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omux

基于 TypeScript · 让 AI 助手直接操作你的系统与工具
⭐ 106 Stars 🍴 2 Forks 💻 TypeScript 📄 未公布协议 🏷 AI 8.0分
8.0AI 综合评分
mcpagent-orchestratorai-agentsautonomous-agentsclaude-code
✦ AI Skill Hub 推荐

omux 是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。

📚 深度解析

omux 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 omux,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。omux 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 omux 评为 AI 评分 8.0 分,属于同类工具中的优质选择。

📋 工具概览

omux 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 106
开发语言
TypeScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
未公布
AI 综合评分
8.0 分
工具类型
MCP工具
Forks
2

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

omux 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/Happenmass/omux

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "omux": {
      "command": "npx",
      "args": ["-y", "omux"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 omux 执行以下任务...
Claude: [自动调用 omux MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "omux": {
      "command": "npx",
      "args": ["-y", "omux"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 45/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

简介

Install

Requires Node 20+ and tmux.

```bash

Demo

omux demo — click to play

Click the thumbnail to play the demo (~70 MB MP4).

Configure

Minimum config:

{
  "defaultAgent": "claude-code",
  "llm": {
    "provider": "anthropic",
    "model": "claude-sonnet-4-6",
    "apiKey": "sk-..."
  }
}

Or run omux config for an interactive TUI. Environment variables (ANTHROPIC_API_KEY, OPENAI_API_KEY, …) are read as fallbacks. To run Claude Code and Codex side by side, add "enabledAgents": ["claude-code", "codex"] — the MainAgent only ever launches adapters in that list.

Supported LLM providers: OpenAI, Anthropic, OpenRouter, DeepSeek, Gemini, Groq, Mistral, xAI (Grok), Together, Moonshot (Kimi), MiniMax, Ollama.

FAQ

Does omux decide which CLI agent to use for a task? Within the adapters you've enabled, yes. The MainAgent sees every active adapter and its characteristics (listed under "Agent Capabilities" in its prompt) and picks per task by fit — lead with Codex for gnarly single-point reasoning and deep debugging, lean Claude Code for broad multi-file work and tight edit→test→rerun loops, then have the other one review (see the execute-then-review FAQ below). If you've enabled only one adapter there's nothing to choose — it just runs that. The menu is always exactly the adapters you turned on: it never silently pulls in a tool you didn't enable. Roles aren't hard-wired — either can implement, either can review; the implement/review split is a heuristic, not a fixed division of labor.

Can I run Claude Code and Codex together? Yes — as of v3.0.0 it's a headline feature. Enable both adapters and omux runs an execute-then-review loop in a single session: Claude Code implements, then a separate Codex agent independently reviews the diff — correctness, edge cases, regressions — and routes fixes back. They stay distinct agents you address individually, and the roles are interchangeable: either can implement, either can review. The default heuristic is Claude-implements / Codex-reviews; you override per task. (Want two fully independent sessions instead? Run two omux instances on different ports.)

Why scope MCPs per-agent instead of globally? Because tool-soup hurts. Every MCP you load injects its tool descriptions into the system prompt of every agent that has it enabled. A docs agent doesn't need your Postgres MCP, and the LLM gets distracted by tools it'll never call. omux lets you give each agent a focused toolset — smaller prompts, faster decisions, no name collisions. Per-agent skill scoping is on the way next.

Why two-tier memory (global + project)? Some things you teach an agent are about you — your coding style, your tone, your colleagues' names. Re-teaching that every time you cd into a new repo is wasteful. Other things are about this codebase — its conventions, its open todos, its architectural quirks — and shouldn't bleed into unrelated projects. omux splits memory into both layers and searches them together. Both run on the same hybrid-search index and the same editing tools, so the experience is identical at either level.

Can I change the context window size? You usually don't have to — omux derives the window from the model id (claude → 200k, gemini / gpt-4.1 → 1M, 500k fallback for unrecognized models). To override: --context-window at launch, or context.contextWindowLimit in ~/.omux/config.json. omux watches usage and auto-compresses (or flushes to memory) when you cross the threshold, so you can match the window to your model and budget without babysitting it.

Why tmux and not the Anthropic SDK / OpenAI Assistants API? Because the experience of Claude Code or Codex is not in their API — it's in their TUI. The interactive confirmations, the step-by-step reasoning, the "here's what I'm about to do" preview — all of that is TUI output. Wrapping the API strips it. Driving the TUI keeps it, and as a bonus you get compatibility with any CLI agent that ever ships.

How does state detection work across agents that update their UI differently? Each adapter declares its own regex patterns. When Claude Code 2026.04 changes its prompt format, you edit one file. The core orchestrator doesn't know or care.

Does omux need its own API key? Yes — one, for the MainAgent's reasoning. The coding agents use whatever keys they already use. You pay twice in tokens but the MainAgent's traffic is much smaller than the coding agents'.

Can I chat in one language while the agents work in another? Yes. omux auto-detects your locale (or you can set locale in ~/.omux/config.jsonzh-CN and en-US are supported today) and uses it for the chat UI and the MainAgent's replies to you. The briefs the MainAgent writes into the coding agents are a separate, steerable channel: tell it once to brief sub-agents in English and it will — so you can read and write in Chinese while Claude Code or Codex gets briefed in English (or any combination). Useful if you think faster in your native language but want the coding agent's reasoning trace to stay in the language its training data is densest in.

Can I run this on a remote server? Yes. tmux is designed for detached sessions. SSH in, start omux, detach, come back hours later, pick up where you left off. This is actually the main mode I use it in.

Can I grab the wheel while an agent is mid-run? Yes. Any agent pane can be taken over from the web UI: you get the live terminal, your keystrokes go straight in, and the MainAgent keeps its hands off that agent until you release it back. For lighter touches, /stop halts the MainAgent between rounds — and it can itself interrupt a sub-agent it catches going off-track.

What happens if the omux server dies mid-task? Less than you'd fear. Sub-agents live in tmux, not in the server process — they keep working right through a server crash or restart. On startup omux re-adopts running omux-* (and legacy cliclaw-*) sessions, restores the conversation from SQLite, and repairs any tool call that was interrupted mid-flight.

Why "omux"? orchestrate × tmux — the orchestrator that lives where your agents live. (omux is the new name of cliclaw.)

🎯 aiskill88 AI 点评 A 级 2026-07-06

omux是一个有趣的项目,实现了AI编码代理的编排

⚡ 核心功能

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 未明确开源协议,商用场景需谨慎评估
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

该工具未明确声明开源协议,商业使用前请联系原作者确认授权范围,避免侵权风险。

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

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❓ 常见问题 FAQ

omux是开源MCP工具,用于编排AI编码代理
💡 AI Skill Hub 点评

经综合评估,omux 在MCP工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。

⬇️ 获取与下载
⚠️ 该工具未声明开源协议,不提供直接下载。请访问原项目了解使用条款。
📚 深入学习 omux
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 omux
Topics mcpagent-orchestratorai-agentsautonomous-agentsclaude-code
GitHub https://github.com/Happenmass/omux
语言 TypeScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/Happenmass/omux

收录时间:2026-07-06 · 更新时间:2026-07-06 · License:未公布 · AI Skill Hub 不对第三方内容的准确性作法律背书。

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