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 Nainish-Rai · MCP Server · ★ 2
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-rollback safe to install? View the security audit →
Git-like undo and rollback checkpoints for OpenAI Codex CLI. Snapshot, diff, and restore files before and after Codex edits. MCP server + Codex hooks for an automatic safety net.
| Stars | 2 |
| Forks | 0 |
| Language | JavaScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 56.3968/100 |
| Open Issues | 2 |
| Last Updated | 2026-06-16 |
| Created | 2026-06-09 |
| Platforms | cli, codex, mcp, node |
| Est. Tokens | ~13k |
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agent-rollback is Git-like undo and rollback checkpoints for OpenAI Codex CLI. Snapshot, diff, and restore files before and after Codex edits. MCP server + Codex hooks for an automatic safety net.. It is categorized as a MCP Server with 2 GitHub stars.
agent-rollback is primarily written in JavaScript. It covers topics such as agent-rollback, ai-agent, checkpoint.
You can find installation instructions and usage details in the agent-rollback GitHub repository at github.com/Nainish-Rai/agent-rollback. The project has 2 stars and 0 forks, indicating an active community.
agent-rollback is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-rollback on Agent Skills Hub include codex-rewind, deterministic-agent-control-protocol, kirby-mcp. 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: