Go 语言编写的 Emby + OpenList (Alist) 网盘直链反向代理服务，深度适配阿里云盘转码播放，支持 OpenList 本地目录树生成，配置简单，DockerCompose 一键部署

一个媒体库 STRM 文件生成工具。和 Emby 优雅配合，媒体资源丝滑入库，支持 302 直链播放，支持同步删除。 配合 Quark-Auto-Save, CloudSaver, Emby 力求即存即看。🥳

A little script to serve Youtube / Twitch / Crunchyroll videos without storage it. Uses yt-dlp HTTP data throught Flask and dynamic URLs. We can use this dynamic URLs to set STRM files.

CloudPan189 Share 是一款专为天翼云盘设计的智能文件分享管理工具。该系统能够将天翼云盘的分享链接转换为标准的目录结构，并通过 WebDAV 协议提供统一的文件访问接口。

Mounts your TorBox account to your local system for use with external applications.

一个为OpenList提供媒体文件Strm生成服务的工具

Emby Strm 插件，支持strm直链，媒体信息持久化、元数据刷新

实时监控Openlist挂载媒体文件夹的增删改变化，自动将媒体重命名为适合emby刮削的标准格式，最后生成strm文件供emby使用并刷新相应媒体库

NDS Filesystem reading and parsing library

GetSTRM creates a directory structure for Plex/Emby of .strm files from an M3U or RockyMyM3U STRM playlist

Jellyfin plugin that probes STRM files to extract media information (codec, resolution, duration, audio). Jellyfin skips STRM files during library scans — this plugin fills that gap.

🤖 Jellyfin plugin with ML-powered per-user recommendations, watch activity insights, automated media cleanup (trickplay, subtitles, symlinks, .strm), Overseerr/Jellyseerr request management, codec/health statistics, growth trends, trash bin, backup/restore & multi-instance Radarr/Sonarr. 8-tab dashboard, 7 languages.

foobar2000 component which adds support for .strm files (as used by Kodi)

STRM file management system for Emby + AList integration with admin UI, incremental sync, Docker/Nginx deployment, and proxy-friendly media workflows.

GRC Mapping Analyst is a NIST IR 8477-based toolkit for AI-assisted cybersecurity crosswalks, producing deterministic set-theory mappings (equal, subset_of, superset_of, intersects_with, not_related) and 12-column STRM CSV outputs across frameworks, regulations, and control catalogs.

Kodi addon for Audiobookshelf with login support, playback, progress sync, and STRM export for audiobooks and podcasts.

Leakage-aware flood susceptibility mapping using classical machine learning and strict spatial holdout, with reproducible preprocessing, explainability analysis, and benchmark comparison across eight models.