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  1. Home
  2. πŸŽ₯ Multimedia Process
  3. Webear
Webear logo
Health: ActiveRecent health check succeeded.Last checked 9/23/2026, 4:01:59 AM

Webear

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website

Give your AI coding assistant ears β€” capture, analyze, and describe live audio.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "webear": {
      "command": "npx",
      "args": [
        "webear"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸŽ₯ More in Multimedia Process

Documentation Overview

webear

npm version npm downloads License: MIT MCP Compatible

Give your AI real senses β€” 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 β€” captured from the browser, analyzed in real time, delivered via MCP.

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


AI Web Perception Demo


What It Does

ToolDescription
capture_audioRecord a short clip (500ms–30s) of what your web app is outputting right now
analyze_audioSignal analysis: RMS, peak dB, clipping, spectral centroid, frequency bands, BPM, timing jitter
describe_audioPlain-English AI description β€” "the kick is boomy with heavy sub buildup around 80 Hz"
diff_audioCompare two captures and flag what changed β€” loudness, tone, timing, clipping

How It Works

Code
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 β€” runs inside your IDE)
    ↓ Retrieves captures, sends to CodedSwitch analysis API
AI Coding Assistant
    β†’ "Your bass band is 42% of the mix (high), spectral centroid
       is 580 Hz (muddy), and timing jitter is 23ms β€” 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

Terminal
npm install webear

2. Add the Express middleware to your dev server

server.ts
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 β€” auto-detect everything (Tone.js or raw Web Audio)

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

Option B β€” explicit AudioContext

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

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

Option C β€” Tone.js project

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

Option D β€” Three.js WebGL Game

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

Option E β€” plain script tag

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

4. Configure your IDE

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

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

Cursor (.cursor/mcp.json):

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

Windsurf (mcp_config.json):

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 β€” optional, and not to start

analyze_audio works with no key and no account. If ffmpeg is on your PATH, it decodes and analyzes the capture on your machine and returns a basic report: duration, loudness, peak level and whether the audio is clipping. Nothing is uploaded. Try the tool before you sign up for anything.

A key unlocks the parts that need more than arithmetic:

No keyWith key
capture_audioβœ“βœ“
analyze_audioBasic β€” duration, loudness, peak, clipping (local)Full β€” spectral centroid, band energy, crest factor, BPM, timing jitter
describe_audio β€” what it SOUNDS likeβ€”βœ“
mix_coach β€” measured + heardβ€”βœ“
diff_audio β€” before/afterβ€”βœ“

To get one:

  1. Create a free account at codedswitch.com.
  2. Go to codedswitch.com/developer (also in the account menu as Developer API).
  3. Click Generate API Key β€” that value is your CODEDSWITCH_API_KEY. Keys start with wbr_.

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

Code
── 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 β€” 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

Code
── Audio Diff: a1b2c3d4… β†’ e5f6g7h8… ──

── Loudness ──────────────────────────────────────────
  RMS: -14.2 dBFS β†’ -12.4 dBFS  (+1.8 dBFS)
⚠ Peak: -3.1 dBFS β†’ -0.2 dBFS  (+2.9 dBFS)
⚠ CLIPPING INTRODUCED β€” gain staging regression

── Tone ──────────────────────────────────────────────
⚠ Spectral centroid: 2847.0 Hz β†’ 1920.0 Hz  (-927.0 Hz)

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

Configuration

Environment Variables

VariableDefaultDescription
WEBEAR_BASE_URLhttp://localhost:4000URL of your dev server (where middleware is mounted)
CODEDSWITCH_API_KEYβ€”API key from codedswitch.com β€” required for analyze_audio and describe_audio
MCP_API_URLhttps://www.codedswitch.comOverride the analysis API base (advanced / self-hosted)

Middleware Options

js
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

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

Why Not Just Use the Microphone?

Microphone MCPs capture room sound β€” 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.


Web Perception β€” Full Sensor Suite

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

SensorWhat it perceives
WebEarAudio β€” mix quality, rhythm, instruments, clipping
WebEyeVisual β€” canvas, UI layout, animations, screenshots
WebSensePerformance β€” frame rate, memory, audio latency
WebNerveNetwork β€” API latencies, connection quality, storage
WebShieldSecurity β€” cookies, storage exposure, CSP, framing
WebLogConsole β€” logs, warnings, errors, uncaught exceptions

Install the full browser SDK

server.ts
import { WebPerception } from 'webear/perception'

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
1
Stargazers on the source repository.
npm downloads
197
Package downloads in the last 30 days.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Webear

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "webear": { "command": "npx", "args": ["webear"] } }

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Technical Specs & Signals

CategoryπŸŽ₯Multimedia Process
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedAug 18, 2026
4/8 checks healthy over the last 45d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 18, 2026
npm downloads197/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
40Quality signal: Fair Β· 40/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
Adoption & activity5/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 4d ago via OSV.dev Β· webear (npm)

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