by plannotator · Codex Skill · ★ 151
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The self-hosted, open-source alternative to Claude Code artifacts.
| Stars | 151 |
| Forks | 8 |
| Language | TypeScript |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 62.5456891091103/100 |
| Open Issues | 14 |
| Last Updated | 2026-09-14 |
| Created | 2026-08-24 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~13k |
These tools work well together with artifact-server for enhanced workflows:
Looking for a artifact-server alternative? If you're comparing artifact-server with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
将 AI 命令行工具以最为原生的方式,集成到微信 ClawBot / 企业微信 bot 中,目前支持集成 Codex、Claude Code、OpenCode、Pi Agent。 支持微信和本地终端线程(thread/s
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Code from anywhere — Telegram bridge for AI coding agents (Claude Code, Codex, OpenCode, Pi, Gemini CLI, Amp).
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artifact-server is The self-hosted, open-source alternative to Claude Code artifacts.. It is categorized as a Codex Skill with 151 GitHub stars.
artifact-server is primarily written in TypeScript. It covers topics such as agent-artifacts, ai-artifacts, artifacts.
You can find installation instructions and usage details in the artifact-server GitHub repository at github.com/plannotator/artifact-server. The project has 151 stars and 8 forks, indicating an active community.
artifact-server is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to artifact-server on Agent Skills Hub include CLI-WeChat-Bridge, kasetto, vibepod-cli. 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: