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 aicanvas-me · MCP Server · ★ 61
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is aicanvas safe to install? View the security audit →
AI Canvas Finished Components, Not Headless Primitives A growing collection of animated React components and composed page blocks, installed as real source code in your project rather than as a dependency. <img src="assets
| Stars | 61 |
| Forks | 8 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64.1382395239388/100 |
| Last Updated | 2026-09-22 |
| Created | 2026-04-04 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~16k |
These tools work well together with aicanvas for enhanced workflows:
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aicanvas is Open-core registry of animated React components, blocks, design systems, and templates. Real, editable code: install with one shadcn CLI command or let your AI agent pull it over MCP.. It is categorized as a MCP Server with 61 GitHub stars.
aicanvas is primarily written in TypeScript. It covers topics such as ai, claude-code, component-library.
You can find installation instructions and usage details in the aicanvas GitHub repository at github.com/aicanvas-me/aicanvas. The project has 61 stars and 8 forks, indicating an active community.
aicanvas is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to aicanvas on Agent Skills Hub include aicanvas, ui-beats, 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: