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 Menghuan1918 · MCP Server · ★ 216
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is drawio2go safe to install? View the security audit →
DrawIO2Go AI-Powered, Human-AI Collaboration 简体中文 | English A modern DrawIO editor application dedicated to building better human-AI collaborative modeling tools with AI assistance. User-centered, enhancing human-machine efficiency, exploring how to best complement each other with AI. Provides out-of-the-box applications (Windows/Linux/Mac OS) or deployment as a web page. https://github.com/user-attachments/assets/40fe5c3b-0f37-4fbf-b6ac-60b8734f2d14 NEW: Canvas Enhancement After inserting images, it will automati
| Stars | 216 |
| Forks | 36 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.428337801153/100 |
| Open Issues | 4 |
| Last Updated | 2026-01-04 |
| Created | 2025-10-20 |
| Platforms | mcp, node |
| Est. Tokens | ~246k |
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drawio2go is A modern DrawIO editor application. AI-Powered, Human-AI Collaboration | AI 加持，人机共绘drawio. It is categorized as a MCP Server with 216 GitHub stars.
drawio2go is primarily written in TypeScript. It covers topics such as ai, ai-agents, drawio.
You can find installation instructions and usage details in the drawio2go GitHub repository at github.com/Menghuan1918/drawio2go. The project has 216 stars and 36 forks, indicating an active community.
drawio2go is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to drawio2go on Agent Skills Hub include golf, Context-Engine, daymon. 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: