webear

Give your AI real senses — hear, see, and feel any web app.

An MCP server + browser SDK that gives AI coding assistants direct sensory access to a live web application. Audio, visuals, performance, network, security, and console — captured from the browser, analyzed in real time, delivered via MCP.

"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.

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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.

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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?"

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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.

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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)
})

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Requirements

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

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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

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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.

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Web Perception — Full Sensor Suite

WebEar started as audio-only. Web Perception expands it to 6 senses:

Sensor	What it perceives
WebEar	Audio — mix quality, rhythm, instruments, clipping
WebEye	Visual — canvas, UI layout, animations, screenshots
WebSense	Performance — frame rate, memory, audio latency
WebNerve	Network — API latencies, connection quality, storage
WebShield	Security — cookies, storage exposure, CSP, framing
WebLog	Console — logs, warnings, errors, uncaught exceptions

Install the full browser SDK

import { WebPerception } from 'webear/perception'

WebPerception.init({
  apiKey: 'wbr_YOUR_API_KEY',
  relayUrl: 'https://www.codedswitch.com',
  sensors: ['ear', 'eye', 'sense', 'nerve', 'shield', 'log'],
})

Or use a single sensor:

import { WebEar } from 'webear/perception'

WebEar.init({
  apiKey: 'wbr_YOUR_API_KEY',
  ear: { audioContext: myCtx, audioNode: masterGain },
})

Connect via MCP (hosted relay — no local server required)

{
  "mcpServers": {
    "webear": {
      "url": "https://www.codedswitch.com/api/webear/mcp/sse",
      "headers": {
        "Authorization": "Bearer wbr_YOUR_API_KEY"
      }
    }
  }
}

Available MCP Tools

Sensor	Tool	Credits	Description
Ear	capture_audio	Free	Record live tab audio
Ear	analyze_audio	1	BPM, loudness, frequency bands, clipping, dynamic range
Ear	describe_audio	2	AI plain-English description — instruments, genre, mood, mix notes
Ear	diff_audio	1	Compare two captures — loudness, tone, timing deltas
Ear	groove_score	2	Grid alignment, swing factor, consistency (0–100%)
Ear	capture_and_analyze	1	Capture + analysis in one call
Ear	mix_coach	3	Structured mixing feedback
Eye	capture_video	Free	Record canvas/video from the tab
Eye	describe_video	2	AI visual description — layout, colors, bugs
Eye	diff_visuals	2	Compare two visual captures
Sense	capture_telemetry	Free	FPS, memory, layout shifts, audio latency
Sense	analyze_telemetry	1	Frame drops, memory pressure, audio underruns
Nerve	capture_nerve	Free	API timings, connection quality, storage size
Nerve	analyze_nerve	1	Slow APIs, connection quality, storage bloat
Shield	capture_shield	Free	Cookies, CSP, storage exposure, framing
Shield	analyze_shield	1	CORS issues, non-HttpOnly cookies, missing CSP
Log	capture_logs	Free	Console output + uncaught exceptions
Log	analyze_logs	1	Error patterns, stack traces, repeated warnings

Get an API Key

Sign up at codedswitch.com → Settings → WebEar. Keys start with wbr_.

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Contributing

See CONTRIBUTING.md.

License

MIT — see LICENSE

Author

Built by @asume21 — CodedSwitch