React + Vite

In this guide, you'll build a tool-calling AI agent using Mastra, then connect it to React by calling the agent directly from Mastra's standalone server.

You'll use AI SDK UI and AI Elements to create a beautiful, interactive chat experience.

Before you begin

• You'll need an API key from a supported model provider. If you don't have a preference, use OpenAI.
• Install Node.js v22.13.0 or later

Create a new React + Vite app (optional)

If you already have a React + Vite app using Tailwind, skip to the next step.

Project scaffold

Run the following command to create a new React + Vite app:

npm

npm create vite@latest mastra-react -- --template react-ts

pnpm

pnpm create vite mastra-react --template react-ts

Yarn

yarn create vite mastra-react --template react-ts

Bun

bunx create-vite mastra-react --template react-ts

This creates a project called mastra-react, but you can replace it with any name you want.

Navigate to your project directory:

cd mastra-react

Tailwind

Next, install Tailwind:

npm

npm install tailwindcss @tailwindcss/vite

pnpm

pnpm add tailwindcss @tailwindcss/vite

Yarn

yarn add tailwindcss @tailwindcss/vite

Bun

bun add tailwindcss @tailwindcss/vite

Configure the Vite plugins:

vite.config.ts

import { defineConfig } from 'vite'
import react from '@vitejs/plugin-react'
import path from 'path'
import tailwindcss from '@tailwindcss/vite'

export default defineConfig({
  plugins: [react(), tailwindcss()],
  resolve: {
    alias: {
      '@': path.resolve(__dirname, './src'),
    },
  },
})

Replace everything in src/index.css with the following:

src/index.css

@import 'tailwindcss';

Add these compilerOptions to tsconfig.json:

tsconfig.json

{
  // ...
  "compilerOptions": {
    "baseUrl": ".",
    "paths": {
      "@/*": ["./src/*"],
    },
  },
}

Edit tsconfig.app.json to resolve paths:

tsconfig.app.json

{
  "compilerOptions": {
    // ...
    "baseUrl": ".",
    "paths": {
      "@/*": ["./src/*"],
    },
    // ...
  },
}

Initialize Mastra

Run mastra init. When prompted, choose a provider (e.g. OpenAI) and enter your key:

npm

npx mastra@latest init

pnpm

pnpm dlx mastra@latest init

Yarn

yarn dlx mastra@latest init

Bun

bun x mastra@latest init

This creates a src/mastra folder with an example weather agent and the following files:

• index.ts: Mastra config, including memory
• tools/weather-tool.ts: A tool to fetch weather for a given location
• agents/weather-agent.ts: A weather agent with a prompt that uses the tool

You'll call weather-agent.ts from your chat UI in the next steps.

Install AI SDK UI & AI elements

Install AI SDK UI along with the Mastra adapter:

npm

npm install @mastra/ai-sdk@latest @ai-sdk/react ai

pnpm

pnpm add @mastra/ai-sdk@latest @ai-sdk/react ai

Yarn

yarn add @mastra/ai-sdk@latest @ai-sdk/react ai

Bun

bun add @mastra/ai-sdk@latest @ai-sdk/react ai

Next, initialize AI Elements. When prompted to select a component library, choose Radix UI, then accept the defaults for the remaining prompts:

npm

npx ai-elements@latest

pnpm

pnpm dlx ai-elements@latest

Yarn

yarn dlx ai-elements@latest

Bun

bun x ai-elements@latest

备注

The ai-elements command runs shadcn add against the AI Elements registry, which currently publishes Radix UI components only. Installing them into a Base UI project produces TypeScript errors, tracked in vercel/ai-elements#383.

The component library prompt only appears when your project has no components.json. If you already have one, check that its style is a Radix option, such as new-york or a radix-* style, and not a base-* style, before running the command.

This downloads the entire AI Elements UI component library into a @/components/ai-elements folder.

Create a chat route

Open ⁠src/mastra/index.ts and add a ⁠chatRoute() to your config. This creates an API route your React frontend can call for AI SDK-compatible chat responses, which you’ll use with ⁠useChat() next.

src/mastra/index.ts

import { Mastra } from '@mastra/core/mastra'
// Existing imports...
import { chatRoute } from '@mastra/ai-sdk'

export const mastra = new Mastra({
  // Existing config...
  server: {
    apiRoutes: [
      chatRoute({
        path: '/chat/:agentId',
      }),
    ],
  },
})

Add the chat UI

Replace the src/App.tsx file to create a chat interface:

src/App.tsx

import * as React from 'react'
import { DefaultChatTransport, type ToolUIPart } from 'ai'
import { useChat } from '@ai-sdk/react'

import {
  PromptInput,
  PromptInputBody,
  PromptInputTextarea,
} from '@/components/ai-elements/prompt-input'

import {
  Conversation,
  ConversationContent,
  ConversationScrollButton,
} from '@/components/ai-elements/conversation'

import { Message, MessageContent, MessageResponse } from '@/components/ai-elements/message'

import { Tool, ToolHeader, ToolContent, ToolInput, ToolOutput } from '@/components/ai-elements/tool'

export default function App() {
  const [input, setInput] = React.useState<string>('')

  const { messages, sendMessage, status } = useChat({
    transport: new DefaultChatTransport({
      api: 'http://localhost:4111/chat/weather-agent',
    }),
  })

  const handleSubmit = async () => {
    if (!input.trim()) return

    sendMessage({ text: input })
    setInput('')
  }

  return (
    <div className="relative mx-auto size-full h-screen max-w-4xl p-6">
      <div className="flex h-full flex-col">
        <Conversation className="h-full">
          <ConversationContent>
            {messages.map(message => (
              <div key={message.id}>
                {message.parts?.map((part, i) => {
                  if (part.type === 'text') {
                    return (
                      <Message key={`${message.id}-${i}`} from={message.role}>
                        <MessageContent>
                          <MessageResponse>{part.text}</MessageResponse>
                        </MessageContent>
                      </Message>
                    )
                  }

                  if (part.type?.startsWith('tool-')) {
                    return (
                      <Tool key={`${message.id}-${i}`}>
                        <ToolHeader
                          type={(part as ToolUIPart).type}
                          state={(part as ToolUIPart).state || 'output-available'}
                          className="cursor-pointer"
                        />
                        <ToolContent>
                          <ToolInput input={(part as ToolUIPart).input || {}} />
                          <ToolOutput
                            output={(part as ToolUIPart).output}
                            errorText={(part as ToolUIPart).errorText}
                          />
                        </ToolContent>
                      </Tool>
                    )
                  }

                  return null
                })}
              </div>
            ))}
            <ConversationScrollButton />
          </ConversationContent>
        </Conversation>
        <PromptInput onSubmit={handleSubmit} className="mt-20">
          <PromptInputBody>
            <PromptInputTextarea
              onChange={e => setInput(e.target.value)}
              className="md:leading-10"
              value={input}
              placeholder="Ask about the weather..."
              disabled={status !== 'ready'}
            />
          </PromptInputBody>
        </PromptInput>
      </div>
    </div>
  )
}

This component connects useChat() to the chat/weather-agent endpoint, sending prompts there and streaming the response back in chunks.

It renders the response text using the <MessageResponse> component, and shows any tool invocations with the <Tool> component.

Test your agent

To test your agent with the chat interface, run both the Mastra server and the Vite development server.

1. Start the Mastra development server:

   npm

   npx mastra dev

   pnpm

   pnpm dlx mastra dev

   Yarn

   yarn dlx mastra dev

   Bun

   bun x mastra dev

2. In a separate terminal window, start the Vite development server:

   npm

   npm run dev

   pnpm

   pnpm run dev

   Yarn

   yarn dev

   Bun

   bun run dev

3. Open your application at http://localhost:5173

4. Try asking about the weather. If your API key is set up correctly, you'll get a response

Next steps

Congratulations on building your Mastra agent with React! 🎉

From here, you can extend the project with your own tools and logic:

• Learn more about agents
• Give your agent its own tools
• Add human-like memory to your agent

When you're ready, read more about how Mastra integrates with AI SDK UI and React, and how to deploy your agent anywhere:

• Integrate Mastra with AI SDK UI
• Deploy your agent anywhere