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separate_audio

Separate audio into isolated vocals, drums, bass, and other stems using Demucs v4. Remove background music and noise from recordings to produce cleaner audio for transcription and analysis.

Instructions

Separate audio into stems (vocals, drums, bass, other) using Meta's Demucs v4. Isolates vocals from music, background noise, and other sounds. Use this before transcription when audio has music, intros, or heavy background noise for dramatically cleaner results.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "audio_path": "<audio_path>"
    },
    "name": "separate_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNoDemucs model. htdemucs is the default (fast, great quality). htdemucs_ft is fine-tuned (slower, best quality). Default: htdemucs
audio_pathYesPath to the audio file
vocals_onlyNoIf true, only separate into vocals + no_vocals (faster). If false, separate into all 4 stems: vocals, drums, bass, other. Default: true

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden for behavioral disclosure. It does convey the isolation behavior and stem outputs, but it omits side effects like output file locations, processing time/resource usage, or whether the original audio is modified. This is a moderate gap given the lack of annotation support.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and includes a practical usage recommendation. Every sentence contributes meaning without repetition or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, method (Demucs v4), and usage scenario, which is sufficient for a straightforward audio-processing tool. However, it lacks details about expected outputs (e.g., files created) and prerequisites or limitations, but given the no-output-schema context, it is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameters are already well-documented in the input schema. The description adds some context by mentioning the specific stems and the vocals focus, but it doesn't elaborate on the model parameter or vocals_only behavior beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool separates audio into specific stems (vocals, drums, bass, other) using Meta's Demucs v4, which directly conveys its function. It also differentiates from sibling tools like transcribe_audio by focusing on the separation use case and explicitly tying it to cleaning audio before transcription.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance on when to use the tool: 'Use this before transcription when audio has music, intros, or heavy background noise for dramatically cleaner results.' This provides clear context and links to a sibling tool, though it doesn't mention when not to use it or alternative tools beyond transcription.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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