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 · ★ 16.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is plate safe to install? View the security audit →
Plate [//]: # ' ' [//]: # 'Welcome to Plate, a rich-text editor framework designed for simplicity and efficiency. Plate consists of four main parts:' [//]: # [//]: # "1. Core: This is the heart of Plate. It's a special plugin system just for . We've made sure everything is neat and tidy, so it's easier for you to develop your project." [//]: # '2. Plugins: We give you a big selection of plugin packages. They help make editor behaviors, hooks, serialization, and normalization better, among other things.' [//]: # '3. Primitives: Besides the headless
| Stars | 16,612 |
| Forks | 997 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 53.0550450791736/100 |
| Open Issues | 17 |
| Last Updated | 2026-09-22 |
| Created | 2019-12-02 |
| Platforms | mcp, node |
| Est. Tokens | ~14k |
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plate is Rich-text editor with AI and shadcn/ui. It is categorized as a MCP Server with 16.6k GitHub stars.
plate is primarily written in TypeScript. It covers topics such as ai, mcp, react.
You can find installation instructions and usage details in the plate GitHub repository at github.com/udecode/plate. The project has 16.6k stars and 997 forks, indicating an active community.
The top alternatives to plate on Agent Skills Hub include ai-website-cloner-template, sim, open-saas. 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: