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AbletonMCP

AbletonMCP

by rephlex187
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

set_track_volume

Adjust the volume level of any Ableton Live track by specifying a track index, volume value (0.0 to 1.0), and track type (regular, return, or master).

Instructions

Set a track's volume.

Parameters:

  • track_index: Index of the track

  • volume: Volume value (0.0-1.0, where ~0.85 is 0dB)

  • track_type: 'regular', 'return', or 'master'

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": {
      "ctx": "<ctx>",
      "track_index": "<track_index>",
      "volume": "<volume>"
    },
    "name": "set_track_volume"
  }
}

Input Schema

NameRequiredDescriptionDefault
ctxYes
volumeYes
track_typeNoregular
track_indexYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description provides useful behavioral context: volume range (0.0-1.0, ~0.85 = 0dB) and track_type options. It adds value beyond the schema.

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 concise: one sentence followed by a parameter list. Every line is informative with no fluff.

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 simplicity of the tool (no output schema, few parameters), the description explains the purpose, parameter details, and constraints fully. No gaps for effective use.

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 0% description coverage; the description compensates by explaining each parameter (track_index, volume, track_type) with their meanings and constraints.

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 'Set a track's volume.' uses a clear verb and resource, distinguishing it from sibling tools like get_track_volume or set_track_panning.

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 is straightforward and implies usage for adjusting volume, but does not explicitly state when not to use it or mention alternatives. However, for a simple setter, this is sufficient.

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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