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 raphaeltm · Agent Tool · ★ 59
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is simple-agent-manager safe to install? View the security audit →
Run AI coding agents in parallel on your own cloud. Every agent gets its own isolated container on a VM billed to your cloud account — full Linux, Docker + git, reachable in the browser. Run 5 or 500 at once. Try it • Star on GitHub • Documentation • Self-Hosting Guide What You Get Agents in parallel, each in a real environment. Every agent runs in its own isolated Docker container on a VM you own — full Linux, Docker, and git, reachable from any browser. Run a handful or hundreds at once, each in a clean workspace. Bring your own cloud. VMs are provisioned in your own Hetzner, Scaleway, or GCP account and billed directly to you. SAM never stores your cloud provider credentials as platform env vars — they're encry
| Stars | 59 |
| Forks | 7 |
| Language | TypeScript |
| Category | Agent Tool |
| License | AGPL-3.0 |
| Quality Score | 69.6164402513106/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-21 |
| Created | 2026-01-24 |
| Platforms | claude-code, node |
| Est. Tokens | ~15k |
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simple-agent-manager is Run multiple coding agents in parallel on your own cloud VMs.. It is categorized as a Agent Tool with 59 GitHub stars.
simple-agent-manager is primarily written in TypeScript. It covers topics such as acp, ai, claude-code.
You can find installation instructions and usage details in the simple-agent-manager GitHub repository at github.com/raphaeltm/simple-agent-manager. The project has 59 stars and 7 forks, indicating an active community.
simple-agent-manager is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to simple-agent-manager on Agent Skills Hub include mobvibe, ralph-starter, deepcontext-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: