Skip to main content
Glama

mcp_opendaw_import_audio_to_tracks

Import an audio file into DAW tracks and optionally split it into stems on separate tracks for mixing and mastering.

Instructions

Import an audio file into the DAW, optionally split into stems on separate tracks.

One-call pipeline: audio file → (optional stem separation) → create instrument tracks → load each stem → place on tracks at start_beat. This is the Suno-to-DAW bridge: generate a track with Suno, download it, then import with stem splitting for mixing and mastering.

Without mode: loads the whole file as one track (simple import). With mode: splits into stems, creates one track per stem, loads and places each.

file_path: Absolute path to WAV/MP3/FLAC/OGG file on disk. mode: Stem separation mode (empty = no split, single track). Modes: "bs6" (6-stem), "scnet" (4-stem), "ensemble" (max quality), "polarformer" (vocal/instrumental), "drumsep" (drum parts). start_beat: Beat position to place the audio region(s) (default 0). bpm: Tempo for the project (affects beat alignment, default 120).

Returns: track count, per-track info (name, sample_id, duration, stem name), and suggested next steps (apply_genre_mix, render_full).

Examples:

Simple import — one track, no splitting

import_audio_to_tracks("/tmp/suno_track.wav")

Split into 6 stems, each on its own track

import_audio_to_tracks("/tmp/suno_track.wav", mode="bs6")

Vocal/instrumental split at beat 4

import_audio_to_tracks("/tmp/vocal.wav", mode="polarformer", start_beat=4)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bpmNo
modeNo
file_pathYes
start_beatNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses the operational pipeline: 'create instrument tracks → load each stem → place on tracks at start_beat.' It explains both modes, lists supported file formats, documents return values, and suggests next steps (apply_genre_mix, render_full), providing transparency well beyond a basic summary.

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 efficiently organized with a pipeline overview, mode explanation, parameter details, return info, and three illustrative examples. Every sentence serves a purpose, and the core purpose is front-loaded, making it easy to scan without unnecessary verbosity.

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 (4 params, mode variations, pipeline behavior), the description is complete. It covers both import modes, parameter semantics, return data, and even offers workflow suggestions. The output schema's existence reduces the burden for return-value details, but the description still exceeds what's needed for safe usage.

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?

The schema has 0% description coverage, but the description compensates completely. It defines file_path's absolute path and supported formats, enumerates all mode values with their meanings, and explains start_beat and bpm with defaults and effects. This adds substantial semantic value beyond the raw schema.

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 opening line states a clear verb+resource: 'Import an audio file into the DAW, optionally split into stems on separate tracks.' The pipeline description (audio file → split → create tracks → load/place) distinguishes it from granular siblings like load_audio or create_audio_track, making the tool's role unmistakable.

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 a concrete use case as 'the Suno-to-DAW bridge' and explains when the mode parameter is used vs. not. However, it does not explicitly list when to use this composite tool over manual alternatives (e.g., load_audio + create_audio_track + place_audio_region), so the guidance is context-rich but not exhaustive.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ameobius-ai/opendaw-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server