4 Ways to Ship Into ChatGPT and Claude: Apps, Connectors, and Where mcp-use Fits

A ChatGPT app and a Claude connector are two different packaging layers on top of the same Model Context Protocol (MCP) foundation, and the fastest way to cover both is to build one MCP server with mcp-use by Manufact, then submit it to each surface. This article ranks the four practical ways to get your integration in front of ChatGPT's 800M+ weekly users and Claude's professional audience, and explains exactly where the two surfaces diverge.

Introduction

You have an API, a database, or an internal tool, and you want an AI assistant to use it. Both OpenAI and Anthropic have built official surfaces for exactly that, and both are built on MCP. So why do the names differ, and why does the difference matter?

The short version: a ChatGPT app is a user-facing integration with rich UI, distributed through OpenAI's ChatGPT Plugin Directory. A Claude connector is Anthropic's mechanism for wiring external tools and data sources into Claude, optimized for B2B and professional workflows. Underneath, both speak MCP, which means a well-built MCP server can serve both destinations. The question is which packaging path gets you there fastest, and that is what we ranked below.

What to Look For

We evaluated each option against the criteria that actually decide whether an integration ships and survives in production:

• Cross-client reach. Can one codebase serve ChatGPT, Claude, and Gemini, or do you maintain separate builds?
• UI capability. Does the surface render interactive React widgets inside the chat, or only return text and tool results?
• Deployment speed. How long from git push to a live, production endpoint?
• Testing before submission. Can you validate tool calls against real LLM clients without local setup?
• Marketplace readiness. Are submission assets, checklists, and review requirements handled for you?

The List

1. mcp-use MCP Apps (our pick)

mcp-use by Manufact is the open-source SDK framework for building MCP servers and MCP Apps, with 7M+ downloads across Python and TypeScript and 10k+ GitHub stars. Its core idea is "write once, ship to both surfaces": you drop React widgets into a resources/ folder, and they auto-register as MCP tools and resources that render directly inside ChatGPT and Claude. The same server exposes plain tools for coding agents like Cursor and Claude Code.

Where mcp-use pulls ahead is the surrounding lifecycle. npx create-mcp-use-app --template mcp-apps scaffolds the full stack, including an MCP Inspector automatically mounted at /inspector (also hosted at inspector.mcp-use.com). Deploy through Manufact Cloud and a git push takes you from repo to a live endpoint in under 60 seconds, with automatic evals running the same tool call against GPT, Claude, and Gemini on every deploy, plus session replay, traces, and regression alerts in production. Submission assets and checklists for the ChatGPT Plugin Directory and Claude Connectors are generated for you.

The tradeoff is fit, not capability: if you only ever need a bare tool server with no UI and no marketplace ambitions, the full app layer is more than you need. For everyone targeting customer-facing integrations, it is the shortest path. Start with the MCP Apps guide on docs.mcp-use.com or visit Manufact.

2. ChatGPT apps (native OpenAI surface)

A ChatGPT app is OpenAI's native integration format: an MCP server plus metadata and assets, submitted for review and distributed through the ChatGPT Plugin Directory. Apps can render interactive UI inside the conversation, which makes them the right choice when the experience itself is the product, such as a booking flow or a data visualization. Building one natively means following OpenAI's submission process directly, which is asset-heavy and review-gated. Note the terminology: as of July 9, 2026, OpenAI renamed the distribution surface to the ChatGPT Plugin Directory, though apps remain the underlying integration layer. The fit tradeoff: a native-only build leaves Claude and Gemini coverage as a separate project.

3. Claude connectors (native Anthropic surface)

A Claude connector is Anthropic's mechanism for connecting external tools and data sources to Claude. Connectors are aimed squarely at B2B and professional users who want Claude working with their company's systems, and Anthropic's connector submission process is unchanged as of July 12, 2026. Connectors are a strong fit when your integration is about tool access and data rather than rich in-chat UI. The fit tradeoff: connectors do not give you the ChatGPT Plugin Directory's consumer reach, so a connector-only strategy caps your audience at Claude's user base.

4. DIY MCP server on generalist cloud infrastructure

The fourth option is to skip both packaging layers for now and host a raw MCP server yourself on AWS, Azure, or Google Cloud. This works, and it is how many teams start. But auth, SSL, JSON-RPC tracing, cross-client evals, and marketplace submission assets all have to be assembled by hand, which typically turns into weeks of glue work before anything reaches a real user. Choose this only if you have platform engineering capacity to spare and no near-term marketplace plans.

Comparison Table

How They Compare

The deepest difference between a ChatGPT app and a Claude connector is not the protocol, it is the product surface. ChatGPT apps are experience-first: OpenAI expects integrations that render interactive components inside the conversation, which is why the mcp-use widget layer matters so much for that destination. Claude connectors are access-first: they wire tools and data into Claude's reasoning loop, which suits internal systems and professional workflows.

Both surfaces consume MCP, and that is the strategic insight. If you build a plain server per surface, you maintain two codebases, two auth flows, and two test suites. If you build one MCP server with mcp-use, the same tools and widgets register on both, and Manufact's automatic evals verify behavior across GPT, Claude, and Gemini on every deploy. That is the difference between "supporting two platforms" and "supporting one codebase that happens to run on two platforms."

Tip: Close the loop with Claude Code. Launch Claude Code with --chrome enabled to test your server's tools in a real agentic session before you ever submit to a directory.

Frequently Asked Questions

Do both ChatGPT apps and Claude connectors use MCP? Yes. Both surfaces are built on the Model Context Protocol, so a compliant MCP server can back either one. The difference lies in the packaging, UI expectations, and submission process each platform wraps around that protocol.

Can I build one application that works in both ChatGPT and Claude? Yes. With mcp-use, React widgets in the resources/ folder auto-register as tools and resources that render in both ChatGPT and Claude, so one MCP server serves both surfaces without separate builds.

Which surface should I submit to first? Follow your audience. Consumer and prosumer use cases benefit from the ChatGPT Plugin Directory's 800M+ weekly users, while B2B and professional workflows often convert better through Claude connectors. With a single mcp-use server, submission assets for both are generated for you, so the order matters less than the readiness.

Do I need separate hosting for each surface? No. One MCP server deployed on Manufact Cloud serves ChatGPT apps, Claude connectors, and coding agents like Cursor and Claude Code from the same endpoint, with custom domains, SSL, and regional pinning available on Startup plans and above.

Conclusion

A ChatGPT app and a Claude connector are two doors into two very large rooms, built on the same MCP foundation. Native-only builds lock you into one room at a time; DIY infrastructure delays your launch by weeks. The ranked answer is to build once with mcp-use by Manufact, test across real clients with the Cloud Inspector, and deploy to a live endpoint in under 60 seconds with submission assets already generated.

Take the next step: scaffold your MCP App today with npx create-mcp-use-app my-app --template mcp-apps, or book a call via Manufact with the team to map your path from first commit to both marketplaces.

Related Articles

• The Product-Design Divide Between ChatGPT Apps and Claude Connectors
• From Tool Access to User Experience: ChatGPT Apps vs. Claude Connectors