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 dmitryryabkov · Agent Tool · ★ 70
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is local-ai-mac safe to install? View the security audit →
Running (and coding with) Local AI on a Mac This is a comprehensive guide on how to run AI models and coding agents locally on a Mac. I gathered various bits and pieces of information scattered across the internet into a single resource. If you have a spare Mac lying around, you can turn it into an “LLM server” and use it instead of paying for OpenAI, Claude, etc. You’ll need a decent amount of RAM for this to work. Around 32GB is where things start getting interesting. I’m currently running 30B-class models with the same 128K context window as OpenAI Codex on an M3 MacBook Pro with 36GB of RAM — all locally. ⚠️ This guide assumes familiarity with LLM concepts, inference engines, and basic system configuration. It is a good starting point for anyone who is building local AI systems or is experimenting with agent workflows. Why? Because it works — and surprisingly well. But more importantly: there are cost and privacy benefits of running AI locally. The architecture of Apple’s M-series chips suits this type of workload. AI models benefit from GPUs with access to large amounts of memory.
| Stars | 70 |
| Forks | 5 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 57.1620626204335/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-13 |
| Created | 2026-04-02 |
| Platforms | claude-code |
| Est. Tokens | ~23k |
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local-ai-mac is Practical guide to running LLMs locally on Apple Silicon, with a focus on architecture, memory scaling, and agent workflows.. It is categorized as a Agent Tool with 70 GitHub stars.
You can find installation instructions and usage details in the local-ai-mac GitHub repository at github.com/dmitryryabkov/local-ai-mac. The project has 70 stars and 5 forks, indicating an active community.
local-ai-mac is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to local-ai-mac on Agent Skills Hub include maclocal-api, SAM, ovo-local-llm. 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: