KaozKit: sandboxed LLM agents in JS, fully on-device on Apple Silicon (MLX / Apple Intelligence / Ollama), MIT

I released KaozKit this week, a Swift library for running LLM agents written in JavaScript inside a Mac app. Built from the start to keep everything local. Providers: MLX with Hugging Face model management built in, Apple Intelligence using the on-device model (no key, no network), plus Ollama and LM Studio if that's your setup. Cloud providers exist too but the point was to not need them. The README demo is an agent that audits your Downloads folder on Apple's local model with zero config. An agent is a JS module of about ten lines. It runs inside XS, a JavaScript engine originally built for microcontrollers, which is why one isolated engine per agent costs almost nothing and you ship neither Node nor Python. What I spent the most time on is what an agent can't do. No fetch, no fs, no ambient anything: it only sees the host functions you hand it. File access is per authorized folder, and anything that acts (shell, HTTP, writes) is opt-in with allow-lists. API keys never reach the JS side. XS also does heap snapshots. The engine dumps its whole heap to disk, so a resident agent, state, conversation and pending timers included, comes back after a restart exactly where it was, with no serialization code on my side. macOS 26+, Apple Silicon, MIT. https://github.com/sebastien-burel/KaozKit Longer write-up on why a microcontroller JS engine turned out to be a good agent runtime: https://www.haruni.net/en/blog/kaozkit-xs-agents Question for people running agents locally: what's your runtime today, and what would it take for you to trust one enough to leave it resident? Sandboxing, auditability, something else? submitted by /u/sburel [link] [comments]

Source: r/ollama | 2026-09-17

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