by hadihonarvar · Claude Skill · ★ 56
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Flock Self-hosted AI for your team. One endpoint. Your hardware. flockllm.com · GitHub · Maintained by Hadi Honarvar Nazari · Apache-2.0 Flock is the self-hosted control plane for LLMs. One Go binary turns your Macs and Linux boxes into a private inference cluster — multi-machine routing, per-user keys, daily quotas, full audit log, and a built-in admin dashboard, behind one endpoint that speaks both the OpenAI and Anthropic APIs. Engine-agnostic: bring Ollama, vLLM, MLX-LM, or llama.cpp-RPC. Run open-weight models (Qwen, Llama, DeepSeek, …) on your own hardware, shard a giant model across several machines via llama.cpp-RPC, and transparently fall back to paid Claude / GPT only when you
| Stars | 56 |
| Forks | 1 |
| Language | Go |
| Category | Claude Skill |
| License | Apache-2.0 |
| Quality Score | 63.926696165146/100 |
| Last Updated | 2026-07-05 |
| Created | 2026-06-05 |
| Platforms | claude-code, go |
| Est. Tokens | ~27k |
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flock is Self-hosted LLM gateway. One Go binary turns your Macs and Linux boxes into a private inference cluster — multi-machine routing, sharding via llama.cpp-RPC, per-user keys + quotas + audit, OpenAI- and. It is categorized as a Claude Skill with 56 GitHub stars.
flock is primarily written in Go. It covers topics such as ai-gateway, aider, anthropic.
You can find installation instructions and usage details in the flock GitHub repository at github.com/hadihonarvar/flock. The project has 56 stars and 1 forks, indicating an active community.
flock is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to flock on Agent Skills Hub include open-jet, Deskdrop, captain-claw. 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: