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VS Code MCP Setup for Audio Tools - Split, Denoise, Reverb

MCPAI Audio ToolsClaude IntegrationCursor Integration

If you already work inside VS Code, you don't need a browser tab to split a song into stems, remove background noise from a podcast recording, or add reverb to a dry vocal. Sonicaura Studio exposes all three AI audio tools through the Model Context Protocol (MCP), which means VS Code (via GitHub Copilot Chat or any MCP-compatible extension) can call them on your behalf.

This guide walks through the full setup — from generating your API key to running your first audio task from inside the editor. It takes about five minutes.

What you can do once it's connected

Once Sonicaura Studio is registered as an MCP server, you can ask your AI assistant in plain language:

  • "Split this MP3 into 6 stems and save them next to the source file."
  • "Remove the background noise from episode-14.wav."
  • "Add bathroom reverb to this vocal take and give me the download link."

The assistant calls the right tool, waits for the result, and returns a signed download URL. No interface, no drag-and-drop, no context switch.

Why use MCP instead of the web interface

The web interface at https://www.sonicaurastudio.com/tools is the fastest way to try the tools. MCP is for when you want to work without leaving your editor:

  • Single quick job — the web interface is faster, but MCP works fine.
  • Batch of 20 files — the web interface is manual each time, MCP is one prompt.
  • Part of a scripted workflow — the web interface cannot do it, MCP can.
  • Away from a browser — the web interface cannot do it, MCP can.
  • Uses the same credits — both yes.

Both routes use the same credit balance. MCP does not have separate pricing.

Prerequisites

Before you start, make sure you have:

  1. VS Code (any recent version — 1.85 or later recommended for MCP support).
  2. An MCP-compatible extension, such as GitHub Copilot Chat, or any client that supports the Model Context Protocol.
  3. A Sonicaura Studio account with at least one credit. New accounts get 2 free credits on signup — no credit card required.
  4. Your MCP API key. You can generate it from your User Center at https://www.sonicaurastudio.com/usercenter/mcp.

Step 1 — Generate your MCP API key

Go to the MCP API Key page inside your User Center at https://www.sonicaurastudio.com/usercenter/mcp. If you don't have a key yet, click Generate API Key. You'll get a string that starts with sk_live_ — copy it somewhere safe.

Treat this key like a password. Anyone with the key can spend your credits.

Step 2 — Register the MCP server in VS Code

VS Code reads MCP servers from a configuration file. The exact path depends on the extension you're using, but the shape of the config is the same. Here is a minimal example (paste this into the MCP settings file):

{
  "mcpServers": {
    "sonicaura": {
      "url": "https://api.sonicaurastudio.com/mcp",
      "headers": {
        "Authorization": "Bearer sk_live_your_key_here"
      }
    }
  }
}

Replace sk_live_your_key_here with the key you generated in Step 1.

If your MCP client does not support remote HTTP servers directly, use the proxy configuration shown in the full setup guide at https://www.sonicaurastudio.com/mcp/vscode.

Step 3 — Verify the connection

Open the VS Code command palette and look for an entry such as "MCP: List Servers" (the exact command depends on your extension). You should see sonicaura listed as connected.

If you see an authentication error, the most common causes are:

  • A typo in the Authorization header — it must be exactly Bearer sk_live_... with a space after Bearer.
  • An expired or regenerated key — if you regenerated the key on the website, the old one stops working immediately.
  • A stale MCP client cache — restart VS Code.

Step 4 — Run your first audio task

With the connection live, open the assistant panel and try a prompt like:

Split /Users/me/Desktop/song.mp3 into 4 stems.

The assistant will:

  1. Call get_upload_url to get a presigned upload URL.
  2. Upload the file to Sonicaura's private R2 storage.
  3. Call process_audio with task_type: "4stems".
  4. Poll check_task_status until the result is ready.
  5. Return signed download URLs for vocals.mp3, drums.mp3, bass.mp3 and other.mp3.

One credit is deducted per task. Files up to 500 MB are supported.

What tools does Sonicaura Studio expose over MCP?

The MCP server exposes five public tools:

  • list_audio_tools — Discover all available capabilities and their parameters.
  • get_upload_url — Get a presigned URL for uploading a file to R2.
  • upload_audio — Upload small files (under 1 MB) directly.
  • process_audio — Submit a task (stem separation, denoise, or reverb).
  • check_task_status — Poll for completion and get signed download URLs.

The task types you can pass to process_audio are:

  • 2stems — vocals + instrumental.
  • 4stems — vocals, drums, bass, other.
  • 6stems — vocals, guitar, bass, drums, piano, other.
  • music_denoise — noise removal that preserves music.
  • denoise — aggressive speech cleanup for podcasts and interviews.
  • reverb — one of five spatial presets: vocal_booth, studio_room, bathroom, concert_hall, church.

Common questions

Is MCP support free?

MCP itself is free — it's an open protocol. Using Sonicaura Studio's tools still costs credits, exactly as it does on the web. One credit per AI task, and credits never expire.

Do I need to install an SDK?

No. The MCP server is a remote HTTP endpoint. You just need an MCP-compatible client: VS Code with an MCP extension, Claude Desktop, Cursor, or any other client that supports the protocol.

Can I use this in Cursor or Claude Desktop too?

Yes. The same MCP server URL and API key work in any MCP-compatible client. See the MCP integration overview at https://www.sonicaurastudio.com/mcp for client-specific instructions.

What audio formats are supported?

The AI tools accept MP3, WAV, FLAC, M4A and MP4 — up to 500 MB per file. Video files are accepted and the audio track is extracted automatically.

Where are my files stored?

Files are uploaded to private object storage (Cloudflare R2), processed on our servers, and returned as signed download links. They are never shared with third parties, and signed links expire after one hour.

What happens if a task fails?

If the underlying model fails, the credit is not consumed — the tool returns an error, and you can retry. If the failure happens after the credit has been deducted, the credit is refunded automatically. If you believe a credit was consumed incorrectly, contact us via the contact page at https://www.sonicaurastudio.com/contact.

Tips for using MCP audio tools inside an agent workflow

A few patterns that make the setup more useful day to day:

  • Chain separation and denoise. Ask the assistant to separate a song, then run music_denoise on the vocal stem. It's two calls, and the assistant will handle the sequencing.
  • Use list_audio_tools first. If you're not sure which task_type to use, ask the assistant to list the available tools. It returns descriptions and typical processing times.
  • Poll with backoff. check_task_status returns processing until the result is ready. Typical timings: 15 seconds for reverb, 30 seconds for denoise, 60–120 seconds for stem separation.
  • Batch in loops. Since each call is independent, you can ask the assistant to loop over a folder of files and process them one by one. Each iteration uses one credit.

Next steps

If you've completed the setup above, you can now run AI audio tasks directly from VS Code. The next things to explore:

To generate or regenerate your MCP API key, visit the MCP API Key page at https://www.sonicaurastudio.com/usercenter/mcp.

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