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Audiolab

作者:Audio-Launch版本 0.5.0i★ –i在你的电脑上运行
注册名称tools.audiolab/audiolab

安装

概览

作者提供的说明(英文原文)

Loudness, true-peak and voice-quality analysis of URLs and local files via the hosted AudioLab API.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:AUDIOLAB_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: AUDIOLAB_API_KEY, AUDIOLAB_API_BASE, AUDIOLAB_TIMEOUT_MS

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • npm已安装 Node.js(用于 npx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "audiolab": {
      "command": "npx",
      "args": [
        "-y",
        "@audiolabtools/mcp-server"
      ],
      "env": {
        "AUDIOLAB_API_KEY": "your-value",
        "AUDIOLAB_API_BASE": "your-value",
        "AUDIOLAB_TIMEOUT_MS": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add audiolab --env AUDIOLAB_API_KEY=your-value --env AUDIOLAB_API_BASE=your-value --env AUDIOLAB_TIMEOUT_MS=your-value -- npx -y @audiolabtools/mcp-server

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "audiolab": {
      "command": "npx",
      "args": [
        "-y",
        "@audiolabtools/mcp-server"
      ],
      "env": {
        "AUDIOLAB_API_KEY": "your-value",
        "AUDIOLAB_API_BASE": "your-value",
        "AUDIOLAB_TIMEOUT_MS": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "audiolab": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@audiolabtools/mcp-server"
      ],
      "env": {
        "AUDIOLAB_API_KEY": "your-value",
        "AUDIOLAB_API_BASE": "your-value",
        "AUDIOLAB_TIMEOUT_MS": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • AUDIOLAB_API_KEY 机密 env
    Optional. Without it: the keyless trial, 20 calls a month per IP, single files up to 4 MB, no batches. A free key from https://audiolab.tools/account gives 1,000 calls and 2 GB per month, no card.
  • AUDIOLAB_API_BASE env
    Defaults to https://audiolab.tools/v1. The value must include the /v1 path segment.
  • AUDIOLAB_TIMEOUT_MS env
    Request timeout in milliseconds.

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 audiolab.tools 验证(注册中心会核实域名所有权)

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32620 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32620 个服务器的 79% 更新
  • 基础检查结果等于或优于此分类中其他 32620 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Audiolab 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:AUDIOLAB_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.5.0)于9天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Intervals MCP

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Intervals MCP

作者:ljcl

Remote MCP server for intervals.icu run data and analysis

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

@audiolabtools/mcp-server

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 measure a public URL or a local file on your machine, but the measuring always happens on the hosted API: the file is read here and uploaded there (see Privacy).

Install

Point your MCP client at the package via npx (nothing to install globally). No account needed for a first score:

{

"mcpServers": { "audiolab": { "command": "npx", "args": ["-y", "@audiolabtools/mcp-server"] } } }

Without a key you are on the keyless trial: 20 calls a month and 3 a minute per IP address, for single analyses of a URL or a local file up to 4 MB. Batches and larger files need a key. A free key gives 1,000 calls and 2 GB a month, no card: sign in at https://audiolab.tools/account, generate one, and add it:

"env": { "AUDIOLAB_API_KEY": "al_live_yourkey" }

Requirements

  • Node ≥ 18: uses the built-in global fetch + AbortSignal.timeout.
  • Optionally an AUDIOLAB_API_KEY (see Install). 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 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.)*
ToolReturns
analyze_loudnessIntegrated LUFS (EBU R128 / BS.1770-4), true-peak (dBTP), LRA, crest factor, stereo correlation, mono compatibility, tonal balance
check_targetPass/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_timeseriesShort-term LUFS over time + downsampled waveform peaks (waveformPoints?)
get_spectrumFFT magnitude data + 7-band energies
analyze_voiceVoice QA: speech/silence ratio, speaking rate, SNR, noise floor, pause energy, sibilance & clipping risk
get_speech_segmentsVoiced regions with start/end + per-segment RMS (auto-trim, chapters)
index_signalContent-type guess, tags, clipping/silence regions, brightness & dynamics buckets
analyze_profileOne named question, voice, master, provenance, dataset, environment, broadcast, loop, room (reverberation from a clap, a pop, an impulse response or a sweep; pass roomSource), chain (lost packets) or pitch (where a voice sits and how clean it is), answered with only the lenses it needs. These ten 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_loudnessA/B on two sources (urlA/pathA + urlB/pathB), returns both results
analyze_batchOne 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
  • *“Is this take usable?”* → analyze_profile with profile:"voice"
  • *“Has this file been re-encoded, and is it all one source?”* → analyze_profile with profile:"provenance"
  • *“Run loudness on ./master.wav”* → analyze_loudness with path
  • *“Does ./mix.mp3 pass Spotify?”* → check_target with path + target:"spotify"

Configuration (env)

VarDefaultPurpose
AUDIOLAB_API_KEY– (optional)Your API key. Without it: the keyless trial (20 calls a month per IP, no batches, files up to 4 MB).
AUDIOLAB_API_BASEhttps://audiolab.tools/v1Override the API base (must be https://).
AUDIOLAB_TIMEOUT_MS330000Per-request timeout in milliseconds (long files and batches stream server-side and can legitimately take minutes).

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 read here and uploaded to the API (small files in the request body; larger files via a private one-shot signed upload into EU storage). The API returns numbers only and does not keep your audio: a direct request is decoded and discarded inside the request, and a signed upload is swept from storage within the hour (see https://audiolab.tools/privacy). This package has no telemetry and writes nothing to disk. There is no offline mode, and the engine is not published as an installable package. If audio must never leave the machine, don't use a hosted analyser; the in-browser labs on the website measure on-device, but they are for people, not for agents.

Limits

  • Local files: up to 150 MB (host bigger ones at a public URL).
  • Duration: loudness routes (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.
  • One file per call (agents loop for many); one-shot (no streaming/realtime).
  • Rate and monthly limits are enforced by the API, per key (per IP address on the keyless trial).

Smoke test

node hosted-server.mjs --selftest   # verifies the 10 tools + guards; no network

License

MIT © Nathan Renting

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