A
licenseA
qualityD
maintenanceAn MCP server that masters audio with a professional signal chain using ffmpeg, enabling loudness analysis, vocal-over-beat mixing, full mastering to target LUFS, and Dolby codec export.
4
7 npm
MIT
Magic Master MCP
by denisok-ai
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TDQS
A4.2/5.0
Scored across 11 tools
Disambiguation4/5
Most tools are cleanly separated: analyze_track, clean_ai_trace, preview_styles, master_track, and batch_master all have clearly different purposes. The only mild overlap is among get_service_info, get_pricing, and check_limits, all of which touch cost/account state and require careful reading.
Naming Consistency4/5
Names are uniformly lowercase snake_case and mostly follow a verb_noun pattern like list_presets, analyze_track, and get_job. The only notable deviation is batch_master, which reads more like a compound noun than the verb_noun pattern used by master_track.
Tool Count5/5
Eleven tools is well within the ideal range and each one earns its place in the mastering workflow. The set covers orientation, presets, pricing, limits, analysis, cleanup, preview, single and batch mastering, job polling, and token purchases without filler.
Completeness5/5
The full workflow is closed: agents can check limits, analyze, preview, master or batch master, poll for results and downloads, and create a top-up link when tokens run out. There are no dead ends in the core lifecycle.
Maintenance
ActivityMaintained
ResponsivenessNo issues