Proporciona a los asistentes de codificación con IA acceso sensorial directo a aplicaciones web en vivo mediante la captura y el análisis de audio, elementos visuales y datos de rendimiento.
También conocido como asume21/webear
- Stars
- 1
- Herramientas
- —
- Descargas, 30 días
- —
- Última versión
- 1.2.4
- Último commit
- 28 oct 2026
- Licencia
- MIT
¿Qué es webear MCP?
webear es un MCP server. Proporciona a los asistentes de codificación con IA acceso sensorial directo a aplicaciones web en vivo mediante la captura y el análisis de audio, elementos visuales y datos de rendimiento.
Resumen generado a partir del README del proyecto
Acerca del MCP server de webear
Webear proporciona a los asistentes de codificación con IA acceso sensorial directo a aplicaciones web en vivo al conectarse con la Web Audio API. Esto permite que una IA escuche la salida digital de una pestaña del navegador sin la interferencia de la acústica de la habitación o del hardware del micrófono. Los desarrolladores pueden integrar esto en su flujo de trabajo utilizando un middleware de Express en un servidor de desarrollo local o conectándose a un relay alojado a través de SSE. El servidor se ejecuta dentro de un IDE como Claude Code, Cursor o Windsurf usando stdio.
Los usuarios pueden interactuar con la aplicación a través de herramientas específicas como capture_audio, analyze_audio, describe_audio y diff_audio. Aunque el análisis básico como el volumen y el clipping se puede realizar localmente con ffmpeg, las funciones avanzadas como el centroide espectral, el BPM y el timing jitter requieren una clave de API de CodedSwitch. El sistema está diseñado para desarrolladores de audio web, creadores de juegos y constructores de aplicaciones musicales que necesitan depurar grafos de audio complejos, sintetizadores o problemas de mezcla directamente a través de su asistente de IA.
Qué puedes hacer con él
- 1Depurar problemas de mezcla de audioPide a tu IA que analice un flujo de audio en vivo para identificar por qué una banda de frecuencia específica suena turbia.
- 2Detectar regresiones de audioUtiliza la herramienta para comparar capturas de audio de diferentes versiones de código y encontrar cambios en el volumen o el tono.
- 3Monitorear el clipping de la señalComprueba si tu aplicación web está produciendo audio que excede los niveles máximos de pico.
- 4Analizar la consistencia rítmicaEvalúa el timing jitter y el BPM de una aplicación musical basada en la web.
Escrito a partir del README del proyecto. Cada caso de uso se verifica con una cita del mismo.
Cómo instalar webear MCP
Formatos verificados el 10 nov 2026Añadir a CursorAñadir a GooseInstalar webear MCP en Claude Code
$ claude mcp add --env 'CODEDSWITCH_API_KEY=<YOUR_CODEDSWITCH_API_KEY>' webear -- npx -y webearInstalar webear MCP en Cursor
~/.cursor/mcp.json
{
"mcpServers": {
"webear": {
"command": "npx",
"args": [
"-y",
"webear"
],
"env": {
"CODEDSWITCH_API_KEY": "<YOUR_CODEDSWITCH_API_KEY>"
}
}
}
}Instalar webear MCP en VS Code
.vscode/mcp.json
{
"servers": {
"webear": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"webear"
],
"env": {
"CODEDSWITCH_API_KEY": "<YOUR_CODEDSWITCH_API_KEY>"
}
}
}
}Instalar webear MCP en VS Code CLI
$ code --add-mcp '{"name":"webear","type":"stdio","command":"npx","args":["-y","webear"],"env":{"CODEDSWITCH_API_KEY":"<YOUR_CODEDSWITCH_API_KEY>"}}'Instalar webear MCP en Claude Desktop
claude_desktop_config.json
{
"mcpServers": {
"webear": {
"command": "npx",
"args": [
"-y",
"webear"
],
"env": {
"CODEDSWITCH_API_KEY": "<YOUR_CODEDSWITCH_API_KEY>"
}
}
}
}Instalar webear MCP en Codex
$ codex mcp add webear --env 'CODEDSWITCH_API_KEY=<YOUR_CODEDSWITCH_API_KEY>' -- npx -y webearInstalar webear MCP en Codex config.toml
~/.codex/config.toml
[mcp_servers.webear] command = "npx" args = ["-y", "webear"] [mcp_servers.webear.env] CODEDSWITCH_API_KEY = "<YOUR_CODEDSWITCH_API_KEY>"
Instalar webear MCP en Gemini CLI
$ gemini mcp add -s user -e 'CODEDSWITCH_API_KEY=<YOUR_CODEDSWITCH_API_KEY>' webear npx -- -y webearInstalar webear MCP en Gemini settings.json
~/.gemini/settings.json
{
"mcpServers": {
"webear": {
"command": "npx",
"args": [
"-y",
"webear"
],
"env": {
"CODEDSWITCH_API_KEY": "<YOUR_CODEDSWITCH_API_KEY>"
}
}
}
}Configuración
CODEDSWITCH_API_KEYObligatorioSecretoAPI key from codedswitch.com for audio analysis
WEBEAR_BASE_URLURL of your dev server where WebEar middleware is mounted
| Nombre | Descripción | Tipo |
|---|---|---|
| CODEDSWITCH_API_KEY | API key from codedswitch.com for audio analysis | ObligatorioSecreto |
| WEBEAR_BASE_URL | URL of your dev server where WebEar middleware is mounted |
Verificaciones automáticas
Ejecutado 13 nov 2026Informe completo →Pasó nuestras verificaciones automáticas. Esto no es una auditoría de seguridad: lee el código y dale al servidor el acceso más limitado que necesite. Cómo funcionan las verificaciones
- Repositorio de origen vinculado y accesibleasume21/webear is public and reachablegithub.com/asume21/webear ↗Aprobado
- El paquete indica este repositorio como su origenwebear names asume21/webear as sourcenpmjs.com/package/webear ↗Aprobado
- Procedencia de la compilación (atestación de Sigstore)No build attestation published for this releaseNo verificado
- Licencia de código abierto (OSI)MITspdx.org/licenses/MIT.html ↗Aprobado
- Commit o lanzamiento en el último añoLast commit or release 2026-10-28github.com/asume21/webear ↗Aprobado
- OpenSSF ScorecardNo verificado
- El nombre del paquete no es similar a un paquete popularNo popular package one edit away from webearAprobado
- No hay avisos críticos en el paquete ni en sus dependencias99 resolved dependencies checked; no critical advisoryosv.dev ↗Aprobado
- Sin instrucciones ocultas para el modelo0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersAprobado
- Las herramientas destructivas están etiquetadasNo verificado
- El endpoint remoto responde al handshake de MCPNo verificado
README
Ver en GitHubwebear
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.

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 — 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 key | With key | |
|---|---|---|
capture_audio |
✓ | ✓ |
analyze_audio |
Basic — duration, loudness, peak, clipping (local) | Full — spectral centroid, band energy, crest factor, BPM, timing jitter |
describe_audio — what it SOUNDS like |
— | ✓ |
mix_coach — measured + heard |
— | ✓ |
diff_audio — before/after |
— | ✓ |
To get one:
- Create a free account at codedswitch.com.
- Go to codedswitch.com/developer (also in the account menu as Developer API).
- Click Generate API Key — that value is your
CODEDSWITCH_API_KEY. Keys start withwbr_.
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_KEYfor 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.
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
- Create a free account at codedswitch.com.
- Open codedswitch.com/developer — also linked as Developer API in the account menu.
- Click Generate API Key and copy it. Keys start with
wbr_.
Free tier: 50 analyses/day, no credit card required.
Changelog
2.0.1
- Fixed the getting-started path for API keys. The previous instruction ("Settings → WebEar") was wrong — there is no WebEar section under Settings. Keys live at codedswitch.com/developer (linked as Developer API in the account menu). Both the Quick Start and the Web Perception sections now point to the correct place.
- The SDK's "missing API key" console error now links straight to the key page.
Contributing
See CONTRIBUTING.md.
License
MIT — see LICENSE
Author
Built by @asume21 — CodedSwitch
Preguntas sobre webear MCP
¿Cómo agrego webear MCP a Claude Code?
Ejecuta claude mcp add --env 'CODEDSWITCH_API_KEY=<YOUR_CODEDSWITCH_API_KEY>' webear -- npx -y webear en tu terminal. Añade --scope user para que esté disponible en todos los proyectos.
¿Cómo agrego webear MCP a Cursor?
Abre ~/.cursor/mcp.json y añade el servidor en mcpServers, usando la configuración de Cursor que se muestra en la sección de instalación de arriba.
¿Requiere analyze_audio una clave de API?
El análisis básico, que incluye duración, volumen, nivel de pico y clipping, funciona localmente sin una clave si ffmpeg está instalado. Las métricas avanzadas como el centroide espectral y el BPM requieren una clave de API de CodedSwitch.