mcp

Lets an assistant such as Claude, ChatGPT or Cursor show a real, clickable interface from your app instead of a wall of text, by serving it over the Model Context Protocol.

WHEN TO USE

SCOPE

USE FOR

Turn a json-render catalog into an MCP tool that renders an interactive UI inside a chat client.
Serve a Vite-bundled React app as the iframe view behind an MCP App's ui:// resource.
Wire a React hook inside the iframe so it fetches the generated spec and renders it live.
Register the resulting MCP server with Cursor, Claude Desktop, or another MCP-capable client.

This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.

In this document (8)

@json-render/mcp

MCP Apps integration that serves json-render UIs as interactive MCP Apps inside Claude, ChatGPT, Cursor, VS Code, and other MCP-capable clients.

Quick Start

Server (Node.js)

import { createMcpApp } from "@json-render/mcp";
import { defineCatalog } from "@json-render/core";
import { schema } from "@json-render/react/schema";
import { shadcnComponentDefinitions } from "@json-render/shadcn/catalog";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import fs from "node:fs";

const catalog = defineCatalog(schema, {
  components: { ...shadcnComponentDefinitions },
  actions: {},
});

const server = createMcpApp({
  name: "My App",
  version: "1.0.0",
  catalog,
  html: fs.readFileSync("dist/index.html", "utf-8"),
});

await server.connect(new StdioServerTransport());

Client (React, inside iframe)

import { useJsonRenderApp } from "@json-render/mcp/app";
import { JSONUIProvider, Renderer } from "@json-render/react";

function McpAppView({ registry }) {
  const { spec, loading, error } = useJsonRenderApp();
  if (error) return <div>Error: {error.message}</div>;
  if (!spec) return <div>Waiting...</div>;
  return (
    <JSONUIProvider registry={registry} initialState={spec.state ?? {}}>
      <Renderer spec={spec} registry={registry} loading={loading} />
    </JSONUIProvider>
  );
}

Architecture

createMcpApp() creates an McpServer that registers a render-ui tool and a ui:// HTML resource
The tool description includes the catalog prompt so the LLM knows how to generate valid specs
The HTML resource is a Vite-bundled single-file React app with json-render renderers
Inside the iframe, useJsonRenderApp() connects to the host via postMessage and renders specs

Server API

createMcpApp(options) - main entry, creates a full MCP server
registerJsonRenderTool(server, options) - register a json-render tool on an existing server
registerJsonRenderResource(server, options) - register the UI resource

Client API (`@json-render/mcp/app`)

useJsonRenderApp(options?) - React hook, returns { spec, loading, connected, error, callServerTool }
buildAppHtml(options) - generate HTML from bundled JS/CSS

Building the iframe HTML

Bundle the React app into a single self-contained HTML file using Vite + vite-plugin-singlefile:

// vite.config.ts
import { defineConfig } from "vite";
import react from "@vitejs/plugin-react";
import { viteSingleFile } from "vite-plugin-singlefile";

export default defineConfig({
  plugins: [react(), viteSingleFile()],
  build: { outDir: "dist" },
});

Client Configuration

Cursor (`.cursor/mcp.json`)

{
  "mcpServers": {
    "my-app": {
      "command": "npx",
      "args": ["tsx", "server.ts", "--stdio"]
    }
  }
}

Claude Desktop

{
  "mcpServers": {
    "my-app": {
      "command": "npx",
      "args": ["tsx", "/path/to/server.ts", "--stdio"]
    }
  }
}

Dependencies

# Server
npm install @json-render/mcp @json-render/core @modelcontextprotocol/sdk

# Client (iframe)
npm install @json-render/react @json-render/shadcn react react-dom

# Build tools
npm install -D vite @vitejs/plugin-react vite-plugin-singlefile

Not standalone. This skill ships with vercel-labs/json-render and only works together with that tool — install the tool first, then add this skill.

Run this outside your AI tool, using Node.js 22.20.0 or newer. Skills CLI 1.7.2 skips skill selection; prompts cancel installation without an interactive terminal. If choosing Project when asked about installation scope, open your project's folder before running this.

Install checklist

Check selected tools if a picker appears; Claude Code may be unchecked under Additional agents. ↑/↓ moves, Space toggles selections, Enter confirms.
Without a tool picker, check Installing to: for your intended tool. Stop if it names a different tool.
If asked, choose Symlink (Recommended) for shared files or Copy to all agents for separate copies; review the summary before confirming installation.
Install the find-skills skill? defaults to Yes, adding another skill for all projects. Choose No if you don't want that extra installation.

Skills CLI 1.7.2 sends install data to skills.sh by default, including the source, skill names, target tools and file details; GitHub sources are reported only when GitHub confirms the repository is public, while other remote sources can also be reported. Confirmed-public GitHub sources also trigger a security-audit request. Before installing, set the environment variable DO_NOT_TRACK=1 or DISABLE_TELEMETRY=1 to disable both.

npx skills add vercel-labs/json-render --skill "mcp" --full-depth

After installing for Claude Code, open it in the installation project if you chose Project; Global makes the skill available across projects on this computer. Once Claude Code loads the skill, its description helps Claude decide when to use it.

If installation created a top-level skills folder that did not exist when your Claude Code session started, run /reload-skills in that session. Run it again after later changes in that folder.

What's inside

Files included with this skill.

View on GitHub