plate: Rich-text editor with AI and shadcn/ui

by udecode · MCP Server · ★ 16.7k

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

Security audit verdict: SAFE · quality 53/100

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. Full audit →

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.

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Quick Facts

Stars16,691
Forks998
LanguageTypeScript
CategoryMCP Server
Quality Score53/100
Open Issues17
Last Updated2026-11-07
Created2019-12-02
Platformsmcp, node
Est. Tokens~14k

About plate

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.

Compatible Skills

These tools work well together with plate for enhanced workflows:

  • fulling — semantic(0.44)+complementary+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • shadcn-ui-mcp-server — semantic(0.42)+shared_fw(react)+rare_topics+same_lang+similar_pop+shared_platform (57%)

plate alternative? Top 6 similar tools

Looking for a plate alternative? If you're comparing plate with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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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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