原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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Audio

作者:audiojs版本 2.10.0i★ 329i在你的电脑上运行
注册名称io.github.audiojs/audio

安装

概览

作者提供的说明(英文原文)

Edit, analyze and convert audio: loudness, spec checks, denoise, EQ, cuts, BPM, key. No ffmpeg.

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: 设计、图片与音频

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:3 项中通过 3 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)。
  • 注册中心没有列出需要填写的密钥。

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": {
    "audio": {
      "command": "npx",
      "args": [
        "-y",
        "audio",
        "--mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add audio -- npx -y audio --mcp

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": {
    "audio": {
      "command": "npx",
      "args": [
        "-y",
        "audio",
        "--mcp"
      ]
    }
  }
}

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": {
    "audio": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "audio",
        "--mcp"
      ]
    }
  }
}

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。

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 audiojs 验证,该账户拥有此仓库

  • ✓ 通过

    仍在维护

    代码最后更新于前天

  • ✓ 通过

    有许可证

    使用 MIT

  • – 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“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2166 个服务器的 100%
  • 发布到注册中心的时间比此分类中其他 2166 个服务器的 44% 更新
  • 基础检查结果等于或优于此分类中其他 2166 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

Audio 安全吗?

它在 3 项适用的基础检查中通过了 3 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?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

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 仓库最后更新于前天,最新版本(2.10.0)于34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:Figma Context MCP, Claude Real Video, Figma MCP Server

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

Figma Context MCP

作者:GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

在你的电脑上运行★ 16,165MIT5个月前更新
安装

Claude Real Video

作者:HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

在你的电脑上运行★ 2,284MIT2个月前更新
安装

Figma MCP Server

作者:figma

The Figma MCP server brings Figma design context directly into your AI workflow.

在云端运行★ 2,15213个月前更新
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。

audio

_High-level audio manipulations: loading, playback, analysis and editing. 140+ plugins: denoise, dynamics, EQ, filters, effects, reverb, time and pitch, spatial, synthesis, music analysis._

  • Any Format — fast wasm codecs, no ffmpeg.
  • Non-destructive — virtual edits, infinite undo, instant clone.
  • Stream-first — playback/encode during decode, realtime editing.
  • Paged — no 2Gb memory limit, open 10Gb+ files.
  • Analysis — loudness, spectrum, beats, pitch, chords, key.
  • Modular – pluggable ops, tree-shakable.
  • CLI — playback, batch processing, scripting, unix pipes, tab completion.
  • Cross-platform — browsers, node, deno, bun.
Start Recipes API CLI FAQ Plugins Architecture Comparison RX 12

Start

Node

npm i audio

import audio from 'audio'

let song = audio('song.mp3') song.play() // the speakers, as a page plays it: no ffmpeg, no player to spawn song.pause(); song.seek(60); song.resume()

let voice = audio('voice.wav').trim().normalize('podcast') await voice.save('clean.mp3') let { pass, rules } = await voice.check('podcast') // each rule of Apple's spec, measured

Browser
<script type="module">

import audio from 'https://esm.sh/audio' audio('./song.mp3').trim().normalize().fade(0.5, 2).clip({ at: 60, duration: 30 }).play()

Audio anywhere
import 'audio/polyfill'          // the page's HTMLAudioElement, in Node, Bun and Deno

let song = new Audio('song.mp3') song.onended = () => console.log('done') await song.play() song.currentTime = 30; song.volume = 0.5; song.loop = true

Events, their order, promises and errors as Chromium's own element has them, compared observation by observation (test/polyfill.js). import { Audio } from 'audio/polyfill' leaves the global alone.

CLI
npm i -g audio # or: npx audio …

audio voice.wav trim normalize podcast save clean.mp3 audio clean.mp3 check podcast

Apple Podcasts https://podcasters.apple.com/support/893-audio-requirements

✓ Loudness -16.44 LUFS -17 to -15

✓ True peak -1.18 dBTP ≤ -1

pass

A fail exits 1, so the same line guards a build: Check in CI.

Skill
npx skills add audiojs/audio
MCP
npx add-mcp "npx -y audio --mcp"  # asks which of your agents: Claude Code, Codex, Cursor, Gemini CLI, Kimi Code, Pi, OpenCode, Zed…

Prompt: make ~/Desktop/interview.m4a podcast-ready and tell me the loudness before and after

One agent at a time: claude mcp add audio -- npx -y audio --mcp, qwen mcp add audio npx -y audio --mcp, droid mcp add audio "npx -y audio --mcp".

Playground and agents
npx audio --bridge

audio bridge on http://127.0.0.1:7777

#

key 3e37b8c61acf5b50f010852168f4843d

agents Claude Code, Codex, Pi, Kimi Code

#

In the playground's Agent panel, paste the key, then Connect. It stays the same next time.

Open the playground, every edit of it a line of audio code, and connect it to the bridge with the key (once: the bridge keeps it), and its chat runs an agent of yours, which measures, looks at, edits and plays the sound open there, and finds which edit did what: it measures the sound before and after each, and what each took out; each tab keeps its conversations, each with the agent, and its model, picked under the message. The bridge finds Claude Code, Codex, Pi, Gemini CLI, Qwen Code, Kimi Code, OpenCode, Kilo Code, Cline, Goose, Factory Droid, Cursor, Augment, Kiro and Mistral Vibe on PATH; any other that speaks ACP runs by its command line, --agent "my-agent --acp".

Any MCP agent gets the playground's tools (state, measure, look, edit, select, play, check, …), the running bridge found by itself: npx add-mcp "npx -y audio --mcp --playground".

An agent thinks with the model its own settings name: Pi takes local ones for good from ollama launch pi --config; Claude Code takes any Anthropic-compatible endpoint from the bridge's environment:

ANTHROPIC_BASE_URL=http://localhost:11434 ANTHROPIC_AUTH_TOKEN=ollama ANTHROPIC_API_KEY= ANTHROPIC_MODEL=qwen3-coder npx audio --bridge
ModelsANTHROPIC_BASE_URL, with the provider's key as ANTHROPIC_AUTH_TOKEN
Ollamahttp://localhost:11434, token ollama (docs)
Z.ai GLMhttps://api.z.ai/api/anthropic (docs)
Kimihttps://api.moonshot.ai/anthropic (docs)
Qwenhttps://coding-intl.dashscope.aliyuncs.com/apps/anthropic, Coding Plan (docs)
DeepSeekhttps://api.deepseek.com/anthropic (docs)
Embed

The playground in any page, its script the element's own text: it runs where the reader scrolls to it, plays, takes edits, and opens whole in the playground. Nothing of the reader's is kept.

<script type="module" src="https://audio.js.org/embed.js"></script>

audio('chime.wav') .trim() .normalize(-1)

What it shows, the frame takes as one JSON: the element's ui attribute, with these attributes over it, each a key of it. panel: code (default), edits (its steps, each with its settings) or none; display: wave or spec; controls: the parts shown, each in its own place: over the picture sound (its name, a menu of its ways in: a file, a take, a sample), link and name (the way to the playground), ruler (the time row; left out, none: the big time says it), look (a band's dropdown of how it draws); in the bar play record loop clock history message heard, a level (level, or what it reads: peak rms loudness), rate channels depth before, view (a switch: the waveform, the spectrogram), open and save (a file of the reader's in; the result out, in the format picked from its menu) — without it, all but sound, view, open and save; ops: edits a press away, one button after the history, a menu of them with their values, as trim normalize(-1) stretch(1.25) reverse (a call's own arguments, or the defaults the menus write); background: the ground it sits on and fades into, a CSS colour, or page, the page's own under the element (the element reads it; a frame can't); height in px. A sound named by its path from the site's root (audio('/sounds/take.mp3')) is that site's file. The shows until the frame comes, and where scripts don't run. Every key, zoom and overshoot too: playground/README.md.

Recipes

Clean up
// master a raw take

let a = audio('raw-take.wav') a.trim(-30).normalize('podcast').fade(0.3, 0.5) await a.save('clean.wav')

// full restoration chain via ecosystem plugins (see API › Plugins) a.gate(-45).dehum().deesser().compressor({ threshold: -18 }).limiter({ ceiling: -1 })

// cut 2:00–2:15, smooth the splice a.remove({ at: 120, duration: 15 }).fade(0.1, { at: 120 })

// find clipped blocks let clips = await a.stat('clipping')

// does it pass? each rule of the spec, measured let { pass, rules } = await a.check('podcast') // acx, podcast, spotify, broadcast, netflix

Master & deliver
// master a song to a reference track: its tone (mid and side), width and loudness, under -1 dBTP

audio('mix.wav').master(await audio('reference.wav')).save('master.wav')

// audiobook chapter for ACX: RMS -23..-18 dB, peaks under -3 dB, floor under -60 dB, room tone at each end, 44.1 kHz let ch = audio('chapter-01.wav') .highpass(80).omlsa({ gMin: -12 }).compressor({ threshold: -24, ratio: 2.5 }) .normalize(-20, 'rms', { ceiling: -3.5 }) .trim().pad(1.5, 2).roomtone() // room tone, not digital silence .resample(44100) console.log(await ch.check('acx')) // passed 10 of 10 real narrations (.work/pro.md) await ch.save('chapter-01.mp3', { bitrate: 192 })

// tighten pauses in a talking-head video, then hand the cuts to the video editor let talk = audio('talk.mp4').shrink(0.3) await talk.save('talk.m4a') // the sound, cut await talk.save('talk.edl') // the same cuts for the picture (Premiere, Resolve)

Compose
// podcast montage

let ep = audio([intro, interview.trim().normalize('podcast'), outro], { crossfade: 0.5 }) await ep.save('episode.mp3')

// voiceover over music music.gain(-12).mix(voice, { at: 2 })

// ringtone: the chorus + fades audio('song.mp3').crop({ at: 45, duration: 30 }).fade(0.5, 2).normalize().save('ringtone.mp3')

// split an audiobook into chapters let [ch1, ch2, ch3] = audio('audiobook.mp3').split(1800, 3600)

// glitch: stutter + reverse let v = a.clip({ at: 1, duration: 0.25 }) audio([v, v, v, v]).reverse({ at: 0.25, duration: 0.25 })

Analyze
// waveform bars — and progressively, as it decodes

let [mins, peaks] = await a.stat(['min', 'max'], { bins: canvas.width }) a.on('data', ({ delta }) => appendBars(delta.max[0], delta.min[0]))

// features for ML let mfcc = await a.stat('cepstrum', { bins: 13 }) let [loud, rms] = await a.stat(['loudness', 'rms'])

// notes, chords, key let notes = await a.stat('notes') // [{time, duration, freq, midi, note, clarity}] let chords = await a.stat('chords') // [{time, duration, label, root, quality, confidence}] let key = await a.stat('key') // {tonic, mode, label, confidence}

Record & generate
// mic take

let a = audio() a.record() // …later a.stop() a.trim().normalize()

// tone — any t => sample function let tone = audio.from(t => Math.sin(440 * Math.PI * 2 * t), { duration: 2 })

// sonify data let s = audio.from(t => Math.sin((200 + data[t / 0.2 | 0]) * Math.PI * 2 * t) * 0.5, { duration: data.length * 0.2 })

Automate
a.gain(t => -12 * (0.5 + 0.5 * Math.cos(t * Math.PI * 4)))  // 2Hz tremolo in dB

a.lowpass(t => 400 + 4000 * t) // filter sweep a.pan({ t: [0, 2, 4], v: [-1, 1, -1] }) // curve L→R→L over 4s, serializable music.ducker({ key: voice }) // sidechain (plugin)

Stream & persist
// stream to network — encode/playback during decode

for await (let chunk of audio('2hour-mix.flac').highpass(40)) socket.send(chunk[0].buffer)

// serialize edits, restore later let json = JSON.stringify(a) // { source, edits, ... } let b = audio(JSON.parse(json)) // re-decode + replay edits

API

Create

| Method                         | Description

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