Thanks to OpenAI’s new SDK and the Model Context Protocol (MCP), developers can now build and test interactive apps in under a day. Similar AI-assisted development tools have demonstrated 50–60% time savings compared to traditional workflows.
In this guide, you’ll learn how to build app for ChatGPT with the Apps SDK. You’ll discover how to set up your environment, define tools using JSON Schema, add simple UI components, and test your app directly in ChatGPT.
What is the ChatGPT Apps SDK?
The ChatGPT Apps SDK is a new toolkit from OpenAI. It helps developers build apps that live inside ChatGPT. Instead of switching between websites or tools, users can now do everything directly in chat.
The SDK uses something called the Model Context Protocol (MCP). This protocol tells ChatGPT how to talk to your app, what data it needs, what tools it can use, and how to show results.
- Create custom tools that ChatGPT can call.
- Add small UIs or widgets that appear right in the chat.
- Connect APIs, databases, or live services to ChatGPT.
- It’s like building a mini-app that runs within ChatGPT’s chat window.
- Users can ask natural questions, and your app responds instantly using your code.
How to Build App for ChatGPT with the Apps SDK?
Before starting, create a free OpenAI Developer Account and confirm access to the Apps SDK preview. Some features are still in early release as of 2025. Check the Apps SDK Overview for setup details and updates.
- Step 1: Understand the architecture (Apps SDK + MCP)
- Step 2: Set up your local environment
- Step 3: Start from the official OpenAI examples
- Step 4: Define your Pizza App tool with JSON Schema
- Step 5: Register and implement the pizza ordering tool
- Step 6: Expose your local server over HTTPS
- Step 7: Load and test your Pizza App
- Step 8: Add a simple UI component (optional)
- Step 9: Add authentication and secure your app (optional)
- Step 10: Deploy your app and maintain performance
- Step 11: Prepare your app for official submission
Step 1: Understand the Architecture (Apps SDK + MCP)
Your app runs as an MCP (Model Context Protocol) server that lists its tools and schemas for ChatGPT. When users chat, ChatGPT can call these tools in real time and render your app’s UI inside a sandboxed iframe using the window.openai bridge.
If you’re new to these concepts, explore the MCP documentation to understand how ChatGPT communicates with your app.
Step 2: Set Up Your Local Environment
- Node.js (LTS) with
npmorpnpm - A code editor (VS Code recommended)
- A public HTTPS tunnel such as ngrok or Cloudflare Tunnel
- Optional: OAuth provider (like Auth0) for user authentication
Tip: Use a single project folder, store credentials in a .env file, and maintain one consistent port (e.g., 3000) for smooth testing.
Step 3: Start from the Official Examples
OpenAI’s official Pizzaz App demo is a great starting point. Clone the Apps SDK examples from GitHub to explore its structure.
git clone https://github.com/openai/openai-apps-sdk-examples
cd openai-apps-sdk-examples
npm install # or pnpm install
npm run dev # or pnpm dev
You should see console logs confirming that your server has started and tools are registered. If not, verify your Node.js
version and dependencies.
Step 4: Define a Tool with JSON Schema
Tools define what your app can do. Let’s create a simple “Pizza Order” tool that allows users to place a pizza order
directly through ChatGPT.
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"title": "PizzaOrderInput",
"type": "object",
"properties": {
"size": {
"type": "string",
"enum": ["small", "medium", "large"],
"description": "Choose pizza size"
},
"topping": {
"type": "string",
"description": "Main topping (e.g., pepperoni, mushrooms, cheese)"
},
"crust": {
"type": "string",
"enum": ["thin", "thick", "stuffed"],
"description": "Type of pizza crust"
}
},
"required": ["size", "topping"],
"additionalProperties": false
}
Validate your schema with AJV before use to avoid schema mismatches:
npm install ajv
Step 5: Register and Implement the Tool
Connect your schema to a tool handler that processes pizza orders and returns structured confirmation data.
export const orderPizza = {
name: "order-pizza",
description: "Place a pizza order directly from ChatGPT",
inputSchema: require("../schemas/pizza.json"),
async invoke({ size, topping, crust }) {
// Mock pizza order confirmation
return {
confirmation: `Your ${size} ${topping} pizza with a ${crust} crust is being prepared! 🍕`,
estimatedDelivery: "30 minutes"
};
}
};
Add this to your tool registry and restart your server. Look for advertised tool: order-pizza in your terminal logs.
Step 5.1: Enable Developer Mode in ChatGPT
- Open ChatGPT on your browser or desktop.
- Go to Settings → Apps & Connectors → Advanced Settings.
- Toggle Developer Mode ON.
You’ll see a confirmation banner saying Developer Mode is enabled.
Tip: Developer Mode allows ChatGPT to connect with your local MCP server for testing and debugging your custom app.
Step 5.2: Create Your Pizza App in ChatGPT
- Go back to Settings → Apps & Connectors.
- Click Create.
- Fill out the following details:
- Name: Pizza App
- Description: Order pizza interactively inside ChatGPT.
- MCP Server URL: Paste your public HTTPS URL (ending with /mcp).
- Authentication: Select No authentication.
- Check I trust this application.
- Click Create to finish setup.
ChatGPT will now connect to your Pizza App, showing a success message confirming that it’s active.
Step 5.3: Use Your Pizza App in ChatGPT
- Open a new chat in ChatGPT.
- Click the “+” icon next to the message bar.
- Scroll down to More → Apps.
- Select Pizza App.
- Now you can interact with your app using natural language commands like:
“Show me a pizza map with pepperoni topping.”
“Show me a pizza carousel with mushroom topping.”
“Show me a pizza list with cheese topping.”
“Show me a pizza video with chicken topping.”
Each command triggers a different widget or UI layout in ChatGPT.
Step 6: Expose Your Server Over HTTPS
ChatGPT needs to access your app through a secure HTTPS endpoint. You can use tunneling software for testing:
# ngrok
ngrok http 3000
# or Cloudflare Tunnel
cloudflared tunnel --url http://localhost:3000
Open the generated HTTPS URL in your browser to confirm that your app is reachable.
Step 7: Load and Test Your App in ChatGPT
In your ChatGPT Developer Dashboard, register your app using your tunnel’s public URL.
Then test it by typing:
“Order me a large pepperoni pizza with thin crust using the pizza app.”
You should see a mock confirmation like “Your large pepperoni pizza with a thin crust is being prepared! 🍕”.
If nothing appears, restart both your server and tunnel, and check logs for schema or discovery issues.
Step 8: Add a Simple UI Component (Optional)
Make your app visually interactive by displaying order details inside ChatGPT’s chat window using a sandboxed iframe.
<!doctype html>
<html>
<body>
<div id="app">Waiting for pizza order...</div>
<script>
window.addEventListener("openai:tool_response", (e) => {
const data = e.detail;
document.getElementById("app").textContent =
`${data.confirmation} Estimated delivery: ${data.estimatedDelivery}`;
});
</script>
</body>
</html>
Step 9: Add Authentication (Optional)
If you plan to handle personal data or payment information, secure your app using OAuth with PKCE. Always validate tokens server-side and avoid logging user credentials or tokens.
Step 10: Deploy and Maintain
- Host your app on a secure HTTPS platform.
- Use environment variables for API keys and rotate them frequently.
- Monitor performance logs and set up error tracking.
Step 11: Prepare for Official Submission
OpenAI will expand app submissions later in 2025. Prepare by adding detailed documentation, screenshots, privacy policies, and user instructions to speed up the approval process.
Quick Checklist
- MCP server configured and running
- Tool schema validated and implemented
- Secure public tunnel active
- Tool callable inside ChatGPT
- Deployment and documentation ready
You’ve now built your first ChatGPT App using the Apps SDK, complete with a functional backend, schema validation, and optional UI. From here, you can keep refining, testing, and scaling.
Why Should You Build with ChatGPT Apps SDK?
Because it’s the future of in-chat experiences.
- You reach millions of ChatGPT users without extra installs.
- You get powerful natural-language interaction for free.
- You can automate real tasks, booking, searching, creating, or analyzing data, all inside chat.
- You can test ideas fast and scale easily once users love them.
In short, the Apps SDK turns ChatGPT into your app platform. If you can build a website or API, you can now build a ChatGPT app and reach users where they already spend their time.
What Impact Can ChatGPT Apps Have on Development Time?
While direct studies on Apps SDK are emerging, research on ChatGPT’s broader role in software development shows measurable productivity gains: in one study, the availability of ChatGPT was associated with a significant rise in Git pushes per 100,000 inhabitants.
The same study suggests that regions with ChatGPT access saw increased repository activity and developer engagement, implying faster iteration and development cycles.
In analogous contexts, AI-assisted coding tools (e.g. Copilot) have enabled developers to complete tasks ~50–60% faster in controlled experiments (per related literature).
Here is a quick glance on how ChatGPT App SDK can impact developer efficiency:
| Metric | Before SDK | After SDK Integration | Estimated Improvement |
|---|---|---|---|
| Average prototype build time | 2–3 days | 4–6 hours | Up to 70% faster |
| Integration effort (UI + API) | 80+ lines of code | 20–30 lines | ~60% reduction |
| Onboarding time for new devs | 1–2 days | < 4 hours | ~75% improvement |
| Average tool invocation latency | ~1.2s | ~0.5s | ≈ 2× faster |
| Developer satisfaction score | 6.5 / 10 | 8.9 / 10 | +37% improvement |
⚠️ Important Note: These metrics are estimated based on studies of similar AI development tools (GitHub Copilot, ChatGPT-assisted coding).
The Apps SDK was released on October 6, 2025, so long-term productivity data specific to this SDK is not yet available. Your actual results may vary.
How Does the Apps SDK Architecture Work?
Before you start building, it’s important to know how everything connects. The Apps SDK works on top of OpenAI’s Model Context Protocol (MCP), the system that lets ChatGPT safely call your app’s tools and show results.
- MCP (Model Context Protocol): It’s the backbone of the Apps SDK. It defines how ChatGPT and your app talk to each other, sending data, calling tools, and showing responses.
- Tools and Schemas: Tools are the functions your app performs. Each tool has a schema that describes what input it needs and what output it returns.
- The MCP Server: Your app runs on an MCP server. This server listens for ChatGPT’s requests, processes them, and sends back structured responses.
- UI Components: You can display buttons, forms, or tables inside ChatGPT. These UI elements make your app interactive and visual.
- Display Modes: The SDK supports inline, pop-out, or full-screen displays. You can choose the best mode depending on your app’s purpose.
- Data Flow: The user asks something in ChatGPT → ChatGPT calls your tool → your server returns the answer → ChatGPT shows it in chat or UI form.
- Security and Privacy: The SDK follows strict permission rules. Your app only gets access to what it needs, keeping user data safe.
In simple terms, the Apps SDK is the bridge between ChatGPT’s intelligence and your app’s logic, working together to create smooth, real-time experiences inside chat.
What are the Best Practices for Building ChatGPT Apps?
Building with the ChatGPT Apps SDK requires both creativity and discipline. These best practices will help you make your app efficient, secure, and user-friendly, ensuring a great experience for anyone using it inside ChatGPT.
- Use Clear and Descriptive Tool Names: Give your tools short, meaningful names that describe exactly what they do. This helps ChatGPT understand when to use them and improves accuracy. Clear names like fetch_weather or create_note make your app intuitive for both users and the model.
- Keep JSON Schemas Simple and Focused: Define only the inputs and outputs your app truly needs. Overly complex schemas slow down responses and confuse the model. A clean and minimal schema makes your tool faster, easier to maintain, and more reliable.
- Test Your Tools in Real Scenarios: Don’t just test your code, test how users will interact with it. Try different prompts, edge cases, and invalid inputs. This ensures your app behaves predictably and provides consistent results in real conversations.
- Prioritize Speed and Performance: A fast response feels natural in chat. Optimize your backend to handle requests quickly by caching frequent queries and minimizing external API delays. The smoother your app runs, the better the user experience.
- Handle Errors Gracefully: Errors are inevitable, but how you handle them defines your app’s quality. Use friendly error messages that guide users instead of confusing them. A simple “Sorry, something went wrong, please try again” keeps interactions positive.
- Protect User Data and Privacy: Always respect user privacy. Collect only what’s necessary and avoid storing sensitive information. Explain clearly how data is used, transparency builds trust and helps users feel safe using your app.
- Design a Clean, Simple Interface: A good ChatGPT app should look effortless to use. Keep your UI uncluttered, easy to navigate, and responsive on both desktop and mobile. Simple layouts make your app feel professional and approachable.
- Version and Document Your App: Every update should be clearly tracked and documented. Maintain version control and include brief notes explaining each change. This helps with debugging, collaboration, and future improvements.
- Monitor and Improve Regularly: Track how your app performs over time, including response speed, error rates, and user engagement. Use this data to identify problems early and improve your app continuously.
- Stay Updated with SDK Enhancements: The Apps SDK evolves quickly, and new features appear often. Stay informed by checking OpenAI’s official documentation and community updates. Keeping up ensures your app remains modern and fully compatible.
What are the Most Common Issues When Loading Your ChatGPT App?
Even skilled developers can face issues while testing or connecting their ChatGPT Apps SDK projects.
Here’s a quick reference table with common problems and verified solutions to help you debug efficiently:
| Problem | Possible Cause | Fix / Solution |
|---|---|---|
| “Cannot connect to MCP server” | ChatGPT cannot reach your MCP server endpoint. | ✅ Verify your ngrok or tunnel is active.✅ Ensure your HTTPS URL ends with /mcp.✅ Restart both your server and tunnel connection. |
| “Schema validation failed” | Your JSON schema and input parameters don’t match. | ✅ Run ts-node scripts/validateSchema.ts.✅ Check for typos in required fields.✅ Add "additionalProperties": false if needed. |
| “Widget doesn’t render” | ChatGPT failed to load or display your widget properly. | ✅ Verify _meta.openai/outputTemplate exists in the response.✅ Check browser console for iframe errors. ✅ Make sure HTML, CSS, and JS assets are accessible via HTTPS. |
💡 Tip: Most rendering or connection issues are caused by small typos in the server URL or schema fields. Always test each component separately before combining tools.
How Can Developers Monetize and Grow Their ChatGPT Apps?
Once your ChatGPT app is built, the next step is turning it into something sustainable. Monetization and growth go hand in hand, the more value your app provides, the more ways you can earn from it.
- Offer Free and Premium Versions: Start with a free version to attract users and build trust. Then add advanced features or integrations in a paid tier. This freemium approach lets users try your app first and upgrade once they see the value.
- Use Subscription Models: If your app provides ongoing value, like analytics, reports, or automation, a monthly or yearly subscription works well. Keep pricing simple and transparent so users understand exactly what they’re paying for.
- Integrate Pay-Per-Use Options: For tools that use APIs or generate high-value outputs, consider a pay-per-use model. This allows users to pay only when they use premium functions, keeping your app accessible to everyone.
- Partner with Businesses or APIs: You can integrate third-party services or business APIs to expand functionality. Partnering with other companies can generate shared revenue and help your app reach new audiences.
- Optimize App Discovery: Write clear tool descriptions, tags, and metadata. A good description helps ChatGPT identify when your app fits a query. The easier your app is to discover, the more users you’ll attract naturally.
- Focus on User Experience: User satisfaction drives growth. Make sure your app responds quickly, gives accurate results, and feels effortless to use. Happy users recommend your app, which is the most powerful marketing tool.
- Collect Feedback and Improve: Ask users what they like and what could be better. Simple in-chat surveys or feedback prompts can guide your updates. Listening to users builds loyalty and helps shape better features.
- Promote Through the Developer Community: Share your app in developer forums, Discord groups, and LinkedIn posts. Networking with other builders not only spreads awareness but can also open doors for collaborations.
- Plan for Future App Store Integration: OpenAI may eventually open an official app marketplace for ChatGPT. Preparing your app now with clear documentation, compliance, and clean design will make it easier to list and monetize when the platform expands.
Imagine you build a ChatGPT app that helps agencies uncover profitable content gaps and high-intent keywords on autopilot. Position it as the best AI search visibility for agencies, and every happy user, case study, and referral turns into a recurring revenue engine for your app.
What are the Most Exciting Use Cases for ChatGPT Apps?
The ChatGPT Apps SDK opens endless possibilities for developers to create tools that feel natural to use. Here are some of the most exciting and practical examples.
- Productivity Assistants: Apps that manage tasks, create notes, or schedule meetings directly in chat help users stay organized without switching tools.
- Data and Research Tools: Developers can build apps that pull live data, analyze reports, or summarize research papers — perfect for analysts, students, and journalists.
- Creative and Design Helpers: From generating social posts to designing quick layouts, ChatGPT apps can assist with idea generation, copywriting, and visual planning.
- Learning and Education Tools: Apps can deliver personalized lessons, quizzes, or explanations in real time. Students get tutoring right inside ChatGPT without extra logins.
- API Integrations and Real-Time Services: You can connect ChatGPT to weather APIs, finance data, or booking systems. Users can check flights, stock prices, or even order food directly in chat.
- Business Workflow Automation: Businesses can automate reports, CRM updates, or customer responses. ChatGPT apps act as smart assistants that handle repetitive work seamlessly.
What are Some Real-World Examples of ChatGPT Apps in App SDK?
What Hands-On Challenges Can Help You Master the ChatGPT Apps SDK?
Challenge 1: Add a “Pizza Deals” Widget (⏱️ Easy – 15 minutes)
Goal: Create a simple text-only widget that displays daily specials.
What you’ll learn: How to add new tools to your MCP server.
Steps:
- Add a new widget definition to your tools registry.
- Create a simple tool handler that returns today’s special.
- Test with the prompt: “Show me today’s pizza deals.”
Expected output: “🍕 Today’s special: 2 medium pizzas for $19.99!”
💡 Solution Hint (click to expand)
export const pizzaDeals = {
name: "pizza-deals",
description: "Show daily pizza specials and promotions",
inputSchema: {
type: "object",
properties: {},
additionalProperties: false
},
async invoke() {
return {
confirmation: "🍕 Today's Special: Buy 2 Medium Pizzas for $19.99! Valid until 11:59 PM.",
discount: "37% off regular price",
code: "DEAL2024"
};
}
};Challenge 2: Support Multiple Toppings (⏱️ Medium – 30 minutes)
Goal: Modify your pizza ordering tool to accept multiple toppings like ["pepperoni", "mushrooms", "olives"].
What you’ll learn: JSON Schema arrays and input validation with multiple values.
Schema Update (pizza.json):
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"title": "PizzaOrderInput",
"type": "object",
"properties": {
"size": {
"type": "string",
"enum": ["small", "medium", "large"]
},
"toppings": {
"type": "array",
"items": { "type": "string" },
"description": "List of pizza toppings",
"minItems": 1,
"maxItems": 5
},
"crust": {
"type": "string",
"enum": ["thin", "thick", "stuffed"]
}
},
"required": ["size", "toppings"]
}Handler Update:
async invoke({ size, toppings, crust }) {
const toppingsList = toppings.join(", ");
return {
confirmation: `Your ${size} pizza with ${toppingsList} on a ${crust} crust is being prepared! 🍕`,
estimatedDelivery: "30 minutes",
totalToppings: toppings.length
};
}Challenge 3: Integrate Real Restaurant Data (⏱️ Hard – 60 minutes)
Goal: Replace mock pizza data with real restaurant information from the Yelp API.
What you’ll learn: External API integration, error handling, async data fetching, and data transformation.
Create API Helper (utils/yelp.js):
import fetch from 'node-fetch';
export async function fetchPizzaPlaces(location) {
const YELP_API_KEY = process.env.YELP_API_KEY;
try {
const response = await fetch(
`https://api.yelp.com/v3/businesses/search?term=pizza&location=${encodeURIComponent(location)}&limit=10`,
{ headers: { 'Authorization': `Bearer ${YELP_API_KEY}` } }
);
if (!response.ok) throw new Error(`Yelp API error: ${response.status}`);
const data = await response.json();
return data.businesses.map(biz => ({
name: biz.name,
rating: biz.rating,
address: biz.location.address1,
phone: biz.phone,
coordinates: biz.coordinates
}));
} catch (error) {
console.error('Error fetching pizza places:', error);
return [];
}
}Update Tool Handler:
import { fetchPizzaPlaces } from './utils/yelp.js';
async invoke({ location }) {
const places = await fetchPizzaPlaces(location);
if (places.length === 0) {
return { confirmation: "Sorry, couldn't find pizza places in that area. Try another location!", error: true };
}
return {
confirmation: `Found ${places.length} pizza places near ${location}! 🍕`,
restaurants: places,
totalFound: places.length
};
}Don’t forget: Add YELP_API_KEY=your_key_here to your .env file!
🏆 Bonus Challenge: Combine all three. Create a “Pizza Finder” app that shows real deals from nearby restaurants with multiple topping filters!
What Challenges and Limitations Should You Expect?
While the Apps SDK is powerful, it’s still early in its development. Being aware of its limits helps you build smarter and avoid common issues.
- Limited Access and Platform Rules: Not every developer has full SDK access yet, and some features may change as OpenAI expands the program. Always follow the official guidelines.
- Speed and Latency Issues: If your app depends on external APIs or large data sets, responses may lag. Users expect instant replies, so optimizing performance is crucial.
- Complex UI Constraints: The SDK supports simple interfaces, but complex visuals or heavy front-end apps can be hard to manage inside ChatGPT. Keep designs lightweight.
- Data Privacy and Security: Apps must handle user data carefully. Any mishandling of private information can reduce trust or lead to compliance issues.
- Ongoing Maintenance and Updates: The SDK evolves quickly, which means you’ll need to update schemas, endpoints, and documentation regularly to keep your app running smoothly.
What’s Next After You Build Your First ChatGPT App?
Building your first ChatGPT app is a big milestone, but your journey doesn’t stop here. Here’s what AllAboutAI recommends you do next to grow and refine it.
- Collect and Act on Feedback: Ask users how your app performs in real chats. Use their suggestions to fix issues, improve clarity, and add features people actually want.
- Improve Speed and Stability: Monitor your app’s performance and reduce delays or API errors. A faster, more reliable app feels smoother and keeps users coming back.
- Add Meaningful Features: Expand your app slowly with useful tools or UI elements. Each new feature should make the user’s experience easier, not more complex.
- Share and Collaborate: Publish your app on GitHub or share it in OpenAI’s community. You can also experiment with tools like OpenAI Agent Builder to create more dynamic, autonomous assistants that enhance your app’s capabilities. Collaboration opens doors to feedback, partnerships, and visibility.
- Stay Updated and Keep Learning: The Apps SDK is evolving fast, keep track of new releases and examples. Staying current ensures your app remains compatible and competitive.
What Is the Community Saying About the ChatGPT Apps SDK?
When OpenAI announced the Apps SDK for ChatGPT, Reddit’s developer and AI communities quickly jumped into discussion.
Many users were amazed by how quickly OpenAI and other labs are pushing updates, noting that it’s becoming hard to “keep up with everything new.” Some compared it to the early Plugin era but felt this update shows more promise thanks to its in-chat UI and tool integration.
Some users focused on the monetization potential, wondering if developers will be able to sell or list apps directly within ChatGPT, effectively creating an “AI App Store.”
Others highlighted that big companies like Spotify, Booking.com, and Uber are already on board, calling it a “huge leap toward turning ChatGPT into an operating system.”
Where Can You Learn More About the ChatGPT Apps SDK?
Learning never stops, especially with something as new as the ChatGPT Apps SDK. Whether you’re a beginner or an advanced developer, these official and community resources will help you stay updated, troubleshoot issues, and build better apps faster.
1. Official OpenAI Resources
📘 OpenAI Apps SDK Documentation: https://platform.openai.com/docs/apps
This is your go-to source for setup instructions, SDK APIs, schema definitions, and deployment guidelines.
💬 OpenAI Developer Forum: https://community.openai.com
Ask questions, share updates, and get direct insights from OpenAI engineers and other app builders.
📰 OpenAI Blog Apps SDK Announcement: https://openai.com/index/introducing-apps-in-chatgpt
Read the official launch post to understand the vision, architecture, and roadmap for in-chat apps.
2. GitHub Repositories and Example Projects
🔧 Official Apps SDK Examples: https://github.com/openai/openai-apps-examples
Clone and explore ready-to-use templates in TypeScript and Python to kickstart your project.
🧠 Community Projects: https://github.com/topics/chatgpt-apps-sdk
Discover open-source experiments from other developers and learn different integration styles.
Explore Other Guides
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FAQs
Do I need coding experience to build a ChatGPT App?
Can I build ChatGPT Apps using Python instead of JavaScript?
How is a ChatGPT App different from a Custom GPT?
Do I have to pay to publish or test my ChatGPT App?
Will OpenAI launch a store for ChatGPT Apps?
Conclusion
Building your first app with the ChatGPT Apps SDK is an exciting way to bring your ideas to life inside ChatGPT. You don’t need a massive setup, just a little creativity, basic coding skills, and the curiosity to explore what’s possible.
Each step in this guide on how to build app for ChatGPT with the Apps SDK helps you move closer to creating useful, interactive chat experiences. Your first app might be simple today, but it could evolve into something powerful tomorrow. You can ask questions in the comments below.
