Categories › Media & Design › Audio, speech & transcription
Audio mastering for AI agents: LUFS analysis, Suno artifact cleanup, free daily master.
Remote server: your requests and data go to echoteka.ai. Claude Code: claude mcp add --transport http mastering https://echoteka.ai/mcp · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
get_service_info — What Echoteka does, what is free, what a credit buys, and where the rules live. Call once at the start of a session.list_presets — All mastering presets with their target loudness in LUFS. Call this to get the exact preset keys that master_track and batch_master accept. check_limits — What this caller may do right now: free master left today and when it resets, credit balance, upload cap, whether advanced modules are availanalyze_track — Measure integrated LUFS, sample peak, duration, sample rate and stereo correlation without processing. Free, a couple of seconds. Run this bclean_ai_trace — Remove the marks an AI generator leaves in the audio (narrow tones above 15 kHz, level jumps at block seams, fixed spectral peaks); loudnesspreview_styles — Master the middle 24 s of the track in 2-6 presets at once and get each one's loudness plus a listen link. FREE (6 per day). Use this insteamaster_track — Master one track. Uses 1 CREDIT when the account has a balance; otherwise it runs on the free quota (1 free master per day (UTC), without adbatch_master — Master up to 10 tracks in one call with the same settings. Needs N CREDITS for N tracks, or N free runs - not one. album_mode (default true)get_job — Status, progress and result metrics (after_lufs, true_peak_db, lra, platform_ready) for a mastering, cleanup or preview job. For previews itNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.