ChatGPT App Builder

Build production-ready ChatGPT apps with interactive widgets using the mcp-use framework and OpenAI Apps SDK. This skill provides zero-config widget development with automatic registration and built-in React hooks.

Quick Start

Always bootstrap with the MCP Apps template:

npx create-mcp-use-app my-chatgpt-app --template mcp-apps
cd my-chatgpt-app
yarn install
yarn dev

This creates a project structure:

my-chatgpt-app/
├── resources/              # React widgets (auto-registered!)
│   ├── display-weather.tsx # Example widget
│   └── product-card.tsx    # Another widget
├── public/                 # Static assets
│   └── images/
├── index.ts               # MCP server entry
├── package.json
├── tsconfig.json
└── README.md

Why mcp-use for ChatGPT Apps?

Traditional OpenAI Apps SDK requires significant manual setup:

• Separate project structure (server/ and web/ folders)
• Manual esbuild/webpack configuration
• Custom useWidgetState hook implementation
• Manual React mounting code
• Manual CSP configuration
• Manual widget registration

mcp-use simplifies everything:

• Single command setup
• Drop widgets in

  resources/

  folder - auto-registered
• Built-in

  useWidget()

  hook with state, props, tool calls
• Automatic bundling with hot reload
• Automatic CSP configuration
• Built-in Inspector for testing
• Dual-protocol support (works with ChatGPT AND MCP Apps clients)

MCP Apps vs ChatGPT Apps SDK

mcp-use supports multiple widget protocols, giving you maximum compatibility:

type: "mcpApps"

type: "appsSdk"

Why MCP Apps?

MCP Apps is the official standard (SEP-1865) for interactive widgets in the Model Context Protocol:

• Universal: Works with ChatGPT, Claude Desktop, Goose, and all MCP Apps clients
• Future-proof: Based on open specification, ensuring long-term compatibility
• Secure: Double-iframe sandbox with granular CSP control
• Zero config: With

  type: "mcpApps"

  , mcp-use automatically generates metadata for BOTH protocols

Key Point: When you use

type: "mcpApps"

Creating Widgets

Simple Widget (Single File)

Create

resources/weather-display.tsx

import { McpUseProvider, useWidget, type WidgetMetadata } from "mcp-use/react";
import { z } from "zod";

// Define widget metadata
export const widgetMetadata: WidgetMetadata = {
  description: "Display current weather for a city",
  props: z.object({
    city: z.string().describe("City name"),
    temperature: z.number().describe("Temperature in Celsius"),
    conditions: z.string().describe("Weather conditions"),
    humidity: z.number().describe("Humidity percentage"),
  }),
};

const WeatherDisplay: React.FC = () => {
  const { props, isPending } = useWidget();

  // Always handle loading state first
  if (isPending) {
    return (
      <McpUseProvider autoSize>
        <div className="animate-pulse p-4">Loading weather...</div>
      </McpUseProvider>
    );
  }

  return (
    <McpUseProvider autoSize>
      <div className="weather-card p-4 rounded-lg shadow">
        <h2 className="text-2xl font-bold">{props.city}</h2>
        <div className="temp text-4xl">{props.temperature}°C</div>
        <p className="conditions">{props.conditions}</p>
        <p className="humidity">Humidity: {props.humidity}%</p>
      </div>
    </McpUseProvider>
  );
};

export default WeatherDisplay;

That's it! The widget is automatically:

• Registered as MCP tool

  weather-display

• Registered as MCP resource

  ui://widget/weather-display.html

• Bundled for Apps SDK compatibility
• Ready to use in ChatGPT

Complex Widget (Folder Structure)

For widgets with multiple components:

resources/
└── product-search/
    ├── widget.tsx          # Entry point (required name)
    ├── components/
    │   ├── ProductCard.tsx
    │   └── FilterBar.tsx
    ├── hooks/
    │   └── useFilter.ts
    ├── types.ts
    └── constants.ts

Entry point (

widget.tsx

import { McpUseProvider, useWidget, type WidgetMetadata } from "mcp-use/react";
import { z } from "zod";
import { ProductCard } from "./components/ProductCard";
import { FilterBar } from "./components/FilterBar";

export const widgetMetadata: WidgetMetadata = {
  description: "Display product search results with filtering",
  props: z.object({
    products: z.array(
      z.object({
        id: z.string(),
        name: z.string(),
        price: z.number(),
        image: z.string(),
      })
    ),
    query: z.string(),
  }),
};

const ProductSearch: React.FC = () => {
  const { props, isPending, state, setState } = useWidget();

  if (isPending) {
    return (
      <McpUseProvider autoSize>
        <div>Loading...</div>
      </McpUseProvider>
    );
  }

  return (
    <McpUseProvider autoSize>
      <div>
        <h1>Search: {props.query}</h1>
        <FilterBar onFilter={(filters) => setState({ filters })} />
        <div className="grid grid-cols-3 gap-4">
          {props.products.map((p) => (
            <ProductCard key={p.id} product={p} />
          ))}
        </div>
      </div>
    </McpUseProvider>
  );
};

export default ProductSearch;

Widget Metadata

Required metadata for automatic registration:

export const widgetMetadata: WidgetMetadata = {
  // Required: Human-readable description
  description: "Display weather information",

  // Required: Zod schema for widget props
  props: z.object({
    city: z.string().describe("City name"),
    temperature: z.number(),
  }),

  // Optional: Disable automatic tool registration
  exposeAsTool: true, // default

  // Optional: Unified metadata (works for BOTH ChatGPT and MCP Apps)
  metadata: {
    csp: {
      connectDomains: ["https://api.weather.com"],
      resourceDomains: ["https://cdn.weather.com"],
    },
    prefersBorder: true,
    autoResize: true,
    widgetDescription: "Interactive weather display",
  },
};

Important:

• description

  : Used for tool and resource descriptions

• props

  : Zod schema defines widget input parameters

• exposeAsTool

  : Set to

  false

  if only using widget via custom tools

• metadata

  : Unified configuration that works for both protocols (recommended)

Content Security Policy (CSP)

Control what external resources your widget can access using CSP configuration:

export const widgetMetadata: WidgetMetadata = {
  description: "Weather widget",
  props: z.object({ city: z.string() }),
  metadata: {
    csp: {
      // APIs your widget needs to call
      connectDomains: ["https://api.weather.com", "https://weather-backup.com"],

      // Static assets (images, fonts, stylesheets)
      resourceDomains: ["https://cdn.weather.com"],

      // External content to embed in iframes
      frameDomains: ["https://embed.weather.com"],

      // Script CSP directives (use carefully!)
      scriptDirectives: ["'unsafe-inline'"],
    },
  },
};

CSP Field Reference:

• connectDomains

  : APIs to call via fetch, WebSocket, XMLHttpRequest

• resourceDomains

  : Load images, fonts, stylesheets, videos

• frameDomains

  : Embed external content in iframes

• scriptDirectives

  : Script-src CSP directives (avoid

  'unsafe-eval'

  in production)

Security Best Practices:

• Specify exact domains:

  https://api.weather.com

• Avoid wildcards:

  https://*.weather.com

  (less secure)
• Never use

  'unsafe-eval'

  unless absolutely necessary
• Test CSP in development before deploying

Metadata Configuration Options

Modern Unified Approach (Recommended)

Use the

metadata

export const widgetMetadata: WidgetMetadata = {
  description: "Weather widget",
  props: propSchema,
  metadata: {
    // Works for BOTH MCP Apps AND ChatGPT
    csp: {
      connectDomains: ["https://api.weather.com"],
      resourceDomains: ["https://cdn.weather.com"],
    },
    prefersBorder: true,
    autoResize: true,
    widgetDescription: "Displays current weather",
  },
};

Legacy Apps SDK Approach (Deprecated)

The old ChatGPT-only format (still supported but not recommended):

export const widgetMetadata: WidgetMetadata = {
  description: "Weather widget",
  props: propSchema,
  appsSdkMetadata: {
    // ChatGPT only - snake_case with openai/ prefix
    "openai/widgetCSP": {
      connect_domains: ["https://api.weather.com"],
      resource_domains: ["https://cdn.weather.com"],
    },
    "openai/widgetPrefersBorder": true,
    "openai/toolInvocation/invoking": "Loading...",
    "openai/toolInvocation/invoked": "Loaded",
  },
};

Migration Note: The old format uses

appsSdkMetadata

openai/

connect_domains

metadata

connectDomains

Using Both for Custom ChatGPT Features

You can combine both fields to use standard metadata plus ChatGPT-specific overrides:

export const widgetMetadata: WidgetMetadata = {
  description: "Weather widget",
  props: propSchema,
  // Unified metadata (dual-protocol)
  metadata: {
    csp: { connectDomains: ["https://api.weather.com"] },
    prefersBorder: true,
  },
  // ChatGPT-specific overrides/additions
  appsSdkMetadata: {
    "openai/widgetDescription": "ChatGPT-specific description",
    "openai/customFeature": "some-value", // Any custom OpenAI metadata
    "openai/locale": "en-US",
  },
};

Use Case: When you need to pass custom OpenAI-specific metadata that doesn't exist in the unified format, add it to

appsSdkMetadata

openai/

useWidget Hook

The

useWidget

const {
  // Widget props from tool input
  props,

  // Loading state (true = tool still executing)
  isPending,

  // Persistent widget state
  state,
  setState,

  // Theme from host (light/dark)
  theme,

  // Call other MCP tools
  callTool,

  // Display mode control
  displayMode,
  requestDisplayMode,

  // Additional tool output
  output,
} = useWidget<MyPropsType, MyOutputType>();

Props and Loading States

Critical: Widgets render BEFORE tool execution completes. Always handle

isPending

const { props, isPending } = useWidget<WeatherProps>();

// Pattern 1: Early return
if (isPending) {
  return <div>Loading...</div>;
}
// Now props are safe to use

// Pattern 2: Conditional rendering
return <div>{isPending ? <LoadingSpinner /> : <div>{props.city}</div>}</div>;

// Pattern 3: Optional chaining (partial UI)
return (
  <div>
    <h1>{props.city ?? "Loading..."}</h1>
  </div>
);

Widget State

Persist data across widget interactions:

const { state, setState } = useWidget();

// Save state (persists in ChatGPT localStorage)
const addFavorite = async (city: string) => {
  await setState({
    favorites: [...(state?.favorites || []), city],
  });
};

// Update with function
await setState((prev) => ({
  ...prev,
  count: (prev?.count || 0) + 1,
}));

Calling MCP Tools

Widgets can call other tools:

const { callTool } = useWidget();

const refreshData = async () => {
  try {
    const result = await callTool("get-weather", {
      city: "Tokyo",
    });
    console.log("Result:", result.content);
  } catch (error) {
    console.error("Tool call failed:", error);
  }
};

Display Mode Control

Request different display modes:

const { displayMode, requestDisplayMode } = useWidget();

const goFullscreen = async () => {
  await requestDisplayMode("fullscreen");
};

// Current mode: 'inline' | 'pip' | 'fullscreen'
console.log(displayMode);

Custom Tools with Widgets

Create tools that return widgets with dual-protocol support:

import { MCPServer, widget, text } from "mcp-use/server";
import { z } from "zod";

const server = new MCPServer({
  name: "weather-app",
  version: "1.0.0",
});

server.tool(
  {
    name: "get-weather",
    description: "Get current weather for a city",
    schema: z.object({
      city: z.string().describe("City name"),
    }),
    // Widget config (registration-time metadata)
    widget: {
      name: "weather-display", // Must match widget in resources/
      invoking: "Fetching weather...",
      invoked: "Weather data loaded",
    },
  },
  async ({ city }) => {
    // Fetch data from API
    const data = await fetchWeatherAPI(city);

    // Return widget with runtime data
    return widget({
      props: {
        city,
        temperature: data.temp,
        conditions: data.conditions,
        humidity: data.humidity,
      },
      output: text(`Weather in ${city}: ${data.temp}°C`),
      message: `Current weather for ${city}`,
    });
  }
);

server.listen();

Key Points:

• baseUrl

  in server config enables proper asset loading
• Widget works with BOTH ChatGPT and MCP Apps clients automatically

• widget: { name, invoking, invoked }

  on tool definition

• widget({ props, output })

  helper returns runtime data

• props

  passed to widget,

  output

  shown to model
• Widget must exist in

  resources/

  folder

Static Assets

Use the

public/

my-app/
├── resources/
├── public/              # Static assets
│   ├── images/
│   │   ├── logo.svg
│   │   └── banner.png
│   └── fonts/
└── index.ts

Using assets in widgets:

import { Image } from "mcp-use/react";

function MyWidget() {
  return (
    <div>
      {/* Paths relative to public/ folder */}
      <Image src="/images/logo.svg" alt="Logo" />
      <img src={window.__getFile?.("images/banner.png")} alt="Banner" />
    </div>
  );
}

Components

McpUseProvider

Unified provider combining all common setup:

import { McpUseProvider } from "mcp-use/react";

function MyWidget() {
  return (
    <McpUseProvider
      autoSize // Auto-resize widget
      viewControls // Add debug/fullscreen buttons
      debug // Show debug info
    >
      <div>Widget content</div>
    </McpUseProvider>
  );
}

Image Component

Handles both data URLs and public paths:

import { Image } from "mcp-use/react";

function MyWidget() {
  return (
    <div>
      <Image src="/images/photo.jpg" alt="Photo" />
      <Image src="data:image/png;base64,..." alt="Data URL" />
    </div>
  );
}

ErrorBoundary

Graceful error handling:

import { ErrorBoundary } from "mcp-use/react";

function MyWidget() {
  return (
    <ErrorBoundary
      fallback={<div>Something went wrong</div>}
      onError={(error) => console.error(error)}
    >
      <MyComponent />
    </ErrorBoundary>
  );
}

Testing

Using the Inspector

1. Start development server:

   yarn dev
   

2. Open Inspector:

   • Navigate to

     http://localhost:3000/inspector

3. Test widgets:

   • Click Tools tab
   • Find your widget tool
   • Enter test parameters
   • Execute to see widget render

4. Debug interactions:

   • Use browser console
   • Check RPC logs
   • Test state persistence
   • Verify tool calls

Testing in ChatGPT

1. Enable Developer Mode:

   • Settings -> Connectors -> Advanced -> Developer mode

2. Add your server:

   • Go to Connectors tab
   • Add remote MCP server URL

3. Test in conversation:

   • Select Developer Mode from Plus menu
   • Choose your connector
   • Ask ChatGPT to use your tools

Prompting tips:

• Be explicit: "Use the weather-app connector's get-weather tool..."
• Disallow alternatives: "Do not use built-in tools, only use my connector"
• Specify input: "Call get-weather with { city: 'Tokyo' }"

Dual-Protocol Note: When using

type: "mcpApps"

Best Practices

Schema Design

Use descriptive schemas:

// Good
const schema = z.object({
  city: z.string().describe("City name (e.g., Tokyo, Paris)"),
  temperature: z.number().min(-50).max(60).describe("Temp in Celsius"),
});

// Bad
const schema = z.object({
  city: z.string(),
  temp: z.number(),
});

Theme Support

Always support both themes:

const { theme } = useWidget();

const bgColor = theme === "dark" ? "bg-gray-900" : "bg-white";
const textColor = theme === "dark" ? "text-white" : "text-gray-900";

Loading States

Always check

isPending

const { props, isPending } = useWidget<MyProps>();

if (isPending) {
  return <LoadingSpinner />;
}

// Now safe to access props.field
return <div>{props.field}</div>;

Widget Focus

Keep widgets focused:

// Good: Single purpose
export const widgetMetadata: WidgetMetadata = {
  description: "Display weather for a city",
  props: z.object({ city: z.string() }),
};

// Bad: Too many responsibilities
export const widgetMetadata: WidgetMetadata = {
  description: "Weather, forecast, map, news, and more",
  props: z.object({
    /* many fields */
  }),
};

Error Handling

Handle errors gracefully:

const { callTool } = useWidget();

const fetchData = async () => {
  try {
    const result = await callTool("fetch-data", { id: "123" });
    if (result.isError) {
      console.error("Tool returned error");
    }
  } catch (error) {
    console.error("Tool call failed:", error);
  }
};

Configuration

Production Setup

Set base URL for production:

const server = new MCPServer({
  name: "my-app",
  version: "1.0.0",
  baseUrl: process.env.MCP_URL || "https://myserver.com",
});

Environment Variables

# Server URL
MCP_URL=https://myserver.com

# For static deployments
MCP_SERVER_URL=https://myserver.com/api
CSP_URLS=https://cdn.example.com,https://api.example.com

Variable usage:

• MCP_URL

  : Base URL for widget assets and CSP

• MCP_SERVER_URL

  : MCP server URL for tool calls (static deployments)

• CSP_URLS

  : Additional domains for Content Security Policy

Deployment

Deploy to mcp-use Cloud

# Login
npx mcp-use login

# Deploy
yarn deploy

Build for Production

# Build
yarn build

# Start
yarn start

Build process:

• Compiles TypeScript
• Bundles React widgets
• Optimizes assets
• Generates production HTML

Common Patterns

Data Fetching Widget

const DataWidget: React.FC = () => {
  const { props, isPending, callTool } = useWidget();

  if (isPending) {
    return <div>Loading...</div>;
  }

  const refresh = async () => {
    await callTool("fetch-data", { id: props.id });
  };

  return (
    <div>
      <h1>{props.title}</h1>
      <button onClick={refresh}>Refresh</button>
    </div>
  );
};

Stateful Widget

const CounterWidget: React.FC = () => {
  const { state, setState } = useWidget();

  const increment = async () => {
    await setState({
      count: (state?.count || 0) + 1,
    });
  };

  return (
    <div>
      <p>Count: {state?.count || 0}</p>
      <button onClick={increment}>+1</button>
    </div>
  );
};

Themed Widget

const ThemedWidget: React.FC = () => {
  const { theme } = useWidget();

  return (
    <div className={theme === "dark" ? "dark-theme" : "light-theme"}>
      Content
    </div>
  );
};

Troubleshooting

Widget Not Appearing

Problem: Widget file exists but tool doesn't appear

Solutions:

• Ensure

  .tsx

  extension
• Export

  widgetMetadata

  object
• Export default React component
• Check server logs for errors
• Verify widget name matches file/folder name

Props Not Received

Problem: Component receives empty props

Solutions:

• Check

  isPending

  first (props empty while pending)
• Use

  useWidget()

  hook (not React props)
• Verify

  widgetMetadata.props

  is valid Zod schema
• Check tool parameters match schema

CSP Errors

Problem: Widget loads but assets fail

Solutions:

• Set

  baseUrl

  in server config
• Add domains to CSP via

  metadata.csp

  (modern) or

  appsSdkMetadata['openai/widgetCSP']

  (legacy)
• Use HTTPS for all resources
• Check browser console for CSP violations

CSP Errors in Production

Problem: Resources blocked by Content Security Policy in production

Solutions:

1. Check browser console for CSP violation messages
2. Add missing domains to your CSP configuration:

   metadata: {
     csp: {
       connectDomains: ['https://api.example.com'], // Add missing API domain
       resourceDomains: ['https://cdn.example.com'], // Add missing CDN domain
     }
   }
   

3. Use exact domains - avoid wildcards in production
4. Test in Inspector before deploying to catch CSP issues early
5. Environment variable alternative: Set

   CSP_URLS

   environment variable with comma-separated domains

Protocol Compatibility Issues

Problem: Widget works in ChatGPT but not MCP Apps clients (or vice versa)

Solutions:

• Use

  type: "mcpApps"

  for dual-protocol support (recommended)
• Check

  baseUrl

  is set correctly in server config
• Verify metadata format: Use

  metadata

  (camelCase) not

  appsSdkMetadata

  (snake_case) for dual-protocol
• Test in Inspector which supports both protocols

When to use each type:

• type: "mcpApps"

  - Maximum compatibility (recommended)

• type: "appsSdk"

  - ChatGPT only (use if you need ChatGPT-specific features not in spec)

Learn More

• Documentation: https://docs.mcp-use.com
• MCP Apps Standard: https://docs.mcp-use.com/typescript/server/mcp-apps (dual-protocol guide)
• Widget Guide: https://docs.mcp-use.com/typescript/server/ui-widgets
• Apps SDK Tutorial: https://docs.mcp-use.com/typescript/server/creating-apps-sdk-server
• Templates: https://docs.mcp-use.com/typescript/server/templates
• ChatGPT Apps Flow: https://docs.mcp-use.com/guides/chatgpt-apps-flow
• Inspector Debugging: https://docs.mcp-use.com/inspector/debugging-chatgpt-apps
• GitHub: https://github.com/mcp-use/mcp-use

Quick Reference

Commands:

• npx create-mcp-use-app my-app --template mcp-apps

  - Bootstrap

• yarn dev

  - Development with hot reload

• yarn build

  - Build for production

• yarn start

  - Run production server

• yarn deploy

  - Deploy to mcp-use Cloud

Widget structure:

• resources/widget-name.tsx

  - Single file widget

• resources/widget-name/widget.tsx

  - Folder-based widget entry

• public/

  - Static assets

Widget metadata:

• description

  - Widget description

• props

  - Zod schema for input

• exposeAsTool

  - Auto-register as tool (default: true)

• metadata

  - Unified config (dual-protocol, recommended)

• metadata.csp

  - Content Security Policy configuration

• appsSdkMetadata

  - ChatGPT-specific overrides (optional)

CSP fields:

• connectDomains

  - APIs to call

• resourceDomains

  - Static assets to load

• frameDomains

  - Iframes to embed

• scriptDirectives

  - Script policies

useWidget hook:

• props

  - Widget input parameters

• isPending

  - Loading state flag

• state, setState

  - Persistent state

• callTool

  - Call other tools

• theme

  - Current theme (light/dark)

• displayMode, requestDisplayMode

  - Display control