> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bytebot.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# API Reference

> Overview of the Bytebot API endpoints for programmatic control

# Bytebot API Overview

Bytebot provides two main APIs for programmatic control:

## 1. Agent API (Task Management)

The Agent API runs on port 9991 and provides high-level task management:

<CardGroup cols={2}>
  <Card title="Task Management" icon="list-check" href="/api-reference/agent/tasks">
    Create, manage, and monitor AI-powered tasks programmatically
  </Card>

  <Card title="UI Integration" icon="window" href="/api-reference/agent/ui">
    WebSocket connections and real-time updates for custom UIs
  </Card>
</CardGroup>

### Agent API Base URL

```
http://localhost:9991
```

### Example Task Creation

```bash theme={null}
curl -X POST http://localhost:9991/tasks \
  -H "Content-Type: application/json" \
  -d '{
    "description": "Download invoices from webmail and organize by date",
    "priority": "HIGH"
  }'
```

## 2. Desktop API (Direct Control)

The Desktop API runs on port 9990 and provides low-level desktop control:

<CardGroup cols={2}>
  <Card title="Computer Control" icon="keyboard" href="/api-reference/computer-use/unified-endpoint">
    Direct control of mouse, keyboard, and screen capture
  </Card>

  <Card title="Usage Examples" icon="code" href="/api-reference/computer-use/examples">
    Code examples for common automation scenarios
  </Card>
</CardGroup>

### Desktop API Base URL

```
http://localhost:9990
```

### Example Desktop Control

```bash theme={null}
curl -X POST http://localhost:9990/computer-use \
  -H "Content-Type: application/json" \
  -d '{"action": "screenshot"}'
```

### MCP Support

The Desktop API also exposes an MCP (Model Context Protocol) endpoint:

```
http://localhost:9990/mcp
```

Connect your MCP client to access desktop control tools over SSE.

## Authentication

* **Local Access**: No authentication required by default
* **Remote Access**: Configure authentication based on your security requirements
* **Production**: Implement API keys, OAuth, or other authentication methods

## Response Formats

### Agent API Response

```json theme={null}
{
  "id": "task-123",
  "status": "RUNNING",
  "description": "Your task description",
  "messages": [...],
  "createdAt": "2024-01-01T00:00:00Z"
}
```

### Desktop API Response

```json theme={null}
{
  "success": true,
  "data": { ... },  // Response data specific to the action
  "error": null     // Error message if success is false
}
```

## Error Handling

Both APIs use standard HTTP status codes:

| Status Code | Description                          |
| ----------- | ------------------------------------ |
| 200         | Success                              |
| 201         | Created (new resource)               |
| 400         | Bad Request - Invalid parameters     |
| 401         | Unauthorized - Authentication failed |
| 404         | Not Found - Resource doesn't exist   |
| 500         | Internal Server Error                |

## Rate Limiting

* **Agent API**: No hard limits, but consider task queue capacity
* **Desktop API**: No rate limiting, but rapid actions may impact desktop performance

## Best Practices

1. **Use Agent API for high-level automation** - Let the AI handle complexity
2. **Use Desktop API for precise control** - When you need exact actions
3. **Combine both APIs** - Create tasks via Agent API, monitor via Desktop API
4. **Handle errors gracefully** - Implement retry logic for transient failures
5. **Monitor resource usage** - Both APIs can be resource-intensive

## Next Steps

<CardGroup cols={2}>
  <Card title="Quick Start" icon="rocket" href="/quickstart">
    Get your APIs running
  </Card>

  <Card title="Task Examples" icon="code" href="/guides/task-creation">
    See the APIs in action
  </Card>
</CardGroup>