mcp
MCP Apps integration for json-render. Use when building MCP servers that render interactive UIs in Claude, ChatGPT, Cursor, or VS Code, or when integrating json-render with the Model Context Protocol.
Install
npx skills add https://github.com/vercel-labs/json-render --skill mcpSKILL.md
@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 anMcpServerthat registers arender-uitool and aui://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 viapostMessageand renders specs
Server API
createMcpApp(options)- main entry, creates a full MCP serverregisterJsonRenderTool(server, options)- register a json-render tool on an existing serverregisterJsonRenderResource(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
Related skills
find-skillsvercel-labs3.6MHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.handoffmattpocock883KCompact the current conversation into a handoff document for another agent to pick up.microsoft-foundrymicrosoft618KBuild, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agcavemanjuliusbrussee544KUltra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".