@agent-tars/core

Agent TARS is a general multimodal AI Agent stack, it brings the power of GUI Agent and Vision into your terminal, computer, browser and product.

It primarily ships with a CLI and Web UI for usage. It aims to provide a workflow that is closer to human-like task completion through cutting-edge multimodal LLMs and seamless integration with various real-world MCP tools.

📣 Just released: Agent TARS Beta - check out our announcement blog post!

https://github.com/user-attachments/assets/772b0eef-aef7-4ab9-8cb0-9611820539d8

For more use cases, please check out #842.

Overview

@agent-tars/core is the core implementation of Agent TARS, built on top of the Tarko Agent framework. It provides a comprehensive multimodal AI agent with advanced browser automation, filesystem operations, and intelligent search capabilities.

Core Features

• 🖱️ One-Click Out-of-the-box CLI - Supports both headful Web UI and headless server) execution.
• 🌐 Hybrid Browser Agent - Control browsers using GUI Agent, DOM, or a hybrid strategy.
• 🔄 Event Stream - Protocol-driven Event Stream drives Context Engineering and Agent UI.
• 🧰 MCP Integration - The kernel is built on MCP and also supports mounting MCP Servers to connect to real-world tools.

Quick Start

# Luanch with `npx`.
npx @agent-tars/cli@latest

# Install globally, required Node.js >= 22
npm install @agent-tars/cli@latest -g

# Run with your preferred model provider
agent-tars --provider volcengine --model doubao-1-5-thinking-vision-pro-250428 --apiKey your-api-key
agent-tars --provider anthropic --model claude-3-7-sonnet-latest --apiKey your-api-key

Visit the comprehensive Quick Start guide for detailed setup instructions.

Quick Start

Installation

npm install @agent-tars/core

Running Agent TARS

Agent TARS can be started in multiple ways:

Option 1: Using @agent-tars/cli (Recommended)

# Install globally
npm install -g @agent-tars/cli

# Run Agent TARS
agent-tars

# Or use directly via npx
npx @agent-tars/cli

Option 2: Using @tarko/agent-cli

# Install globally
npm install -g @tarko/agent-cli

# Run Agent TARS through tarko CLI
tarko run agent-tars

# Or use directly via npx
npx @tarko/agent-cli run agent-tars

Option 3: Programmatic Usage

Basic Usage

import { AgentTARS } from '@agent-tars/core';

// Create an agent instance
const agent = new AgentTARS({
  model: {
    provider: 'openai',
    model: 'gpt-4',
    apiKey: process.env.OPENAI_API_KEY,
  },
  workspace: './workspace',
  browser: {
    headless: false,
    control: 'hybrid',
  },
});

// Initialize and run
await agent.initialize();
const result = await agent.run('Search for the latest AI research papers');
console.log(result);

Configuration

AgentTARSOptions

interface AgentTARSOptions {
  // Model configuration
  model?: {
    provider: 'openai' | 'anthropic' | 'doubao';
    model: string;
    apiKey: string;
  };
  
  // Browser settings
  browser?: {
    headless?: boolean;
    control?: 'dom' | 'visual-grounding' | 'hybrid';
    cdpEndpoint?: string;
  };
  
  // Search configuration
  search?: {
    provider: 'browser_search' | 'tavily';
    count?: number;
    apiKey?: string;
  };
  
  // Workspace settings
  workspace?: string;
  
  // MCP implementation
  mcpImpl?: 'in-memory' | 'stdio';
}

Browser Control Modes

• dom: Direct DOM manipulation (fastest, most reliable)
• visual-grounding: Vision-based interaction (most flexible)
• hybrid: Combines both approaches (recommended)

Advanced Usage

Custom Instructions

const agent = new AgentTARS({
  instructions: `
    You are a specialized research assistant.
    Focus on academic papers and technical documentation.
    Always provide citations and sources.
  `,
  // ... other options
});

Browser State Management

// Get browser control information
const browserInfo = agent.getBrowserControlInfo();
console.log(`Mode: ${browserInfo.mode}`);
console.log(`Tools: ${browserInfo.tools.join(', ')}`);

// Access browser manager
const browserManager = agent.getBrowserManager();
if (browserManager) {
  const isAlive = await browserManager.isBrowserAlive();
  console.log(`Browser status: ${isAlive ? 'alive' : 'dead'}`);
}

Workspace Operations

// Get current workspace
const workspace = agent.getWorkingDirectory();
console.log(`Working in: ${workspace}`);

// All file operations are automatically scoped to workspace
const result = await agent.run('Create a summary.md file with today\'s findings');

Error Handling

try {
  await agent.initialize();
  const result = await agent.run('Your task here');
} catch (error) {
  console.error('Agent error:', error);
} finally {
  // Always cleanup
  await agent.cleanup();
}

API Reference

Core Methods

• initialize(): Initialize the agent and all components
• run(message): Execute a task with the given message
• cleanup(): Clean up all resources
• getWorkingDirectory(): Get current workspace path
• getBrowserControlInfo(): Get browser control status
• getBrowserManager(): Access browser manager instance

Events

The agent emits events through the event stream:

agent.eventStream.subscribe((event) => {
  if (event.type === 'tool_result') {
    console.log(`Tool ${event.name} completed`);
  }
});

Resources

• 📄 Blog Post
• 🐦 Release Announcement on Twitter
• 🐦 Official Twitter
• 💬 Discord Community
• 💬 飞书交流群
• 🚀 Quick Start
• 💻 CLI Documentation
• 🖥️ Web UI Guide
• 📁 Workspace Documentation
• 🔌 MCP Documentation

Features

• 🌐 Advanced Browser Control: Multiple control strategies (DOM, Visual, Hybrid)
• 📁 Safe Filesystem Operations: Workspace-scoped file management
• 🔍 Intelligent Search: Integration with multiple search providers
• 🔧 MCP Integration: Built-in Model Context Protocol support
• 📸 Visual Understanding: Screenshot-based browser interaction
• 🛡️ Safety First: Path validation and workspace isolation

What's Changed

See Full CHANGELOG

Contributing

See CONTRIBUTING.md for development guidelines.

License

Apache-2.0 - See LICENSE for details.