Components as Tools

"use client";import React from "react";import {  CopilotChat,  CopilotKit,  useComponent,} from "@copilotkit/react-core/v2";import { BarChart, barChartPropsSchema } from "./bar-chart";import { PieChart, pieChartPropsSchema } from "./pie-chart";import { useSuggestions } from "./suggestions";function Chat() {  useComponent({    name: "render_bar_chart",    description: "Display a bar chart with labeled numeric values.",    parameters: barChartPropsSchema,    render: BarChart,  });  useComponent({    name: "render_pie_chart",    description: "Display a pie chart with labeled numeric values.",    parameters: pieChartPropsSchema,    render: PieChart,  });  useSuggestions();  return (    <div className="flex justify-center items-center h-screen w-full">      <div className="h-full w-full max-w-4xl">        <CopilotChat          agentId="gen-ui-tool-based"          className="h-full rounded-2xl"        />      </div>    </div>  );}export default function ControlledGenUiDemo() {  return (    <CopilotKit runtimeUrl="/api/copilotkit" agent="gen-ui-tool-based">      <Chat />    </CopilotKit>  );}

What is this?#

Tool-based Generative UI is the simplest form of Generative UI: you register a React component with useComponent, and CopilotKit exposes it to the agent as a tool. When the agent calls the tool, CopilotKit renders your component inline in the chat, passing the tool's arguments straight through as typed props.

Unlike tool rendering, which wraps a real backend tool in a custom UI, tool-based GenUI is the component. There is no handler, no user interaction, no server-side execution. The agent decides when to show it, populates the data, and CopilotKit paints it.

When should I use this?#

Use useComponent when you want to:

• Display rich UI (cards, charts, tables, dashboards) inline in the chat
• Show structured data the agent has derived from its reasoning
• Render previews, status indicators, or visual summaries
• Let the agent present information beyond plain text

For components that need user interaction, see Human-in-the-loop. For operational transparency around a real backend tool, see Tool rendering.

How it works in code#

import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

// `render_bar_chart` is intentionally NOT declared here. It is a
// frontend-only tool registered via `useComponent`, and the adapter
// forwards it as a client tool on every run.
export const chartAgent = new Agent({
  id: "chart-agent",
  name: "Chart Agent",
  model: openai("gpt-4o"),
  instructions: SYSTEM_PROMPT,
});

const SYSTEM_PROMPT = `You are a data visualization assistant.

When the user asks for a chart, call the frontend \`render_bar_chart\` tool
with a concise title and a \`data\` array of \`{label, value}\` items.

Keep chat responses brief and let the chart do the talking.`;

Import the React hook and Zod in the component that registers the tool. This also applies to the built-in agent, which needs no backend tool-registration step.

import { useComponent } from "@copilotkit/react-core/v2";
import { z } from "zod";

useComponent takes a name, a Zod schema for its props, and the component to render. The runtime registers it as a frontend tool so the agent can discover it, and Zod validates the LLM's arguments before they reach your component.

  useComponent({    name: "render_bar_chart",    description: "Display a bar chart with labeled numeric values.",    parameters: barChartPropsSchema,    render: BarChart,  });

The component itself is ordinary React: it reads only its props and can stream in as the agent fills the payload. The example above uses Recharts for the bar chart; it doesn't know anything about CopilotKit.