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 caliber-ai-org · MCP Server · ★ 1.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-setup safe to install? View the security audit →
Caliber Hand-written files go stale the moment you refactor. Your AI agent hallucinates paths that no longer exist, misses new dependencies, and gives advice based on yesterday's architecture. Caliber generates and maintains your AI context files (, , , ) so they stay accurate as your code evolves — and keeps every agent on your team in sync, whether they use Claude Code, Cursor, Codex, OpenCode, or GitHub Copilot. Before / After M
| Stars | 1,275 |
| Forks | 123 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.8586244075067/100 |
| Open Issues | 18 |
| Last Updated | 2026-09-19 |
| Created | 2026-03-10 |
| Platforms | claude-code, cli, codex, mcp, node |
| Est. Tokens | ~18k |
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ai-setup is Continuously sync your AI setups with one command. Codebase tailor suited agent skills, MCPs and config files for Claude Code, Cursor, and Codex.. It is categorized as a MCP Server with 1.3k GitHub stars.
ai-setup is primarily written in TypeScript. It covers topics such as agent-config, ai-agents, anthropic.
You can find installation instructions and usage details in the ai-setup GitHub repository at github.com/caliber-ai-org/ai-setup. The project has 1.3k stars and 123 forks, indicating an active community.
ai-setup is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-setup on Agent Skills Hub include Unity-MCP, claude-code-plugins-plus-skills, agnix. 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: