Skip to main content
Glama

mcp_opendaw_remix_track

Remix audio automatically in one call: analyze BPM/key, import stems, generate harmony, apply genre mix, and master to target loudness.

Instructions

Full Suno remix pipeline in one call — analyze → import → harmony → mix → master.

Takes any audio file (from download_audio or local) and creates a complete remix: detect BPM + key → set project tempo → import stems → auto-generate matching chord progression → harmonic arrangement → genre mix → mastering. One call replaces 8-10 individual tool calls.

Steps performed:

  1. analyze_track (BPM + key + mode + LUFS)

  2. set_bpm to detected tempo

  3. import_audio_to_tracks (with stem separation if stem_mode set)

  4. create_progression_from_key (diatonic, style-appropriate)

  5. create_harmonic_arrangement (arp + melody on top of stems)

  6. apply_genre_mix (genre-specific processing)

  7. add_mastering_chain (LUFS target)

After this call, the project is remix-ready — call render_full to export.

filename: Path to audio file (from download_audio or local path). genre: Genre for mix processing (synthwave, house, techno, dnb, trap, etc). style: Progression style (pop, jazz, rock, synthwave, folk, lofi). stem_mode: Stem separation mode ("bs2", "bs4", "bs6") or "" for simple import. master_lufs: Mastering target (-14 Spotify, -10 loud, -16 Apple). add_harmony: If True, generates harmonic layers (arp + melody). Default True. add_counter_melody: If True, adds counter-melody layer. Default False. bars: Arrangement length in bars. Default 8.

Returns: analysis results, tracks created, harmony layers, effects, mastering.

Example:

Full pipeline: Suno → download → remix

chirp_generate → audio_url download_audio(audio_url) → /tmp/track.wav remix_track("/tmp/track.wav", genre="synthwave", style="synthwave", stem_mode="bs6", add_counter_melody=True) render_full() → export

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
barsNo
genreNosynthwave
styleNopop
filenameYes
stem_modeNobs4
add_harmonyNo
master_lufsNo
add_counter_melodyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries full behavioral burden and does well by disclosing the exact ordered steps (analyze_track, set_bpm, import_audio_to_tracks, etc.), conditional stem separation, and return contents. It lacks explicit error behavior, idempotency, or whether existing project state is cleared, so it is not perfect.

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

Conciseness4/5

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

The description is well-structured with an overview, numbered step list, parameter definitions, returns, and an example. There is minor redundancy between the opening pipeline phrase and 'One call replaces 8-10 individual tool calls,' but the length is justified for an 8-parameter complex tool.

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?

The description covers all essential dimensions: when to use, what the pipeline does step-by-step, all parameter semantics, return values, and a concrete usage example. Given the tool's complexity and lack of annotations, this is fully complete.

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 compensates fully with a dedicated parameter list defining every parameter with concrete examples and defaults: genre examples, stem_mode choices ('bs2', 'bs4', 'bs6'), master_lufs targets (-14 Spotify, -10 loud), and boolean semantics. This is excellent compensation.

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 opens with 'Full Suno remix pipeline in one call — analyze → import → harmony → mix → master', clearly identifying a specific composite verb+resource. It distinguishes itself from granular siblings by stating 'One call replaces 8-10 individual tool calls,' making its unique pipeline role explicit.

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?

It states input context ('Takes any audio file (from download_audio or local)') and provides a clear follow-up workflow ('call render_full to export'). It implicitly guides usage via 'One call replaces 8-10 individual tool calls', but does not explicitly name alternatives or state when not to use this tool.

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