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 ZhuLinsen · MCP Server · ★ 190
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MiniAgent safe to install? View the security audit →
MiniAgent 🚀 5分钟手搓一个 AI Coding 助手 + 命令行版 Manus！ | English 💡 核心特性 一个 核心文件，复刻 Claude Code 的编程能力 + Manus 的系统操控能力！ MiniAgent 是一个极简、透明、强大的 CLI Agent 框架，拒绝臃肿的依赖和复杂的架构： 🧠 Code Agent: 像 Claude Code 一样写代码、修 Bug、跑测试 🦾 OS Agent: 像 Manus 一样操控浏览器、编辑文档、管理应用 ⚡ 极简实现: 核心引擎 完全透明可控，适合学习和魔改 🤖 全模型支持: DeepSeek、OpenAI、Gemini、Claude 等所有兼容 OpenAI 接口的模型 🔌 高扩展性: 极简装饰器模式，3行代码即可挂载自定义工具 🔄 双模式工具调用: 文本解析模式（透明可学习）+ 原生 Function Calling 模式（更可靠） 🎯 Skill 系统: 可复用的 Agent 配置，内置 coder/researcher/reviewer/tester 四个角色 🛡️ 安全防护: 危险命令自动拦截确认，防止 LLM 幻觉导致破坏性操作 💬 流式输出: 打字机效果实时输出，长对话自动压缩上下文 🔗 MCP 协议: 支持连接 MCP 工具服务器，接入社区生态 🤝 Agent 编排: 内置编排器，支持任务分解 + 多角色协同 🤔 Why MiniAgent? | OS 控制
| Stars | 190 |
| Forks | 41 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 63.8274053853193/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-12 |
| Created | 2025-04-27 |
| Platforms | claude-code, cli, mcp, python |
| Est. Tokens | ~15k |
These tools work well together with MiniAgent for enhanced workflows:
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MiniAgent is 🚀「 5分钟手搓一个 AI Coding 助手 + 命令行版 Manus」 ⚡️Build an AI Coding Assistant + CLI-based Manus in 5 Minutes!. It is categorized as a MCP Server with 190 GitHub stars.
MiniAgent is primarily written in Python. It covers topics such as agent, claude, claudecode.
You can find installation instructions and usage details in the MiniAgent GitHub repository at github.com/ZhuLinsen/MiniAgent. The project has 190 stars and 41 forks, indicating an active community.
MiniAgent is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to MiniAgent on Agent Skills Hub include argo, wcgw, oreilly-ai-agents. 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: