# Osaurus — macOS AI Harness with Sandbox + MCP > Osaurus is a native macOS AI harness for agents, memory, and tools: run local/offline models, start a server/CLI, and expose tools via an MCP server. ## Install Merge the JSON below into your `.mcp.json`: ## Quick Use ```bash brew install --cask osaurus osaurus ui osaurus serve ``` ```json { "mcpServers": { "osaurus": { "command": "osaurus", "args": ["mcp"] } } } ``` ## Intro Osaurus is a native macOS AI harness for agents, memory, and tools—run offline local models or connect to cloud providers, then expose tools via an MCP server. The repo is GitHub-verified at 5,230★ and documents a brew cask install. **Best for:** macOS users who want one harness for agents + memory + tools across local and cloud models **Works with:** macOS Apple Silicon; local/offline models; OpenAI/Anthropic/Ollama-compatible APIs; MCP server mode **Setup time:** 15–30 minutes ### Key facts (verified) - README provides `brew install --cask osaurus` and `osaurus ui/serve/status` commands. - README notes sandboxed execution in an isolated Linux VM on macOS 26+ (Tahoe). - README lists MCP server config snippet: `command: osaurus` with args `["mcp"]`. - GitHub: 5,230 stars · 275 forks; pushed 2026-05-13 (GitHub API verified). ## Main If you are evaluating multiple models/providers, Osaurus helps because the harness (agents + memory + tools) stays constant while models change. A good first week plan: - Install and run the UI + server. - Create one agent with a dedicated working folder. - Turn on the sandbox only for tasks that need shell execution, and keep workloads separated per agent. Once stable, connect an MCP client so your other tools can reuse Osaurus-managed capabilities. ### README excerpt (verbatim)
Own your AI.
Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source.
Download for Mac · Docs · Models · Discord · Twitter · Plugin Registry
--- ## Inference is all you need. Everything else can be owned by you. ### FAQ **Q: Is Osaurus offline?** A: README says it works fully offline with local models, and can also connect to cloud providers when desired. **Q: How do I install it?** A: Install via `brew install --cask osaurus` or download the DMG from GitHub releases. **Q: How do I expose it via MCP?** A: Add an MCP server entry with `command: osaurus` and `args: ["mcp"]` per README. ## Source & Thanks > Source: https://github.com/osaurus-ai/osaurus > License: MIT > GitHub stars: 5,230 · forks: 275 --- ## 快速使用 ```bash brew install --cask osaurus osaurus ui osaurus serve ``` ```json { "mcpServers": { "osaurus": { "command": "osaurus", "args": ["mcp"] } } } ``` ## 简介 Osaurus 是原生 macOS 的 AI harness:集成 agent、记忆与工具,可离线跑本地模型或连接云端 provider,并通过 MCP server 暴露工具。仓库 GitHub 已验证 5,230★,并提供 brew cask 安装。 **最适合:** 想在 macOS 上用一个 harness 统一管理 agent、记忆与工具,并在本地/云模型间切换的用户 **适配:** macOS Apple Silicon;本地/离线模型;兼容多家 API;支持 MCP server 模式 **配置时间:** 15–30 分钟 ### 关键事实(已验证) - README 提供 `brew install --cask osaurus`,以及 `osaurus ui/serve/status` 命令。 - README 提到在 macOS 26+ 上可用隔离 Linux VM 作为沙箱执行环境。 - README 给出 MCP server 配置片段:`command: osaurus` + `args: ["mcp"]`。 - GitHub:5,230 stars · 275 forks;最近更新 2026-05-13(GitHub API 验证)。 ## 正文 当你在评估多个模型/Provider 时,Osaurus 的价值在于:模型可以换,但 harness(agent + 记忆 + 工具)不变。 建议第一周按步骤落地: - 安装并启动 UI + server。 - 创建一个带独立工作目录的 agent。 - 只有在需要执行 shell/编译等任务时再开启沙箱,并按 agent 维度隔离工作负载。 稳定后,再把它作为 MCP server 接入其他客户端,让你的工具链复用 Osaurus 的能力。 ### README 原文节选(verbatim)
Own your AI.
Agents, memory, tools, and identity that live on your Mac. Built purely in Swift. Fully offline. Open source.
Download for Mac · Docs · Models · Discord · Twitter · Plugin Registry
--- ## Inference is all you need. Everything else can be owned by you. ### FAQ **Osaurus 能离线用吗?** 答:README 表示可完全离线运行本地模型,也可在需要时连接云端 provider。 **怎么安装?** 答:按 README:`brew install --cask osaurus`,或从 GitHub Releases 下载 DMG。 **如何以 MCP 暴露?** 答:按 README:配置 `command: osaurus` 与 `args: ["mcp"]`。 ## 来源与感谢 > Source: https://github.com/osaurus-ai/osaurus > License: MIT > GitHub stars: 5,230 · forks: 275 --- Source: https://tokrepo.com/en/workflows/osaurus-macos-ai-harness-with-sandbox-mcp Author: MCP Hub