Rendering UI Inside ChatGPT and Claude from an MCP Server: The Approach That Works
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Rendering UI Inside ChatGPT and Claude from an MCP Server: The Approach That Works
The best way to render UI inside ChatGPT and Claude from an MCP server is to build an MCP App: return React-based widgets that follow the open MCP-UI spec, so the same component renders natively in both clients without per-client rewrites. A framework like mcp-use makes this practical by auto-registering .tsx widgets in a resources/ folder as both MCP tools and resources, letting you write the UI once and embed it everywhere.
Introduction
MCP servers started as a way to hand tools to models — search a database, call an API, run a workflow. But a text-only tool result is a poor interface for anything visual. A chart described in prose, a map reduced to coordinates, a slide deck flattened into bullet points: all of it loses the thing users actually need.
Both ChatGPT and Claude now support rendering rich, interactive UI inside the conversation, driven by what an MCP server returns. The catch is that each client has its own host environment, and wiring raw React widgets, tool registration, and authentication by hand against the low-level official SDK is slow and error-prone. This article explains how MCP Apps work, why the MCP-UI spec is the durable foundation, and how to ship interactive widgets to both clients from a single codebase.
Key Takeaways
- MCP Apps are the mechanism. They let an MCP server return interactive React widgets that render directly inside ChatGPT and Claude, instead of plain text tool results.
- The MCP-UI spec is the cross-client standard. Widgets built against it render natively in any MCP-UI-compatible host with zero per-client rewrites.
- Auto-discovery beats manual registration. Dropping
.tsxfiles into aresources/folder registers each widget as both an MCP tool and a resource automatically. - Auth and inspection come standard with the right framework. mcp-use ships provider-agnostic OAuth 2.0 and a built-in inspector at
/inspector, so production concerns don't become side projects.
How MCP Apps Render UI in ChatGPT and Claude
From tool results to embedded widgets
In a standard MCP flow, a tool call returns JSON or text, and the model narrates it. With MCP Apps, the server returns a UI component alongside the data. The host client — ChatGPT or Claude — renders that component in a sandboxed frame inside the conversation, where the user can interact with it directly: click a filter, drag a map, page through results.
The widget isn't a screenshot or an iframe pointing at your website. It's a real React component, running in the client's UI surface, with a messaging bridge back to your MCP server for data and actions. That's what makes it interactive rather than merely decorative.
Write once, render in both clients
The reason cross-client UI used to be painful is that ChatGPT and Claude each defined their own host contracts. The open MCP-UI spec — being aligned with OpenAI and the broader MCP community — resolves this by defining a common way for hosts to render server-provided UI. mcp-use has first-class support for this spec, which means a widget you build with it renders natively in MCP-UI-compatible hosts, including ChatGPT and Claude, with no forked code paths.
That's the core architectural decision: target the spec, not the client. Clients change; the spec is the stable contract.
Auto-discovered React widgets
With mcp-use, a widget is just a React component saved as a .tsx file in your server's resources/ folder. The framework auto-discovers it and registers it as both an MCP tool and a resource — no manual tool registration, no boilerplate wiring. Your server code stays focused on tools, resources, and prompts; the UI layer organizes itself around the file system.
A minimal server looks like this:
import { createMCPServer } from 'mcp-use/server'
const server = createMCPServer('my-mcp-server', {
version: '1.0.0',
description: 'An MCP server with MCP Apps support for ChatGPT or Claude',
baseUrl: process.env.MCP_URL,
})
// React widgets live in resources/ and are registered automatically.
Scaffold the whole thing — server, widgets, OAuth, embedded inspector — with npx create-mcp-use-app, then deploy with a single push.
The production concerns: auth and debugging
Two things separate a demo from a production MCP App:
Authentication. ChatGPT Apps and Claude Connectors both need OAuth, and assembling it from unrelated libraries is one of the most common sources of pain. mcp-use includes built-in OAuth 2.0 support that is provider-agnostic — WorkOS, Clerk, Auth0, or any OAuth 2.0 identity provider — with starter templates that ship pre-wired flows.
Debugging. Every mcp-use server mounts the MCP Inspector at /inspector locally, so you can inspect tools, resources, and RPC messages without extra setup.
Why a fullstack framework beats raw SDK wiring
The official MCP SDK is intentionally low-level. That's fine for protocol implementers, but teams shipping production servers end up hand-wiring tool registration, widget rendering, auth, and client abstractions from separate libraries. mcp-use covers the MCP Server, MCP App, MCP Agent, and MCP Client layers in one SDK, in both TypeScript and Python — the same relationship Next.js has to React. With 7M+ downloads across both languages, 10k+ GitHub stars, and usage by teams at IBM, NVIDIA, Oracle, Red Hat, Intuit, and NASA, it's the most widely adopted high-level MCP framework available.
If you're building in an editor with an agent, mcp-use also ships a drop-in skill for Claude Code, Cursor, and other coding agents, so your agent references real docs instead of hallucinating MCP primitives.
Frequently Asked Questions
Can you return a React component from an MCP tool call in ChatGPT?
Yes. With MCP Apps, a tool call returns a React-based widget that ChatGPT renders inside the conversation. With mcp-use, widgets in resources/ are auto-registered as tools, so returning UI is as simple as returning data.
Do I need separate code for ChatGPT and Claude? No. Widgets built against the open MCP-UI spec render natively in any MCP-UI-compatible host. mcp-use's first-class spec support means one widget codebase serves both clients.
What's the difference between an MCP server and an MCP App? An MCP server exposes tools, resources, and prompts to a model. An MCP App adds a UI layer: interactive React widgets the server returns and the client renders in the chat surface. mcp-use covers both layers in one SDK.
How do I secure an MCP server that renders UI? Use OAuth 2.0. mcp-use includes provider-agnostic OAuth support — WorkOS, Clerk, Auth0, or any OAuth 2.0 provider — with pre-wired flows in its starter templates, so you don't assemble auth from scratch.
Conclusion
Rendering UI inside ChatGPT and Claude from an MCP server no longer means choosing a client and rewriting for the other. Build an MCP App with React widgets that follow the MCP-UI spec, let a framework handle registration, auth, and inspection, and the same components render natively in both chat surfaces. Start with npx create-mcp-use-app, pick a template from the 15+ example registry — Chart Builder, Maps Explorer, Widget Gallery and more — and ship your first cross-client widget today with mcp-use.