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 limecloud · MCP Server · ★ 1.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is lime safe to install? View the security audit →
Lime 青柠一下，灵感即来 给中文创作者用的开源 AI 内容工作台 AI content workspace for Chinese creators: desktop writing, research, prompt management, knowledge base, and multi-model workflows. 简体中文 · English · 文档 · 发布记录 · 问题反馈 把资料、灵感、生成、修改和复盘放在一个地方，让一次创作不是一次性聊天，而是一条能继续推进的工作流。 目录 Lime 是什么 你可以用 Lime 做什么 几个创作者会遇到的真实时刻 一次创作可以这样开始 核心工作流 适合谁 如果你在找这些工具 不太适合谁 快速开始 技术栈与平台 常见问题 开源协议 免责声明 Lime 是什么 Lime 是一个开源的 Electron 桌面端 AI 内容工作台，面向中文创作者、品牌运营、研究型写作者和小团队，覆盖 AI 写作、选题研究、素材管理、提示词沉淀、知识库和多模型创作流程。 English summary: Lime is a
| Stars | 1,471 |
| Forks | 207 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 59.8958906044112/100 |
| Open Issues | 12 |
| Last Updated | 2026-09-15 |
| Created | 2025-12-13 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
These tools work well together with lime for enhanced workflows:
Looking for a lime alternative? If you're comparing lime with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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lime is Full-stack AI agent for coding, files, terminals, tools, research, content, multimodal work, and multi-agent workflows.. It is categorized as a MCP Server with 1.5k GitHub stars.
lime is primarily written in TypeScript. It covers topics such as agent, agent-collaboration, agent-harness.
You can find installation instructions and usage details in the lime GitHub repository at github.com/limecloud/lime. The project has 1.5k stars and 207 forks, indicating an active community.
The top alternatives to lime on Agent Skills Hub include hope-agent, tuui, openloomi. 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: