Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zhouxiaoka · MCP Server · ★ 9.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is autoclip safe to install? View the security audit →
AutoClip - 视频高光切片自动化工具 支持YouTube/B站视频下载、自动切片、智能合集生成 语言: English | 中文 🎯 项目简介 AutoClip是一个基于AI的智能视频切片处理系统,能够自动从YouTube、B站等平台下载视频,通过AI分析提取精彩片段,并智能生成合集。系统采用现代化的前后端分离架构,提供直观的Web界面和强大的后端处理能力。 ✨ 核心特性 🎬 多平台支持: YouTube、B站视频一键下载,支持本地文件上传 🤖 AI智能分析: 基于通义千问大语言模型的视频内容理解 ✂️ 自动切片: 智能识别精彩片段并自动切割,支持多种视频分类 📚 智能合集: AI推荐和手动创建视频合集,支持拖拽排序 🚀 实时处理: 异步任务队列,实时进度反馈,WebSocket通信 🎨 现代界面: React + TypeScript + Ant Design,响应式设计 📱 移动端支持【开发中】: 响应式设
| Stars | 9,189 |
| Forks | 1,677 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 60.9869981857473/100 |
| Open Issues | 7 |
| Last Updated | 2026-10-06 |
| Created | 2025-07-08 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~17k |
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autoclip is AutoClip|一个链接,一键出片。开源 AI 视频剪辑桌面工具,将播客、访谈、课程等长视频自动剪成短视频,生成字幕、封面和发布文案,适配抖音、小红书、TikTok、Reels 与 YouTube Shorts。Open-source AI video clipping & content repurposing.. It is categorized as a MCP Server with 9.2k GitHub stars.
autoclip is primarily written in Python. It covers topics such as ai-agent, ai-video-editor, content-repurposing.
You can find installation instructions and usage details in the autoclip GitHub repository at github.com/zhouxiaoka/autoclip. The project has 9.2k stars and 1677 forks, indicating an active community.
autoclip is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to autoclip on Agent Skills Hub include OpenChatCut, open-cowork, chatgpt-on-wechat. 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: