Echoteka MCP
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ECHOTEKA_MCP_URL | No | Server the bridge connects to. Use https://echoteka.ai/mcp/oauth for sign-in. | https://echoteka.ai/mcp |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_service_infoA | What Echoteka does, what is free, what a credit buys, and where the rules live. Call once at the start of a session. |
| list_presetsA | All mastering presets with their target loudness in LUFS. Call this to get the exact preset keys that master_track and batch_master accept. Use preview_styles instead when you want to HEAR 2-6 of them on the actual track before choosing, and get_service_info when you need the wider service manifest rather than the preset list. Free. |
| check_limitsA | What this caller may do right now: free master left today and when it resets, credit balance, upload cap, whether advanced modules are available. Call before mastering. |
| analyze_trackA | Measure integrated LUFS, sample peak, duration, sample rate and stereo correlation without processing. Free, a couple of seconds. Run this before choosing a preset. Note: true peak and loudness range are NOT part of this fast pass — they are measured on the result and come back from get_job. |
| clean_ai_traceA | Remove the marks an AI generator leaves in the audio (narrow tones above 15 kHz, level jumps at block seams, fixed spectral peaks); loudness and tone stay as they are. It does not hide that a track is AI-made - disclose AI use wherever a platform asks. Free, never spends a credit. Returns a job id - poll get_job. |
| preview_stylesA | 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 instead of guessing a preset, and instead of spending a credit to 'try' one. |
| master_trackA | Master one track. Uses 1 CREDIT when the account has a balance; otherwise it runs on the free quota (1 free master a day, without advanced modules). Returns a job id immediately - poll get_job (typical 20-60 s, up to 10 min with restoration). The source is fetched by this server, so the ceiling here is 100 MB per file. Pass dry_run=true first if you want to see what would be used and the effective settings before anything is spent. |
| batch_masterA | 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) levels the tracks RELATIVE to each other: the loudest hits the target exactly, the others keep their offsets, so a quiet interlude is not inflated to single level. Limits: 10 tracks, 100 MB per file and 300 MB per call (this server's own caps, for memory). A big album takes minutes - send fewer, longer tracks per call rather than all at once. Returns one job id per track - poll each with get_job. Pass dry_run=true to see what would be used and the settings before anything is spent. |
| get_jobA | Status, progress and result metrics (after_lufs, true_peak_db, lra, platform_ready) for a mastering, cleanup or preview job. For previews it returns each style with its loudness and a listen link. When a master is done it also returns download_url - a signed link that works without credentials for about an hour. Free. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| master_for_platform | Analyze the track, pick the preset and the platform target, master it, and report LUFS / true peak back. |
| fix_ai_track | Clean the AI generator artifacts first, then master with the unlimiter preset if the source is brickwalled. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Mastering passport | Interactive result card: loudness before/after, true peak, range, target deviation and the download link. |
| Agent playbook | Rules for agents using the service. |
| Service manifest | Endpoints, presets, free allowance, policies. |
| Terms | Terms summary and rights. |
TDQS
Scored across 9 tools
Each tool has a clearly distinct purpose, and descriptions explicitly cross-reference near-neighbors (e.g. list_presets vs preview_styles vs get_service_info, analyze_track vs get_job metrics). master_track vs batch_master differ clearly by cardinality, and the info tools (get_service_info/check_limits/list_presets) are cleanly separated by scope. Little risk of misselection.
All nine tools follow a consistent snake_case verb_noun pattern: get_service_info, list_presets, check_limits, analyze_track, master_track, batch_master, clean_ai_trace, preview_styles, get_job. No mixed conventions or casing. batch_master is the only slight variant but stays within the same readable pattern.
Nine tools is well-scoped for an audio mastering service, with no redundant or filler entries. Each tool maps to a distinct step (orient, check limits, list presets, analyze, preview, master single/batch, clean, poll).
The surface covers the full mastering lifecycle: orientation, limits, presets, pre-analysis, preview, single/batch mastering, cleanup, and result retrieval. Minor gaps exist, such as no job cancellation or way to list/enumerate existing jobs (only get_job by id), but core workflows are fully supported.