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 icekale · MCP Server · ★ 74
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rednote-downloader safe to install? View the security audit →
RedNote Downloader Service 中文 | English 一个面向 Docker / Unraid 部署的自托管多平台媒体下载器，支持 RedNote / 小红书、 / ，以及抖音单视频链接或分享文案。它提供 Web UI、浏览器预览、本地代理下载、服务端保存和 Telegram 回传。 从 开始，Docker 镜像内置 REST 服务。抖音单视频可以在同一个容器内完成解析与服务端下载，不需要再额外部署 Python 下载器。 主要功能 小红书 / RedNote：支持分享文案、 / 短链和页面链接解析下载。 X / Twitter：支持帖子图片、视频媒体解析和代理下载。 抖音：支持单视频分享文案、短链和 ，Docker 镜像内置下载器，默认单容器可用。 Web UI：输入链接即可预览图片/视频，支持浏览器代理下载和服务端保存。 Telegram：可选配置 bot，把解析到的媒体回传到指定聊天。 Unraid / Docker：使用 挂载保存配置和下载结果， 与 分平台保存，Cookie 不写入镜像。 能力边界 抖音第一版只支持单视频，不支持图文、主页、合集、音乐、收藏、直播或批量主页下载。 “去水印”定义为优先选择平台返回的无水印或低水印视频源；如果只能拿到疑似带水印候选，会返回 warning 并仍允许下载。 服务不会对媒体做转码、压缩、裁剪或 OpenCV/ffmpeg 水印擦除。 如果目标站点返回验证码、风控页，或者没有暴露可用媒体地址，服务会直接报错。 Docker 镜像默认内置 REST 服务，用于抖音服务端下载；Cookie 只在运行时通过 Web UI 或环境变量传入，不会写入镜像。 API 健康检查。 请求体： 返回： 时返回解析出的媒体信息。 时把文件保存到 ，并返回保存路径。 批量输入支持一行一个链接，返回 和 。 代理下载远端媒体或允许目录内的本地媒体。 常见参数： : 远端媒体 URL。 : 可重复传入的备用媒体 URL。 : 本地媒体绝对路径，必须位于允许目录内。 : 下载文件名。
| Stars | 74 |
| Forks | 13 |
| Language | JavaScript |
| Category | MCP Server |
| Quality Score | 66.4264290736013/100 |
| Last Updated | 2026-09-16 |
| Created | 2026-03-18 |
| Platforms | docker, mcp, node |
| Est. Tokens | ~14k |
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rednote-downloader is Self-hosted RedNote, X/Twitter, and Douyin downloader for Docker/Unraid.. It is categorized as a MCP Server with 74 GitHub stars.
rednote-downloader is primarily written in JavaScript. It covers topics such as docker, mcp, openclaw.
You can find installation instructions and usage details in the rednote-downloader GitHub repository at github.com/icekale/rednote-downloader. The project has 74 stars and 13 forks, indicating an active community.
The top alternatives to rednote-downloader on Agent Skills Hub include mcp-server-code-execution-mode, JoySafeter, human-mcp. 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: