AIエージェント
osaurus
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
★ 8.0k スターMIT
ガイドを見る →macos-harnessは、browser-useが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: browser-use/macos-harness）。GitHubスターは902、フォークは61で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年8月17日です。
A minimal harness that lets an LLM fully control a Mac.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Accessibility APIs drive real apps.
Thin on purpose - easy to understand.
Bring your own model.
OS-level, not just browser-level.
Free to hack on.
Built by agent-infra veterans.
Download the source and move into the project folder.
git clone https://github.com/browser-use/macos-harness.git
cd macos-harnessCreate a virtual environment and install the requirements.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtTreat these as starting points - the README documents the exact commands.
python examples/quickstart.pyIt is an open-source project at browser-use/macos-harness with 61 forks. Check the repo's contributors and recent commits to judge how active maintenance is.
Yes - it is MIT licensed, so you can use, modify, and distribute it freely, including in commercial projects.
The harness is free; the model driving it is usually a paid API or a local model.
It gives an LLM full control of your Mac - run it in a VM or a spare machine, never on your daily driver with sensitive data. Treat it as research tooling.
Clone the repo, read the README's quickstart, and run the provided example - most projects get you to a first result in minutes.
Osaurus — own your AI: a native macOS agent harness with any model, memory and fully offline execution.
A self-healing harness that connects an LLM directly to your real browser
Control Android and iOS devices with natural language — an LLM-agnostic mobile agent framework and CLI.
The open-source library that lets AI agents control a real browser.
An MCP server and CLI that lets AI agents build, test and run iOS and macOS projects.
FIRERPA / LAMDA — full-stack Android device control: remote desktop, automation, MITM, Frida and MCP.
LibreAIカタログに掲載されたAIエージェントプロジェクトの中で最もスターの多いもの — macos-harnessが合わなかった場合に検討したい、現実的な候補リストです。
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
カタログの中でmacos-harnessとスター数が近いAIエージェントプロジェクト — 前後の棚もそのまま見て回れます。
A self-improving QA agent that writes tests in plain English.
Test your agents against prompt-injection attacks.
A memory and retrieval server built for LLMs.
SimWorld: an Unreal Engine 5 simulator for evaluating LLM/VLM agents in physical and social worlds.
An enterprise MCP gateway: governed, auditable tool access for agents.
An MCP server that puts Hyperbrowser's browsers behind the protocol.