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mcp_opendaw_transcribe_drums

Convert a drum recording or any percussive audio into MIDI notes on your DAW track. Detects kick, snare, and hi-hat onsets to create playable MIDI patterns.

Instructions

Transcribe drum onsets from an audio file into MIDI notes on a DAW track.

Audio-to-MIDI drum transcription — converts a drum recording (or any audio with percussive content) into MIDI notes. Pure Python, no external deps.

Pipeline:

  1. Parse WAV file

  2. Split into 3 frequency bands (kick <250Hz, snare 250-2500Hz, hat >2500Hz)

  3. Per-band onset detection (energy spike above local average)

  4. Classify each onset: kick (pitch 36), snare (38), hat (42)

  5. Estimate velocity from onset amplitude

  6. Convert onset times to beat positions (if bpm provided)

  7. Create MIDI notes on the specified track via create_notes_batch

Use cases:

  • Extract a drum groove from a Suno track → reuse as MIDI pattern

  • Transcribe a real drum recording → edit/quantize in DAW

  • Replace original drums with a different instrument

filename: WAV file name (in exports dir) or absolute path. bpm: Tempo for beat conversion (0 = auto-detect via detect_bpm first). sensitivity: Onset detection threshold (1.0=more sensitive, 2.0=less, default 1.5). unit_index: AU index with note tracks. track_index: Track to place transcribed notes.

Returns: notes created, onset count, band counts (kick/snare/hat), bpm, duration.

Example:

Transcribe a drum loop from a downloaded Suno track

result = transcribe_drums("suno_track.wav", bpm=120)

Auto-detect BPM first

result = transcribe_drums("drum_loop.wav") # bpm=0 → auto-detect

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bpmNo
filenameYes
unit_indexNo
sensitivityNo
track_indexNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. It details the internal pipeline (frequency bands, onset detection, classification into kick/snare/hat, velocity estimation, beat conversion, note creation). It discloses that notes are created on the specified track via create_notes_batch. However, it doesn't mention potential failure modes or format limitations (e.g., only WAV).

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 well-structured: concise first sentence, numbered pipeline, use cases, parameter list, return values, and examples. No redundant information; every sentence adds value. Front-loaded with the main purpose.

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

Completeness5/5

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

Given the tool's complexity (multi-step pipeline, 5 parameters, return structure), the description is remarkably complete. It explains the process, parameter semantics, return values, and provides a realistic example. Output schema exists, but the description still lists return fields for clarity.

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

Parameters5/5

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

Schema description coverage is 0%, but the description explains all five parameters: filename (WAV file or path), bpm (tempo, 0=auto-detect), sensitivity (threshold 1.0-2.0), unit_index (AU with note tracks), track_index (target track). It also includes default values and an example, fully compensating for missing schema descriptions.

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's purpose: 'Transcribe drum onsets from an audio file into MIDI notes on a DAW track.' It specifies it's for drum/percussive content, contrasting with sibling transcription tools like transcribe_melody. The verb 'transcribe' and resource 'drums' are specific.

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 provides concrete use cases (extract drum groove, transcribe recording, replace drums) and examples. It implies when to use (percussive audio) but doesn't explicitly state when not to use or compare directly to alternatives like transcribe_melody.

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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