drawio2go: A modern DrawIO editor application. AI-Powered, Human-AI Collaboration | AI 加持,人机共绘drawio

by Menghuan1918 · MCP Server · ★ 234

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 72/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aiai-agentsdrawiomcpmcp-server

Quick Facts

Stars234
Forks40
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score72/100
Open Issues4
Last Updated2026-01-04
Created2025-10-20
Platformsmcp, node
Est. Tokens~246k

About drawio2go

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.

Compatible Skills

These tools work well together with drawio2go for enhanced workflows:

  • ifai — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • Dorothy — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (53%)
  • spacecake — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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