经 AI Skill Hub 精选评估,TangleClaw 获评「推荐使用」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。
AI编程会话协调器,持久tmux会话,多引擎管理,提高开发效率
TangleClaw 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
AI编程会话协调器,持久tmux会话,多引擎管理,提高开发效率
TangleClaw 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
# 方式一:npm 全局安装 npm install -g tangleclaw # 方式二:npx 直接运行(无需安装) npx tangleclaw --help # 方式三:项目依赖安装 npm install tangleclaw # 方式四:从源码运行 git clone https://github.com/Jason-Vaughan/TangleClaw cd TangleClaw npm install npm start
# 命令行使用
tangleclaw --help
# 基本用法
tangleclaw [options] <input>
# Node.js 代码中使用
const tangleclaw = require('tangleclaw');
const result = await tangleclaw.run(options);
console.log(result);
# tangleclaw 配置说明 # 查看配置选项 tangleclaw --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量(覆盖配置文件) export TANGLECLAW_CONFIG="/path/to/config.yml"
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-logo.png?raw=true" alt="TangleClaw logo" width="200"> </p>
<p align="center"> <strong>AI coding session orchestrator</strong> — persistent sessions, multi-engine management, methodology enforcement, mobile access </p>
<p align="center"> <code>claude code</code> · <code>codex</code> · <code>gemini cli</code> · <code>aider</code> · <code>openclaw</code> · <code>tmux</code> · <code>pwa</code> · <code>zero dependencies</code> </p>
<p align="center"> <strong>macOS only</strong> (launchd required for service management) </p>
---
You VPN into your dev machine. You SSH in. You navigate to your project directory, fire up an AI coding agent, and start building. Thirty minutes later your VPN hiccups, or your SSH tunnel drops, or your laptop goes to sleep — and the session is gone. The agent's context, your conversation history, everything. There's no way to reconnect. You SSH back in, start over, and re-explain what you were doing.
TangleClaw was built to fix that. It wraps AI coding sessions in persistent tmux processes so they survive network drops, device switches, and reconnects. Close your laptop at your desk, open your phone on the couch, and pick up the exact same session. The agent never knows you left.
What started as session persistence grew into a full orchestration platform. Once you have persistent sessions, you start wanting a dashboard to manage them. Then you want your development methodology enforced as structural rules, not suggestions the agent can ignore. Then you want engine-native config generated automatically so Claude Code, Codex, Gemini CLI, and Aider all get the same instructions without you maintaining four different config files. Then you want port conflict management across projects, mobile access, idle detection, session wrap protocols.
TangleClaw is all of that — a local platform that sits between you and your AI coding agents, accessible from any browser or phone on your network. Project groups with shared markdown docs, per-session launch-mode selection (from fully interactive to full-autonomy sandboxed), file-based session memory that persists across restarts, a one-click mkcert HTTPS wizard, and a universal project-version detection chain are all wired in.
launchModes launch as before; Claude Code ships with all five wired in.md files on session launch.tangleclaw/memories/ that persists context across AI sessions. The guide is injected into every engine config so Claude, Codex, Gemini, and Aider all read and update it the same way~/.tangleclaw/certs/, and hot-swaps the server to HTTPS with a restart overlay. Required for OpenClaw Web UI device pairing; optional manual-cert and skip paths also supported.tangleclaw/project-version.txt (AI-recorded) → CHANGELOG.md → version.json → package.json. The session wrap re-records it, so the dashboard badge stays honest across any project convention<details> <summary>All features</summary>
node:sqlite and node:testbrew install ttyd)brew install tmux)git clone https://github.com/Jason-Vaughan/TangleClaw.git
cd TangleClaw
./deploy/install.sh
The install script: 1. Checks prerequisites (node 22+, ttyd, tmux) 2. Generates launchd plists with correct paths 3. Installs and loads the services 4. Runs a health check
Access the landing page at http://localhost:3102. On first launch, a setup wizard walks you through configuration — including choosing your projects directory. This is a single folder where all your managed projects live (e.g., ~/Projects). TangleClaw scans this directory, detects existing repos and engines, and lets you attach them as managed projects.
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-screenshots/project%20splash%20screen%20with%20sampele%20cards.png?raw=true" alt="TangleClaw dashboard" width="800"> <br><em>Dashboard — project cards with engine badges, methodology status, git info, and session indicators</em> </p>
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-screenshots/project%20info%20panel%20expanded.png?raw=true" alt="Project info panel" width="800"> <br><em>Project detail panel — engine, methodology, active session, git state, settings, and session management</em> </p>
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-screenshots/porthub-registry%20list%20example.png?raw=true" alt="PortHub registry" width="800"> <br><em>PortHub registry — all port leases grouped by project with conflict detection</em> </p>
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-screenshots/launch%20mode%20selector%20modal.png?raw=true" alt="Launch mode selector" width="480"> <br><em>Launch mode selector — pick per-session permission mode (Interactive / Accept Edits / Plan Only / Auto / Bypass)</em> </p>
<p align="center"> <img src="https://github.com/Jason-Vaughan/project-assets/blob/main/tangleclaw-screenshots/shared%20directories%20and%20files%20between%20groups%20modal.png?raw=true" alt="Shared directories between groups" width="800"> <br><em>Project groups & shared docs — link related projects and share markdown across them with doc locking</em> </p>
Global config lives at ~/.tangleclaw/config.json (auto-created on first run).
Key settings: - serverPort — Landing page server port (code default: 3101, launchd override: 3102) - ttydPort — ttyd terminal port (code default: 3100, launchd override: 3101) - projectsDir — Root directory for managed projects - defaultEngine — Default AI engine for new projects - defaultMethodology — Default methodology template - deletePassword — Optional password for destructive operations - httpsEnabled / httpsCertPath / httpsKeyPath — TLS configuration
Engine profiles: ~/.tangleclaw/engines/*.json Methodology templates: ~/.tangleclaw/templates/
See the Configuration Reference for all fields, types, and defaults.
TangleClaw是一个开源的AI工作流,提供了持久的tmux会话和多引擎管理功能,提高了开发效率,但其使用场景和安装说明需要进一步完善
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。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:TangleClaw 的核心功能完整,质量良好。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | TangleClaw |
| 原始描述 | 开源AI工作流:AI coding session orchestrator — persistent tmux sessions, multi-engine manageme。⭐6 · JavaScript |
| Topics | workflowaiai-agentai-codingaiderclaude-codejavascript |
| GitHub | https://github.com/Jason-Vaughan/TangleClaw |
| License | MIT |
| 语言 | JavaScript |
收录时间:2026-05-23 · 更新时间:2026-05-30 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
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