webear

webear

Give your AI coding assistant ears.

An MCP server that lets AI coding assistants capture, analyze, and describe live audio from a running web application — not a file on disk, not the physical microphone. The actual AudioContext output your app is rendering right now.

"The beat sounds muddy" → your AI captures 3 seconds, measures the spectral centroid at 580 Hz with 45% energy below 250 Hz, and tells you exactly why.

What It Does

Tool	Description
capture_audio	Record a short clip (500ms–30s) of what your web app is outputting right now
analyze_audio	Signal analysis: RMS, peak dB, clipping, spectral centroid, frequency bands, BPM, timing jitter
describe_audio	Plain-English AI description — "the kick is boomy with heavy sub buildup around 80 Hz"
diff_audio	Compare two captures and flag what changed — loudness, tone, timing, clipping

How It Works

Browser (Web Audio API)
    ↓ MediaRecorder taps the AudioContext output node
    ↓ Uploads WebM blob via HTTP POST
Express Middleware (your dev server)
    ↓ Stores captures in memory, dispatches commands via SSE
MCP Server (stdio — runs inside your IDE)
    ↓ Retrieves captures, sends to CodedSwitch analysis API
AI Coding Assistant
    → "Your bass band is 42% of the mix (high), spectral centroid
       is 580 Hz (muddy), and timing jitter is 23ms — the scheduler
       is drifting under load."

The key difference from every other audio MCP: this taps the Web Audio graph directly, bypassing room acoustics, microphone hardware, and the need to export files.

Quick Start

1. Install

npm install webear

2. Add the Express middleware to your dev server

import express from 'express'
import { webearMiddleware } from 'webear/middleware'

const app = express()
app.use(express.json())

// Mount the audio debug bridge (automatically disabled in production)
app.use('/api/webear', webearMiddleware())

app.listen(5000)

3. Add the client snippet to your web app

Option A — auto-detect everything (Tone.js or raw Web Audio)

import WebEar from 'webear/client'
WebEar.init()

Option B — explicit AudioContext

const ctx = new AudioContext()
const masterGain = ctx.createGain()
masterGain.connect(ctx.destination)

WebEar.init({ audioContext: ctx, outputNode: masterGain })

Option C — Tone.js project

import * as Tone from 'tone'
WebEar.init({ toneJs: true })

Option D — Three.js WebGL Game

import * as THREE from 'three'
const listener = new THREE.AudioListener()
camera.add(listener)
WebEar.init({ tapNode: listener.getInput() })

Option E — plain script tag

<script src="node_modules/webear/client-snippet.js"></script>
<script>WebEar.init()</script>

4. Configure your IDE

Claude Code (.mcp.json in project root):

{
  "mcpServers": {
    "webear": {
      "command": "npx",
      "args": ["webear"],
      "env": {
        "WEBEAR_BASE_URL": "http://localhost:5000",
        "CODEDSWITCH_API_KEY": "your-key-here"
      }
    }
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "webear": {
      "command": "npx",
      "args": ["webear"],
      "env": {
        "WEBEAR_BASE_URL": "http://localhost:5000",
        "CODEDSWITCH_API_KEY": "your-key-here"
      }
    }
  }
}

Windsurf (mcp_config.json):

{
  "webear": {
    "command": "npx",
    "args": ["webear"],
    "disabled": false,
    "env": {
      "WEBEAR_BASE_URL": "http://localhost:5000",
      "CODEDSWITCH_API_KEY": "your-key-here"
    }
  }
}

5. Get an API key

Get your free CODEDSWITCH_API_KEY at codedswitch.com.

Free tier: 50 analyses/day. No credit card required.

6. Start your dev server, open your app, play audio, then ask your AI:

"Capture 3 seconds and tell me why the bass sounds muddy."

"Compare the audio before and after my last commit."

"Is there any clipping in the high-frequency range?"

Example Output

analyze_audio

── Audio Analysis Report ──────────────────────────────
Duration:          3.02s

── Loudness ─────────────────────────────────────────
RMS:               -12.4 dBFS
Peak:              -1.2 dBFS
Dynamic range:     11.2 dB
Crest factor:      3.63
Clipping:          none

── Tone ──────────────────────────────────────────────
Spectral centroid: 2847 Hz
DC offset:         0.00012 (ok)

── Frequency Bands ───────────────────────────────────
Sub  (20-80 Hz):   8.2%
Bass (80-250 Hz):  22.1%
Mid  (250-2k Hz):  38.4%
Hi-mid (2-6k Hz):  21.8%
High (6k+ Hz):     9.5%

── Rhythm ────────────────────────────────────────────
Estimated BPM:     92
Onset count:       12
Timing jitter:     4.2 ms std dev

── Summary ───────────────────────────────────────────
Loudness: -12.4 dBFS RMS, peak -1.2 dBFS. Tone: balanced (centroid 2847 Hz).
Band mix — sub: 8% | bass: 22% | mid: 38% | hi-mid: 22% | high: 10%.
Rhythm: estimated 92 BPM, 12 onsets detected. Timing: very tight (< 5 ms jitter).

diff_audio

── Audio Diff: a1b2c3d4… → e5f6g7h8… ──

── Loudness ──────────────────────────────────────────
  RMS: -14.2 dBFS → -12.4 dBFS  (+1.8 dBFS)
⚠ Peak: -3.1 dBFS → -0.2 dBFS  (+2.9 dBFS)
⚠ CLIPPING INTRODUCED — gain staging regression

── Tone ──────────────────────────────────────────────
⚠ Spectral centroid: 2847.0 Hz → 1920.0 Hz  (-927.0 Hz)

── Interpretation ────────────────────────────────────
A gain bug was introduced that causes clipping.
Tonal character changed noticeably — EQ or filter behaviour may have shifted.

Configuration

Environment Variables

Variable	Default	Description
WEBEAR_BASE_URL	http://localhost:4000	URL of your dev server (where middleware is mounted)
CODEDSWITCH_API_KEY	—	API key from codedswitch.com — required for analyze_audio and describe_audio
MCP_API_URL	https://www.codedswitch.com	Override the analysis API base (advanced / self-hosted)

Middleware Options

webearMiddleware({
  maxCaptures: 50,       // Max captures in memory (default: 50)
  maxAgeMins: 10,        // Auto-evict after N minutes (default: 10)
  maxUploadBytes: 50e6,  // Max upload size (default: 50MB)
  devOnly: true,         // Disable in production (default: true)
})

Client Options

WebEar.init({
  audioContext: myCtx,             // Your AudioContext instance
  outputNode: myGainNode,          // The node to tap (defaults to destination)
  toneJs: true,                    // Auto-detect Tone.js context
  bridgeBase: '/api/webear',  // Override API path
  devOnly: true,                   // Only init outside of production (default: true)
})

Requirements

• Node.js >= 18
• A browser that supports MediaRecorder (Chrome, Firefox, Edge, Safari 14+)
• A CODEDSWITCH_API_KEY for analysis (free at codedswitch.com)

Who Is This For?

• Web Audio / Tone.js developers — debug beats, synths, effects, and mixing without leaving your IDE
• Game audio developers — verify sound effects, spatial audio, and mixing in real-time
• Music app builders — catch regressions between code changes with diff_audio
• Podcast / streaming apps — validate audio quality, levels, and encoding
• Anyone whose app makes sound — if it has a Web Audio graph, your AI can now hear it

Why Not Just Use the Microphone?

Microphone MCPs capture room sound — your fan noise, chair creaks, and room reverb are all in the recording. webear taps the Web Audio API before it hits the DAC, giving you a clean digital signal with no room artifacts.

Contributing

See CONTRIBUTING.md.

License

MIT — see LICENSE

Author

Built by @asume21 — CodedSwitch