Webear MCP server
Give your AI coding assistant ears — capture, analyze, and describe live audio.
1 stars
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If you have run it, two minutes of your experience saves the next person an afternoon.
Webear tools (4, 2 write)
write = sends, deletes, buys or postsRead from the package source without running it. The installed server may list more.
analyze_audiowrite actionRun signal analysis on a captured audio clip. Returns RMS, peak dB, clipping, spectral centroid, frequency band energy, estimated BPM, and timing jitter.
capture_audioRecord a short clip of what the running web app is currently outputting. Returns a capture ID you can pass to analyze_audio or describe_audio.
describe_audiowrite actionSend a captured audio clip to Gemini or GPT-4o to get a plain-English description of what it sounds like — useful when something sounds wrong but you cannot describe it.
diff_audioCompare two audio captures and flag what changed — loudness, tone, timing, clipping. Use this before and after a code change to verify the audio impact.
Public scan report
scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it
- Code scan20 source files scanned25/25
- –Live reliabilityno gateway calls yet and no remote to proben/a
- –Tool poisoningtools not inspected (local package is not executed); not countedn/a
- Auth qualitystatic API keys via environment variables6/15
- Maintenancelast push 41 days ago12/15
- Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Install Webear in Claude Code, Cursor or VS Code
Runs npx -y webear on your machine. Read the scan report first; the gateway never runs local packages.
claude mcp add webear -- npx -y webear
What the publisher says
From the Webear repository's README, as published. We do not edit it. Read it on GitHub
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.
What It Does
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 webear2. 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"
}
}
}
}Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Webear: common questions
- Is Webear MCP server safe?
- Mostly: it is graded B (78/100). Read the Webear safety report
- How do I install Webear?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Webear need an API key?
- Yes. The registry entry asks for
CODEDSWITCH_API_KEY. - Is Webear maintained?
- The last commit was 56 days ago (2026-08-18). The latest release is v1.2.4.
- What can I use instead of Webear?
- Servers from other publishers that do the same job: Audio MCP server, three.ws Vision MCP server and Openrouter Multimodal MCP server. Compare all Webear alternatives.
Alternatives to Webear
Same job from other publishers: the closest match first, then the best rated.
- AudioEdit, analyze and convert audio: loudness, spec checks, denoise, EQ, cuts, BPM, key. No ffmpeg.not reviewedEstablishedA
- three.ws VisionImage understanding for AI agents — analyze and describe any image via the three.ws pipeline.not reviewedEstablishedA
- Openrouter MultimodalChat with 300+ LLMs via OpenRouter. Analyze and generate images, audio, and video from MCP.not reviewedGrowingB
- DembrandtDesign tokens from any live site: colours, type, spacing, components, drift against a baseline.not reviewedWidely usedB
- FunASRTranscribe local audio with FunASR and SenseVoice using private, on-device inference.not reviewedEstablishedA