> Discover all available pages from the documentation index: https://mastra.ai/llms.txt

# Integrate Mastra in your Electron project

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

You'll use [AI SDK UI](https://ai-sdk.dev/docs/ai-sdk-ui/overview) to create a beautiful, interactive chat experience.

## Before you begin

- You'll need an API key from a supported [model provider](https://mastra.ai/models). If you don't have a preference, use [OpenAI](https://mastra.ai/models/providers/openai).
- Install Node.js `v22.13.0` or later

## Create a new Electron app (optional)

If you already have an Electron app, skip to the next step.

Scaffold a new Electron app using [electron-vite](https://electron-vite.org/):

**npm**:

```bash
npm create @quick-start/electron@latest electron-chat -- --template react-ts --skip
```

**pnpm**:

```bash
pnpm create @quick-start/electron electron-chat --template react-ts --skip
```

**Yarn**:

```bash
yarn create @quick-start/electron electron-chat --template react-ts --skip
```

**Bun**:

```bash
bunx @quick-start/create-electron@latest electron-chat --template react-ts --skip
```

This creates a new Electron app called `electron-chat` with React and TypeScript. Navigate into the project directory:

```bash
cd electron-chat
```

### Edit CSP settings

In order for the Electron app to call the Mastra server, you need to adjust the Content Security Policy (CSP) settings.

Open `src/renderer/index.html` and update the `<meta http-equiv="Content-Security-Policy">` tag to include `http://localhost:4111` in the `connect-src` directive:

```html
<meta
  http-equiv="Content-Security-Policy"
  content="default-src 'self'; connect-src http://localhost:4111; script-src 'self'; style-src 'self' 'unsafe-inline'; img-src 'self' data:"
/>
```

> **Info:** For production deployments you'll need to adjust this to match your actual server URL.

### Edit `main.css`

Open `src/renderer/src/assets/main.css` and change its contents to:

```css
@import './base.css';

body {
  background: var(--ev-c-white);
  color: var(--ev-c-black);
}
```

## Initialize Mastra

Run [`mastra init`](https://mastra.ai/reference/cli/mastra). When prompted, choose a provider (e.g. OpenAI) and enter your key:

**npm**:

```bash
npx mastra@latest init
```

**pnpm**:

```bash
pnpm dlx mastra@latest init
```

**Yarn**:

```bash
yarn dlx mastra@latest init
```

**Bun**:

```bash
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**:

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

**pnpm**:

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

**Yarn**:

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

**Bun**:

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

## Create a chat route

Open `src/mastra/index.ts` and add a [`chatRoute()`](https://mastra.ai/reference/ai-sdk/chat-route) to your config. This creates an API route your Electron frontend can call for AI SDK-compatible chat responses, which you'll use with `useChat()` next.

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

export const mastra = new Mastra({
  // Existing config...
  server: {
    cors: {
      origin: '*', // Restrict this to your app's origin in production
      allowMethods: ['*'],
      allowHeaders: ['*'],
    },
    apiRoutes: [
      chatRoute({
        path: '/chat/:agentId',
      }),
    ],
  },
})
```

> **Info:** CORS is required because the Electron renderer loads from a different origin than the Mastra server. For production deployments, restrict the origin to your application's actual origin.

## Add the chat UI

Open `src/renderer/src/App.tsx` and replace its contents with the chat component:

```tsx
import { useState } from 'react'
import { useChat } from '@ai-sdk/react'
import { DefaultChatTransport, type ToolUIPart } from 'ai'

const STATE_TO_LABEL_MAP: Record<string, string> = {
  'input-streaming': 'Streaming input...',
  'input-available': 'Input ready',
  'approval-requested': 'Approval requested',
  'approval-responded': 'Approval responded',
  'output-available': 'Complete',
  'output-error': 'Error',
}

export default function App(): React.JSX.Element {
  const [input, setInput] = useState('')

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

  const handleSubmit = (e: React.FormEvent<HTMLFormElement>): void => {
    e.preventDefault()
    if (!input.trim()) return
    sendMessage({ text: input })
    setInput('')
  }

  return (
    <main
      style={{
        maxWidth: '48rem',
        marginLeft: 'auto',
        marginRight: 'auto',
        padding: '1.5rem',
        width: '100%',
        height: '100vh',
      }}
    >
      <div style={{ display: 'flex', flexDirection: 'column', height: '100%' }}>
        <div style={{ flex: '1 1 0%', minHeight: 0, overflowY: 'auto' }} data-name="conversation">
          <div
            data-name="conversation-content"
            style={{ display: 'flex', flexDirection: 'column', gap: '2rem' }}
          >
            {messages.map((message, messageIndex) => (
              <div key={messageIndex}>
                {message.parts.map((part, partIndex) => {
                  if (part.type === 'text') {
                    return (
                      <div
                        key={partIndex}
                        data-name="message"
                        style={{
                          display: 'flex',
                          width: '100%',
                          maxWidth: '95%',
                          flexDirection: 'column',
                          gap: '0.5rem',
                          ...(message.role === 'user'
                            ? { marginLeft: 'auto', justifyContent: 'flex-end' }
                            : {}),
                        }}
                      >
                        <div
                          data-name="message-content"
                          style={{
                            display: 'flex',
                            width: 'fit-content',
                            maxWidth: '100%',
                            minWidth: 0,
                            flexDirection: 'column',
                            gap: '0.5rem',
                            overflow: 'hidden',
                            fontSize: '0.875rem',
                            ...(message.role === 'user'
                              ? {
                                  marginLeft: 'auto',
                                  borderRadius: '0.5rem',
                                  backgroundColor: '#dbeafe',
                                  paddingLeft: '1rem',
                                  paddingRight: '1rem',
                                  paddingTop: '0.75rem',
                                  paddingBottom: '0.75rem',
                                }
                              : {}),
                          }}
                        >
                          <div
                            data-name="message-response"
                            style={{ width: '100%', height: '100%' }}
                          >
                            {part.text}
                          </div>
                        </div>
                      </div>
                    )
                  }
                  if (part.type.startsWith('tool-')) {
                    const toolPart = part as unknown as ToolUIPart
                    return (
                      <div
                        key={partIndex}
                        data-name="tool"
                        style={{
                          marginBottom: '1.5rem',
                          width: '100%',
                          borderRadius: '0.5rem',
                          border: '1px solid #d1d5db',
                          boxShadow: '0 1px 3px 0 rgba(0,0,0,0.1)',
                        }}
                      >
                        <details
                          data-name="tool-header"
                          style={{ width: '100%', padding: '0.75rem', cursor: 'pointer' }}
                        >
                          <summary style={{ fontWeight: 500, fontSize: '0.875rem' }}>
                            {toolPart.type.split('-').slice(1).join('-')} -{' '}
                            {STATE_TO_LABEL_MAP[toolPart.state ?? 'output-available']}
                          </summary>
                          <div data-name="tool-content">
                            <div
                              data-name="tool-input"
                              style={{
                                overflow: 'hidden',
                                paddingTop: '1rem',
                                paddingBottom: '1rem',
                              }}
                            >
                              <div
                                style={{
                                  fontWeight: 500,
                                  color: '#6b7280',
                                  fontSize: '0.75rem',
                                  textTransform: 'uppercase',
                                  letterSpacing: '0.05em',
                                }}
                              >
                                Parameters
                              </div>
                              <pre
                                style={{
                                  width: '100%',
                                  overflowX: 'auto',
                                  borderRadius: '0.375rem',
                                  border: '1px solid #d1d5db',
                                  backgroundColor: '#f9fafb',
                                  padding: '0.75rem',
                                  fontSize: '0.875rem',
                                }}
                              >
                                <code>{JSON.stringify(toolPart.input, null, 2)}</code>
                              </pre>
                            </div>
                            <div
                              data-name="tool-output"
                              style={{
                                overflow: 'hidden',
                                paddingTop: '1rem',
                                paddingBottom: '1rem',
                              }}
                            >
                              <div
                                style={{
                                  fontWeight: 500,
                                  color: '#6b7280',
                                  fontSize: '0.75rem',
                                  textTransform: 'uppercase',
                                  letterSpacing: '0.05em',
                                }}
                              >
                                {toolPart.errorText ? 'Error' : 'Result'}
                              </div>
                              <pre
                                style={{
                                  width: '100%',
                                  overflowX: 'auto',
                                  borderRadius: '0.375rem',
                                  border: '1px solid #d1d5db',
                                  backgroundColor: '#f9fafb',
                                  padding: '0.75rem',
                                  fontSize: '0.875rem',
                                }}
                              >
                                <code>{JSON.stringify(toolPart.output, null, 2)}</code>
                              </pre>
                              {toolPart.errorText && (
                                <div data-name="tool-error" style={{ color: '#dc2626' }}>
                                  {toolPart.errorText}
                                </div>
                              )}
                            </div>
                          </div>
                        </details>
                      </div>
                    )
                  }
                  return null
                })}
              </div>
            ))}
          </div>
        </div>
        <form
          style={{
            width: '100%',
            display: 'grid',
            gridTemplateColumns: '1fr auto',
            gap: '1.5rem',
            flexShrink: 0,
            paddingTop: '1rem',
          }}
          onSubmit={handleSubmit}
          data-name="prompt-input"
        >
          <input
            name="chat-input"
            style={{
              borderRadius: '0.5rem',
              border: '1px solid #d1d5db',
              boxShadow: '0 1px 2px 0 rgba(0,0,0,0.05)',
              height: '2.5rem',
              padding: '0 0.75rem',
            }}
            placeholder="City name"
            value={input}
            onChange={e => setInput(e.target.value)}
          />
          <button
            style={{
              backgroundColor: '#2563eb',
              color: 'white',
              boxShadow: '0 10px 15px -3px rgba(0,0,0,0.1)',
              border: '1px solid #60a5fa',
              paddingLeft: '1rem',
              paddingRight: '1rem',
              whiteSpace: 'nowrap',
              borderRadius: '0.5rem',
              fontSize: '0.875rem',
              fontWeight: 500,
              transition: 'all',
              flexShrink: 0,
              outline: 'none',
            }}
            type="submit"
          >
            Send
          </button>
        </form>
      </div>
    </main>
  )
}
```

This connects [`useChat()`](https://ai-sdk.dev/docs/reference/ai-sdk-ui/use-chat) to the `/chat/weather-agent` endpoint, sending propmts there and streaming the response back in chunks.

## Test your agent

To test your agent with the chat interface, run both the Mastra server and the Electron app.

1. Start the mastra development server:

   **npm**:

   ```bash
   npx mastra dev
   ```

   **pnpm**:

   ```bash
   pnpm dlx mastra dev
   ```

   **Yarn**:

   ```bash
   yarn dlx mastra dev
   ```

   **Bun**:

   ```bash
   bun x mastra dev
   ```

2. In a separate terminal, start the Electron app:

   **npm**:

   ```bash
   npm run dev
   ```

   **pnpm**:

   ```bash
   pnpm run dev
   ```

   **Yarn**:

   ```bash
   yarn dev
   ```

   **Bun**:

   ```bash
   bun run dev
   ```

3. An Electron window opens with the chat interface

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 Electron! 🎉

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

- Learn more about [agents](https://mastra.ai/docs/agents/overview)
- Give your agent its own [tools](https://mastra.ai/docs/agents/using-tools)
- Add human-like [memory](https://mastra.ai/docs/memory/overview) 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](https://mastra.ai/guides/build-your-ui/ai-sdk-ui)
- Deploy your agent [anywhere](https://mastra.ai/docs/deployment/overview)