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 antoinebou12 · MCP Server · ★ 98
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is uml-mcp safe to install? View the security audit →
UML-MCP: Diagram Generation via MCP Generate UML and other diagrams through the Model Context Protocol. At a glance , , lis
| Stars | 98 |
| Forks | 28 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 78.2534807053997/100 |
| Open Issues | 3 |
| Last Updated | 2026-09-04 |
| Created | 2025-04-01 |
| Platforms | mcp, python |
| Est. Tokens | ~15k |
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PlantUML diagrams (.puml) from natural language via Kroki — no Java install. 10+ UML types, 5 themes, PNG/SVG,
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uml-mcp is UML-MCP Server is a UML diagram generation tool based on MCP (Model Context Protocol), which can help users generate various types of UML diagrams through natural language description or directly writ. It is categorized as a MCP Server with 98 GitHub stars.
uml-mcp is primarily written in Python. It covers topics such as mcp, uml.
You can find installation instructions and usage details in the uml-mcp GitHub repository at github.com/antoinebou12/uml-mcp. The project has 98 stars and 28 forks, indicating an active community.
uml-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to uml-mcp on Agent Skills Hub include plantuml-skill. 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: