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@audiolabtools/mcp-server
Advanced tools
MCP server for AudioLab, loudness (EBU R128 / BS.1770-4), true-peak, voice-quality, and signal analysis for AI agents (Claude, Cursor, any MCP client), via the AudioLab hosted API. No local audio engine required.
MCP (Model Context Protocol) server that gives any MCP-capable AI (Claude Desktop, Claude Code, Cursor, and others) ten audio-analysis tools, backed by the hosted AudioLab API. It is a thin HTTP client: no local audio engine, no ffmpeg, nothing to compile. It can analyse a public URL or a local file on your machine.
Point your MCP client at the package via npx (nothing to install globally):
{
"mcpServers": {
"audiolab": {
"command": "npx",
"args": ["-y", "@audiolabtools/mcp-server"],
"env": { "AUDIOLAB_API_KEY": "al_live_yourkey" }
}
}
}
Get a key: sign in at https://audiolab.tools/account and generate one (free tier available).
fetch + AbortSignal.timeout.AUDIOLAB_API_KEY. No ffmpeg, no native dependencies.Every tool takes one audio source: a public url or a local path:
{ url: "https://…" }: a public https URL the API fetches server-side.{ path: "./mix.wav" }: a file on the machine running this server. Files up to 4 MB
are sent inline; larger files (up to 150 MB) upload over a signed URL, are analysed, and
are swept from storage within the hour. (Local path works only in this stdio server, not the
remote /mcp endpoint.)| Tool | Returns |
|---|---|
analyze_loudness | Integrated LUFS (EBU R128 / BS.1770-4), true-peak (dBTP), LRA, crest factor, stereo correlation, mono compatibility, tonal balance |
check_target | Pass/fail vs a delivery target (spotify / apple-music / youtube / tidal / amazon-music / podcast / ebu-broadcast / atsc-broadcast, or target:"custom" + lufs+tp), with per-metric deltas and an ffmpeg loudnorm fix command |
analyze_timeseries | Short-term LUFS over time + downsampled waveform peaks (waveformPoints?) |
get_spectrum | FFT magnitude data + 7-band energies |
analyze_voice | Voice QA: speech/silence ratio, speaking rate, SNR, noise floor, room echo, sibilance & clipping risk |
get_speech_segments | Voiced regions with start/end + per-segment RMS (auto-trim, chapters) |
index_signal | Content-type guess, tags, clipping/silence regions, brightness & dynamics buckets |
analyze_profile | One named question, voice, master, provenance, dataset, environment, broadcast or loop, answered with only the lenses it needs. These seven need a paid plan; the free tier gets the basic profile, keyed by stable lens id. Add series:true for the curves, per-block lanes and per-phrase values. Carries a note when the profile’s voice lenses land on non-speech material. Full catalogue: https://audiolab.tools/lenses |
compare_loudness | A/B on two sources (urlA/pathA + urlB/pathB), returns both results |
analyze_batch | One route over up to 20 sources in a single call (urls and/or paths), per-item ok/data/error. For folder QA, library indexing, or checking a whole release against a target. Each item meters as one call |
Example asks to your AI:
analyze_loudness with urlanalyze_profile with profile:"voice"analyze_profile with profile:"provenance"analyze_loudness with pathcheck_target with path + target:"spotify"| Var | Default | Purpose |
|---|---|---|
AUDIOLAB_API_KEY | – (required) | Your API key. |
AUDIOLAB_API_BASE | https://audiolab.tools/v1 | Override the API base (must be https://). |
AUDIOLAB_TIMEOUT_MS | 330000 | Per-request timeout in milliseconds (long files and batches stream server-side and can legitimately take minutes). |
Analysis happens on the AudioLab API, so the audio does reach audiolab.tools: a url
is fetched server-side, and a local path is sent to the API (small files inline; larger
files via a private one-shot signed upload that is deleted right after analysis). The API
returns numbers only and does not retain your audio (see https://audiolab.tools/privacy).
This package has no telemetry and writes nothing to disk. If audio must never leave the
machine, don't use a hosted analyser.
analyze_loudness, check_target, analyze_timeseries, get_spectrum) handle long files (podcast episodes, full sets, up to ~3 h) via server-side streaming; voice/signal routes are limited to ~7 minutes.node hosted-server.mjs --selftest # verifies the 10 tools + guards; no network
MIT © Nathan Renting
FAQs
MCP server for AudioLab, loudness (EBU R128 / BS.1770-4), true-peak, voice-quality, and signal analysis for AI agents (Claude, Cursor, any MCP client), via the AudioLab hosted API. No local audio engine required.
We found that @audiolabtools/mcp-server demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.

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