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 openlegion-ai · MCP Server · ★ 116
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openlegion safe to install? View the security audit →
The secure AI agent runtime for builders who can't afford a security incident. []() Run autonomous, self-hosted AI agent fleets that are isolated, auditable, and production-ready. Every agent runs in its own Docker container, API keys never leave the credential vault, and per-agent budgets cap spend. A source-available, security-first OpenClaw alternative for teams. Chat via Telegram, Discord, Slack, or WhatsApp. 100+ LLM providers via LiteLLM. [What is OpenLegio
| Stars | 116 |
| Forks | 26 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 64.8346705759243/100 |
| Open Issues | 5 |
| Last Updated | 2026-08-23 |
| Created | 2026-02-19 |
| Platforms | docker, mcp, python |
| Est. Tokens | ~25k |
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openlegion is Secure autonomous AI agent framework and platform. Build AI teams by describing what you want. Orchestrate agents that can do everything a human can do.. It is categorized as a MCP Server with 116 GitHub stars.
openlegion is primarily written in Python. It covers topics such as agent-framework, agent-orchestration, agentic-ai.
You can find installation instructions and usage details in the openlegion GitHub repository at github.com/openlegion-ai/openlegion. The project has 116 stars and 26 forks, indicating an active community.
The top alternatives to openlegion on Agent Skills Hub include Network-AI, captain-claw, mate. 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: