Music Tag Web is a self-hosted Docker application for editing and managing music file metadata across multiple audio formats. It addresses the problem that users with music libraries stored on remote NAS systems or Linux servers cannot use traditional desktop tools like MP3Tag or MusicBrainz Picard to modify metadata remotely. The tool runs as a containerized service accessible through a web browser, allowing users to edit ID3 tags, album artwork, lyrics, and other metadata directly on files stored on their music servers without uploading content to third-party services.
The project supports a comprehensive range of audio formats including FLAC, APE, WAV, AIFF, WV, TTA, MP3, M4A, OGG, MPC, OPUS, WMA, DSF, and MP4. Beyond basic metadata editing, it offers batch operations for tag scraping and repair, music fingerprinting for identifying songs with missing or corrupted tags, intelligent file organization by artist and album, and text replacement for cleaning corrupted or malformed tags. Additional capabilities include batch format conversion via integrated FFmpeg, automatic splitting of cue sheet files, multilingual lyric embedding, and playback statistics visualization.
This tool is designed specifically for Homelab enthusiasts running self-hosted music services like Navidrome or Jellyfin on NAS devices or Linux servers. It functions as a companion application to these music servers, enabling remote metadata management through a responsive web interface that works on mobile browsers. The project is compatible with various NAS platforms including Synology and QNAP through Docker deployment, and integrates with private cloud storage solutions for online playback and tag editing.
Development activity shows consistent engagement with the codebase through regular updates and refinements to core functionality. The project maintains active issue resolution and feature additions that respond to user needs in the self-hosted music server community. Documentation is provided in multiple languages to serve its international user base.
