No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by bytedance · MCP Server · ★ 38.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is UI-TARS-desktop safe to install? View the security audit →
Introduction English | 简体中文 TARS\ is a Multimodal AI Agent stack, currently shipping two projects: Agent TARS and UI-TARS-desktop: Agent TARS UI-TARS-desktop 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 mu
| Stars | 38,933 |
| Forks | 3,937 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 68.7429440435133/100 |
| Open Issues | 444 |
| Last Updated | 2026-09-11 |
| Created | 2025-01-19 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~18k |
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UI-TARS-desktop is The Open-Source Multimodal AI Agent Stack: Connecting Cutting-Edge AI Models and Agent Infra. It is categorized as a MCP Server with 38.9k GitHub stars.
UI-TARS-desktop is primarily written in TypeScript. It covers topics such as agent, agent-tars, browser-use.
You can find installation instructions and usage details in the UI-TARS-desktop GitHub repository at github.com/bytedance/UI-TARS-desktop. The project has 38.9k stars and 3937 forks, indicating an active community.
UI-TARS-desktop is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to UI-TARS-desktop on Agent Skills Hub include gpt-researcher, midscene, bytebot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: