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Ableton MCP Server

get_loop_settings

Read the Arrangement loop's enabled state, start, and length in beats to inspect Ableton Live loop geometry for playback automation.

Instructions

Read Arrangement loop enablement, start, and length.

Side effects: none. Example: get_loop_settings() returns loop geometry in beats. Edge cases: values can change with user interaction during a session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose 'Side effects: none' plus the useful edge case that values can change with user interaction during a session. It adds nothing about permissions, caching, or refresh/polling behavior, so it is only partially complete for an annotation-free tool.

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?

Front-loaded with the purpose and organized under clear labels (Side effects, Example, Edge cases). The Example line is nearly redundant for a zero-argument call, a small amount of padding against an otherwise tight structure.

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 simple, zero-parameter tool with no output schema and no annotations, the description usefully states the return content ('loop geometry in beats'), the safety profile ('Side effects: none'), and a behavioral caveat. It is complete enough to call correctly, missing only the read-only confirmation an annotation would normally supply.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing to disambiguate and the baseline is 4. The description does not introduce parameter concepts that could mislead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Read') and precise resource ('Arrangement loop enablement, start, and length'), so the agent knows exactly what is returned. It implicitly contrasts with the write siblings (set_loop, set_loop_start, set_loop_length) but never names the distinction, so it falls short of the 5 bar for explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this versus the many read siblings (get_scenes, get_track_state, get_locators) or versus the set_loop* writers. The example just restates a parameterless call rather than explaining a scenario that selects this tool.

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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