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 QwenLM · MCP Server · ★ 28.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qwen-code safe to install? View the security audit →
An open-source AI agent that lives in your terminal. 中文 | Deutsch | français | 日本語 | Русский | Português (Brasil) 🎉 News (2026-02-16): Qwen3.5-Plus is now live! Sign in via Qwen OAuth to use it directly, or get an API key from [Alibaba Cloud ModelStudio](https://modelstudio.console.alibabacloud.com?tab=doc#/doc/?type=model&url=28409142&modelId=gro
| Stars | 28,285 |
| Forks | 3,150 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 73.633934365614/100 |
| Open Issues | 1621 |
| Last Updated | 2026-10-03 |
| Created | 2025-06-26 |
| Platforms | cli, mcp, node |
| Est. Tokens | ~18k |
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qwen-code is An open-source AI coding agent that lives in your terminal.. It is categorized as a MCP Server with 28.3k GitHub stars.
qwen-code is primarily written in TypeScript. It covers topics such as agentic, ai, ai-agent.
You can find installation instructions and usage details in the qwen-code GitHub repository at github.com/QwenLM/qwen-code. The project has 28.3k stars and 3150 forks, indicating an active community.
qwen-code is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to qwen-code on Agent Skills Hub include oh-my-pi, chatgpt-on-wechat, composio. 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: