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 Justin0504 · MCP Server · ★ 92
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Sovereign-OS safe to install? View the security audit →
Featured in: Agent Governance
A governed AI workforce, ready to deploy on day one. Submit a goal — Sovereign-OS plans it, approves the budget, executes with built-in workers, and delivers a cryptographically verified result. Quick Start • Architecture • Features • Deployment • Configuration • Custom Workers • Docs Overview Sovereign-OS is not another chatbot wrapper or agent framework. It is an operating system for autonomous AI work: a governance layer that enforces budget, quality, and permissions before any token
| Stars | 92 |
| Forks | 13 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 65.4470886774065/100 |
| Last Updated | 2026-09-17 |
| Created | 2026-03-04 |
| Platforms | mcp, python |
| Est. Tokens | ~17k |
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Sovereign-OS is Constitution-first AI orchestration: one Charter (YAML) defines mission, budget & rules. CEO plans → CFO approves → Ledger tracks every cent & token → Auditor scores. 16 workers, Stripe, MCP. Think. A. It is categorized as a MCP Server with 92 GitHub stars.
Sovereign-OS is primarily written in Python. It covers topics such as agent-framework, ai-agents, audit-trail.
You can find installation instructions and usage details in the Sovereign-OS GitHub repository at github.com/Justin0504/Sovereign-OS. The project has 92 stars and 13 forks, indicating an active community.
The top alternatives to Sovereign-OS on Agent Skills Hub include OmoiOS, DashClaw, vizra-adk. 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: