Skip to main content
Glama

mcp_opendaw_apply_mix_preset

Apply a mix preset (volume, pan, mute, solo) across all audio units in one call, replacing multiple individual track adjustments. Uses genre-specific or custom JSON presets.

Instructions

Apply a mix preset to all audio units in one call — volume, pan, mute, solo.

Replaces 10-30 set_track_volume/set_track_panning/set_track_mute calls. Presets can be genre-specific or custom JSON.

preset: JSON object mapping unit indices to settings: {"0": {"volume_db": -3, "panning": 0.0, "mute": false}, "1": {"volume_db": -6, "panning": -0.3, "solo": false}, ...}

Alternatively, use a named preset: "lofi", "house", "balanced", "wide"

Returns applied settings per unit.

Example: preset='{"0":{"volume_db":-3,"panning":0},"1":{"volume_db":-6,"panning":-0.3}}' preset='lofi' (built-in: kicks +0, bass -3, synths -6, wide pans)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presetYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It explains the operation, parameter format, and return value, but lacks details on side effects (e.g., whether existing settings are overwritten, behavior on invalid indices), reversibility, or prerequisites. It adds useful context but not complete behavioral disclosure.

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 slightly verbose but every sentence is informative. It is front-loaded with the primary purpose, then details the parameter format, examples, and return value. The structure is logical and scannable, though a bit dense.

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?

For a single-parameter tool, the description is quite complete: it covers the main use case, parameter format, built-in options, and return value. However, it does not differentiate from similar batch tools like apply_full_mix or apply_genre_mix, and misses edge cases like invalid presets or partial application. Given no annotations, it's strong but has minor gaps.

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 input schema has a single 'preset' parameter with zero description coverage. The description fully compensates by providing the exact JSON structure, named presets, and multiple examples. This is exemplary parameter documentation that goes far beyond the 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 description clearly states 'Apply a mix preset to all audio units in one call — volume, pan, mute, solo.' This specifies the action, target scope, and attributes, distinguishing it from individual set_track_* tools. It also mentions the batch nature, which separates it from siblings.

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 explicitly says 'Replaces 10-30 set_track_volume/set_track_panning/set_track_mute calls,' providing a clear alternative and when this tool is beneficial. It does not explicitly state when NOT to use it, but the context strongly implies the batch-vs-individual tradeoff.

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