@audiolabtools/mcp-server

MCP (Model Context Protocol) server that gives any MCP-capable AI — Claude Desktop, Claude Code, Cursor, and others — nine 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.

Install

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).

Requirements

Node ≥ 18 — uses the built-in global fetch + AbortSignal.timeout.
An AUDIOLAB_API_KEY. No ffmpeg, no native dependencies.

Tools

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 50 MB) upload over a one-shot signed URL, are analysed, and are then deleted. (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 + dominant band
`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
`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 the loudness of https://example.com/track.wav” → analyze_loudness with url
“Run loudness on ./master.wav” → analyze_loudness with path
“Does ./mix.mp3 pass Spotify?” → check_target with path + target:"spotify"

Configuration (env)

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`	`60000`	Per-request timeout in milliseconds.

Privacy

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.

Limits

Local files: up to 50 MB (host bigger ones at a public URL).
One file per call (agents loop for many); one-shot (no streaming/realtime).
Rate and monthly limits are enforced by the API, per key.

Smoke test

node hosted-server.mjs --selftest   # verifies the 9 tools + guards; no network

audiolab-mcp-server

Install to Claude Code

README