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 av · MCP Server · ★ 3.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is harbor safe to install? View the security audit →
https://github.com/user-attachments/assets/e4897391-c5a8-4391-93c3-9f8b76155f11 [](https://textclip.sh?ask=claude#c=TZTNjiM1EIDveQofga2N4LJCkQZpZ2AAaVZCzBNU29XdtSm7PLY7P2QjjYQUshyjleC6J8S8Bnd4h34S5E4GcbH6p7r8lb-qg5To2l8Hm7vvx-PQ6xsXXapeUbtRHzTQeTqIW5e7ujRni-OvPa2oGfqEi6PEFpm41m39YfETJX1pNbTcjcfHNScOnfnCejceTu0gkgvapcGhTFGBbBmPj7truIX7vYlJWxa6X2M09La-O5xyweBQNJApQwgk4-HEoVAKVMxDGg8nrw0LmfH4p0Xbknn8ZOK86npORfz122XIB5dz0en27H49P9u69efT6bXVtzvQwrTZGWIl4KB1DwabZYmTA2Cd1XAg855JQUobcCYYOliVhyK0mTymDeEdRdAvIqWYJtEFYaqPiwKsbBJPHDeRIFTJDxCSU9rdXu-kgQbhJZHssUJf6QJvzfX-hrF9MFw1rYNvFAhi2pefQ1Q1rbGAFz8shogMtlDxY9e124P391S4Tpk3oIFKKQhu2CI7bLUTB
| Stars | 3,218 |
| Forks | 228 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 61.1345081880163/100 |
| Open Issues | 67 |
| Last Updated | 2026-09-21 |
| Created | 2024-07-27 |
| Platforms | cli, docker, mcp, python |
| Est. Tokens | ~20k |
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harbor is Stop configuring your AI stack. Start using it. One command brings a complete pre-wired LLM stack with hundreds of services to explore.. It is categorized as a MCP Server with 3.2k GitHub stars.
harbor is primarily written in Python. It covers topics such as ai, automation, bash.
You can find installation instructions and usage details in the harbor GitHub repository at github.com/av/harbor. The project has 3.2k stars and 228 forks, indicating an active community.
harbor is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to harbor on Agent Skills Hub include bytebot, mcpm.sh, flow-like. 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: