jsonc must match TypeScript

{ "assets": { "binding": "ASSETS" } }  // wrangler.jsonc


type Bindings = { ASSETS: Fetcher };  // index.ts

Issue #5: SSE Connection Drops After 100 Seconds

Error: SSE stream closes unexpectedly Fix: Send heartbeat every 30s (Workers timeout at 100s inactivity)

const heartbeat = setInterval(async () => {
  await stream.writeSSE({ data: JSON.stringify({ type: 'heartbeat' }), event: 'ping' });
}, 30000);

Issue #6: ChatGPT Doesn't Suggest Tool

Error: Tool registered but never appears in suggestions Fix: Use action-oriented descriptions

// ✅ Good: 'Use this when user wants to see a location on a map'
// ❌ Bad: 'Shows a map'

Issue #7: Widget Can't Access Initial Data

Error: window.openai.getInitialData() returns undefined Fix: Pass data via _meta.initialData

return {
  content: [{ type: 'text', text: 'Here is your map' }],
  _meta: { initialData: { location: 'SF', zoom: 12 } }
};

Issue #8: Widget Scripts Blocked by CSP

Error: Refused to load script (CSP directive) Fix: Use inline scripts or same-origin scripts. Third-party CDNs blocked.

<!-- ✅ Works --> <script>console.log('ok');</script>
<!-- ❌ Blocked --> <script src="https://cdn.example.com/lib.js"></script>

Issue #9: Hono Global Response Override Breaks Next.js (v1.25.0-1.25.2)

Error: No response is returned from route handler (Next.js App Router) Source: GitHub Issue #1369 Affected Versions: v1.25.0 to v1.25.2 Fixed In: v1.25.3 Why It Happens: Hono (MCP SDK dependency) overwrites global.Response, breaking frameworks that extend it (Next.js, Remix, SvelteKit). NextResponse instanceof check fails. Prevention:

  • Upgrade to v1.25.3+ (recommended)

  • Before fix: Use webStandardStreamableHTTPServerTransport instead

  • Or: Run MCP server on separate port from Next.js/Remix/SvelteKit app

// ✅ v1.25.3+ - Fixed
const transport = new StreamableHTTPServerTransport({
  sessionIdGenerator: undefined,
});

// ✅ v1.25.0-1.25.2 - Workaround
import { webStandardStreamableHTTPServerTransport } from '@modelcontextprotocol/sdk/server/index.js';
const transport = webStandardStreamableHTTPServerTransport({
  sessionIdGenerator: undefined,
});

Issue #10: Elicitation (User Input) Fails on Cloudflare Workers

Error: EvalError: Code generation from strings disallowed Source: GitHub Issue #689 Why It Happens: Internal AJV v6 validator uses prohibited APIs on edge platforms Prevention: Avoid elicitInput() on edge platforms (Cloudflare Workers, Vercel Edge, Deno Deploy)

Workaround:

// ❌ Don't use on Cloudflare Workers
const userInput = await server.elicitInput({
  prompt: "What is your name?",
  schema: { type: "string" }
});

// ✅ Use tool parameters instead
server.setRequestHandler(CallToolRequestSchema, async (request) => {
  const { name } = request.params.arguments as { name: string };
  // User provides via tool call, not elicitation
});

Status: Requires MCP SDK v2 to fix properly. Track PR #844.

Issue #11: SSE Transport Statefulness Breaks Serverless Deployments

Error: 400: No transport found for sessionId Source: GitHub Issue #273 Why It Happens: SSEServerTransport relies on in-memory session storage. In serverless environments (AWS Lambda, Cloudflare Workers), the initial GET /sse request may be handled by Instance A, but subsequent POST /messages requests land on Instance B, which lacks the in-memory state. Prevention: Use Streamable HTTP transport (added in v1.24.0) instead of SSE for serverless deployments Solution: For stateful SSE, deploy to non-serverless environments (VPS, long-running containers)

Official Status: Fixed by introducing Streamable HTTP (v1.24+) - now the recommended standard for serverless.

Issue #12: OAuth Configuration Requires TWO Separate Apps

Source: Cloudflare Remote MCP Server Docs Why It Happens: OAuth providers validate redirect URLs strictly. Localhost and production have different URLs, so they need separate OAuth client registrations. Prevention:

# Development OAuth App
Callback URL: http://localhost:8788/callback

# Production OAuth App
Callback URL: https://my-mcp-server.workers.dev/callback

Additional Requirements:

  • KV namespace for auth state storage (create manually)

  • COOKIE_ENCRYPTION_KEY env var: openssl rand -hex 32

  • Client restart required after config changes

Issue #13: Widget State Over 4k Tokens Causes Performance Issues (Community-sourced)

Source: OpenAI Apps SDK - ChatGPT UI Why It Happens: Widget state persists only to a single widget instance tied to one conversation message. State is reset when users submit via the main chat composer instead of widget controls. Prevention: Keep state payloads under 4k tokens for optimal performance

// ✅ Good - Lightweight state
window.openai.setWidgetState({ selectedId: "item-123", view: "grid" });

// ❌ Bad - Will cause performance issues
window.openai.setWidgetState({
  items: largeArray,           // Don't store full datasets
  history: conversationLog,    // Don't store conversation history
  cache: expensiveComputation  // Don't cache large results
});

Best Practice:

  • Store only UI state (selected items, view mode, filters)

  • Fetch data from MCP server on widget mount

  • Use tool calls to persist important data

Issue #14: Widget-Initiated Tool Calls Fail Without Permission Flag (Community-sourced)

Source: OpenAI Apps SDK - ChatGPT UI Why It Happens: Components initiating tool calls via window.openai.callTool() require the tool marked as "able to be initiated by the component" on the MCP server. Without this flag, calls fail silently. Prevention: Mark tools as widgetCallable: true in annotations

// MCP Server - Mark tool as widget-callable
server.setRequestHandler(ListToolsRequestSchema, async () => ({
  tools: [{
    name: 'update_item',
    description: 'Update an item',
    inputSchema: { /* ... */ },
    annotations: {
      openai: {
        outputTemplate: 'ui://widget/item.html',
        // ✅ Required for widget-initiated calls
        widgetCallable: true
      }
    }
  }]
}));

// Widget - Now allowed to call tool
window.openai.callTool({
  name: 'update_item',
  arguments: { id: itemId, status: 'completed' }
});

Widget Development Best Practices

File Upload Limitations (Community-sourced)

Source: OpenAI Apps SDK - ChatGPT UI

window.openai.uploadFile() only supports 3 image formats: image/png, image/jpeg, and image/webp. Other formats fail silently.

// ✅ Supported
window.openai.uploadFile({ accept: 'image/png,image/jpeg,image/webp' });

// ❌ Not supported (fails silently)
window.openai.uploadFile({ accept: 'application/pdf' });
window.openai.uploadFile({ accept: 'text/csv' });

Alternative for Other File Types:

  • Use base64 encoding in tool arguments

  • Request user paste text content

  • Use external upload service (S3, R2) and pass URL

Tool Performance Targets (Community-sourced)

Source: OpenAI Apps SDK - Troubleshooting

Tool calls exceeding "a few hundred milliseconds" cause UI sluggishness in ChatGPT. Official docs recommend profiling backends and implementing caching for slow operations.

Performance Targets:

  • < 200ms: Ideal response time

  • 200-500ms: Acceptable but noticeable

  • > 500ms: Sluggish, needs optimization

Optimization Strategies:

// 1. Cache expensive computations
const cache = new Map();
if (cache.has(key)) return cache.get(key);
const result = await expensiveOperation();
cache.set(key, result);

// 2. Use KV/D1 for pre-computed data
const cached = await env.KV.get(`result:${id}`);
if (cached) return JSON.parse(cached);

// 3. Paginate large datasets
return {
  content: [{ type: 'text', text: 'First 20 results...' }],
  _meta: { hasMore: true, nextPage: 2 }
};

// 4. Move slow work to async tasks
// Return immediately, update via follow-up

MCP SDK 1.25.x Updates (December 2025)

Breaking Changes from @modelcontextprotocol/sdk@1.24.x → 1.25.x:

  • Removed loose type exports (Prompts, Resources, Roots, Sampling, Tools) - use specific schemas

  • ES2020 target required (previous: ES2018)

  • setRequestHandler is now typesafe - incorrect schemas throw type errors

New Features:

  • Tasks (v1.24.0+): Long-running operations with progress tracking

  • Sampling with Tools (v1.24.0+): Tools can request model sampling

  • OAuth Client Credentials (M2M): Machine-to-machine authentication

Migration: If using loose type imports, update to specific schema imports:

// ❌ Old (removed in 1.25.0)
import { Tools } from '@modelcontextprotocol/sdk/types.js';

// ✅ New (1.25.1+)
import { ListToolsRequestSchema, CallToolRequestSchema } from '@modelcontextprotocol/sdk/types.js';

Zod 4.0 Migration Notes (MAJOR UPDATE - July 2025)

Breaking Changes from zod@3.x → 4.x:

  • .default() now expects input type (not output type). Use .prefault() for old behavior.

  • ZodError: error.issues (not error.errors)

  • .merge() and .superRefine() deprecated

  • Optional properties with defaults now always apply

...

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Rating4.3 / 5.0
Version
Updated2026年5月17日
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Compatible Platforms

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Timeline

Created2026年3月17日
Last Updated2026年5月17日