No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by NanmiCoder · MCP Server · ★ 14.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cc-haha safe to install? View the security audit →
Claude Code Haha English · 简体中文 Claude Code Haha is a desktop Claude Code workspace for macOS, Windows, and Linux: sessions, projects, branch / Worktree launch, workspace changes and diff review, permission approval, model setup, Computer Use, H5 remote access, IM integration, and scheduled tasks in one app.
| Stars | 14,671 |
| Forks | 8,582 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64.3510561344544/100 |
| Open Issues | 178 |
| Last Updated | 2026-09-22 |
| Created | 2026-03-31 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~17k |
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cc-haha is Local-first cross-platform desktop workspace for Claude Code / agents: multi-agent, Git worktrees, code diffs, skill marketplace, multi-model, Computer Use, task-aware desktop pets, with WeChat, Feish. It is categorized as a MCP Server with 14.7k GitHub stars.
cc-haha is primarily written in TypeScript. It covers topics such as agent, ai, ai-agent.
You can find installation instructions and usage details in the cc-haha GitHub repository at github.com/NanmiCoder/cc-haha. The project has 14.7k stars and 8582 forks, indicating an active community.
cc-haha is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to cc-haha on Agent Skills Hub include oh-my-pi, ai-guide, bytebot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: