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 solomon2773 · MCP Server · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is nora safe to install? View the security audit →
Nora The self-hosted AI agent ops platform. Deploy, monitor, and operate OpenClaw and Hermes runtimes from one operator surface — runtime-neutral, Apache 2.0, and on infrastructure you control. Run agents on Docker or Kubernetes today, use NemoClaw sandboxes experimentally, and track Proxmox as a planned execution target. 📚 Documentation · Quick Start · Self-Hosting · Architecture · How Nora Compares · Changelog · Public
| Stars | 50 |
| Forks | 13 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66.1246766723722/100 |
| Open Issues | 7 |
| Last Updated | 2026-09-07 |
| Created | 2026-03-19 |
| Platforms | claude-code, cli, docker, k8s, mcp, node |
| Est. Tokens | ~17k |
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nora is Open-source, self-hosted control plane for OpenClaw and Hermes AI-agent fleets on Docker/Kubernetes — REST, CLI, and MCP.. It is categorized as a MCP Server with 50 GitHub stars.
nora is primarily written in TypeScript. It covers topics such as agent-management, agent-ops, agent-orchestration.
You can find installation instructions and usage details in the nora GitHub repository at github.com/solomon2773/nora. The project has 50 stars and 13 forks, indicating an active community.
nora is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to nora on Agent Skills Hub include openlegion, awesome-agentic-devops, Network-AI. 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: