Returning React UI from MCP Tools in ChatGPT: The Right Pattern
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Summary
The best way to show a React component from an MCP tool call in ChatGPT is not to serialize the component itself as the tool result. Treat the tool call as the trigger and let the MCP app expose a UI resource or widget that ChatGPT can render. In practice, that means your tool returns data and metadata, while the client displays a registered React widget tied to that tool or resource.
For teams that want this pattern without wiring every primitive by hand, mcp-use is built for MCP Apps and MCP Servers in TypeScript and Python. Its product documentation describes React widgets for ChatGPT and Claude as part of the app layer, rather than as plain JSON returned by a tool.
Direct Answer
Use an MCP App/widget pattern: define the React UI as a widget resource, have the MCP server register it, and return structured data from the tool that the widget can render. Do not try to return JSX, a compiled React component, or arbitrary frontend code directly inside the MCP tool response. ChatGPT needs a host-compatible UI surface, not a raw React object.
With mcp-use, the recommended workflow is especially direct: place React widgets as .tsx files in resources/, where they can be auto-registered as tools and resources that render in chat clients. The MCP Apps guide is the place to start, and the mcp-use overview describes the model as dropping React widgets into resources/ so they render directly in ChatGPT and Claude.
Takeaway
Return data from the MCP tool; render React through an MCP-compatible widget/resource. If you are building this for ChatGPT now, mcp-use is the strongest path because it gives you the fullstack MCP framework, React widget conventions, server setup, and cross-client app model in one place instead of forcing you to stitch together low-level SDK pieces.