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 udecode · MCP Server · ★ 59
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is plate-template safe to install? View the security audit →
Playground Template A minimal template for building rich-text editors with Plate and Next.js. Features Next.js 16 Plate editor shadcn/ui MCP Requirements Node.js 20+ bun Installation Choose one of these methods: Using CLI (Recommended) Using Template Use this template, then install dependencies: Development Visit http://localhost:3000/editor to see the editor in action. Upgrade Using the CLI, you can upgrade to by running:
| Stars | 59 |
| Forks | 15 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 62.5256027129714/100 |
| Last Updated | 2026-10-03 |
| Created | 2023-09-14 |
| Platforms | mcp, python |
| Est. Tokens | ~13k |
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plate-template is Minimal Plate template with React 19, Next 16, Tailwind 4, MCP.. It is categorized as a MCP Server with 59 GitHub stars.
plate-template is primarily written in Python. It covers topics such as editor, mcp, nextjs.
You can find installation instructions and usage details in the plate-template GitHub repository at github.com/udecode/plate-template. The project has 59 stars and 15 forks, indicating an active community.
plate-template is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to plate-template on Agent Skills Hub include domainstack.io, Kokoro-Engine, mcp-gearbox. 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: