Media

Classroom Recording Cleaner

Clean lecture recordings with speech-focused EQ, hum reduction, peak control, and optional long-silence trimming.

file· File resultOpen tool

Quick start

Call this tool from your code in three languages.

cURL

# 1) Request a presigned URL → returns { uploadUrl, storageKey }
curl -X POST 'https://api.elysiatools.com/api/upload/presign/audio-classroom-recording-cleaner' \
  -H 'Content-Type: application/json' \
  -d '{"filename":"audioFile.ext","contentType":"application/octet-stream","size":12345}'

# 2) PUT the file bytes directly to the presigned uploadUrl
curl -X PUT '<presigned uploadUrl>' \
  --data-binary @/path/to/file.ext

# 3) Call the tool, passing the returned storageKey for each file field
curl -X POST 'https://api.elysiatools.com/en/api/tools/audio-classroom-recording-cleaner' \
  -F 'audioFile=uploads/2026/01/01/your-tool-1700000000000-abc123.ext' \
  -F 'trimLongSilences=true' \
  -F 'minimumSilenceSeconds=1.2' \
  -F 'silenceThresholdDb=-42' \
  -F 'applauseControl=gentle' \
  -F 'outputFormat=mp3'

API reference

Send a POST request with your inputs as JSON. File parameters require a separate upload first.

Endpoint

HTTP

POST https://api.elysiatools.com/en/api/tools/audio-classroom-recording-cleaner

Parameters

Name	Type	Required	Description
audioFile	fileupload required	Yes	—
trimLongSilences	checkbox	No	—
minimumSilenceSeconds	number	No	—
silenceThresholdDb	number	No	—
applauseControl	select	No	—
outputFormat	select	No	—

File-type parameters must be uploaded first via POST /upload/audio-classroom-recording-cleaner, then the returned filePath is passed to the corresponding file field.

Response format

File result

JSON

{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}

MCP integration

Add this tool to your Model Context Protocol server so AI agents can list and call it.

Server configuration

Add this block to your MCP client configuration:

mcp.json

{
  "mcpServers": {
    "elysiatools-audio-classroom-recording-cleaner": {
      "name": "audio-classroom-recording-cleaner",
      "description": "Clean lecture recordings with speech-focused EQ, hum reduction, peak control, and optional long-silence trimming.",
      "baseUrl": "https://api.elysiatools.com/mcp/sse?toolId=audio-classroom-recording-cleaner",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

List available tools

After connecting to the SSE endpoint, list the exposed tools:

tools/list

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/list"
}

Call this tool

Invoke the tool by its id, passing arguments built from its parameters:

tools/call

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "audio-classroom-recording-cleaner",
    "arguments": {
  "audioFile": "https://example.com/file.ext",
  "trimLongSilences": true,
  "minimumSilenceSeconds": 1.2,
  "silenceThresholdDb": -42,
  "applauseControl": "gentle",
  "outputFormat": "mp3"
}
  }
}

Chain multiple tools in one session with a comma-separated toolId list, e.g. /mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp (max 20).

File parameters accept a public file URL only (https://…). Local paths, data: URIs, and Base64 strings are not supported.

Questions or issues? Contact [email protected]