goose vs Happy
Side-by-side comparison of two AI agent tools
Short answer
- goose is growing faster: +3,352 GitHub stars in the last 30 days vs +1,196 for Happy.
- Pick goose for: an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test. Pick Happy for: mobile and Web client for Codex and Claude Code, with realtime voice, encryption and fully featured.
From GitHub data refreshed daily.
gooseopen-source
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
Happyopen-source
Mobile and Web client for Codex and Claude Code, with realtime voice, encryption and fully featured
Metrics
| goose | Happy | |
|---|---|---|
| Stars | 54.9k | 24.0k |
| Star velocity /mo | 3.4k | 1.2k |
| Commits (90d) | 805 | 322 |
| Releases (6m) | 10 | 10 |
| Downloads (30d, npm + PyPI) | — | 35.1K |
| Overall score | 0.8821825173304099 | 0.8295861408886525 |
Pros
- +支持任何LLM模型且可多模型配置，灵活性极高
- +能够自主完成端到端开发任务，不仅仅是代码建议
- +开源架构支持自定义扩展和MCP服务器集成
- +提供完整的移动端访问能力，支持 iOS、Android 和 Web 平台
- +端到端加密保护代码安全，开源架构支持代码审计
- +无缝设备切换体验，一键在手机和桌面间转换控制权
Cons
- -需要本地安装和配置，对新手用户可能有一定门槛
- -作为自主代理执行任务时可能需要用户监督和验证结果
- -需要安装额外的 CLI 包装器，增加了系统复杂度
- -依赖网络连接进行远程通信，可能受网络状况影响
- -作为第三方工具，需要额外的配置和维护工作
Use Cases
- •从零开始构建完整项目原型，包括代码编写和测试
- •对现有代码库进行重构和优化改进
- •管理复杂的工程流水线和自动化开发工作流
- •外出时通过手机监控长时间运行的 AI 编程任务
- •在多设备间灵活切换，随时随地查看代码生成进度
- •团队协作场景下的远程代码审查和实时监控
FAQ
- Which is more popular, goose or Happy?
- goose has more GitHub stars (54,890 vs 23,993).
- Which is more actively developed, goose or Happy?
- goose had more commits in the last 90 days (805 vs 322).
- Should I use goose or Happy?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.