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lmms-mcp

by TypeWolf

add_effect

Add audio effects to any track or mixer channel in LMMS. Specify the effect type, wet/dry mix, and chain position to shape your sound.

Instructions

Add an effect to a track's or mixer channel's effect chain.

Args: target_type: "track" or "mixer" target_index: Track index or mixer channel number (0=Master) effect: Built-in LMMS effect name. Valid: amplifier, bassbooster, bitcrush, compressor, crossovereq, delay, dispersion, dualfilter, dynamicsprocessor, eq, flanger, frequencyshifter, multitapecho, reverbsc, slewdistortion, stereoenhancer, stereomatrix, waveshaper wet: Wet/dry mix 0.0-1.0 (1.0=full effect) enabled: Whether the effect is active position: Chain position to insert at (None=end of chain)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wetNo
effectYes
enabledNo
positionNo
target_typeYes
target_indexYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds helpful behavioral details such as valid effect names, wet/dry range (0.0-1.0), mixer index 0=Master, and position None=end. However, it does not disclose mutation side effects, error handling, or whether inserting at a position replaces an existing effect.

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 compact and well-structured: a one-sentence summary followed by a clear Args list. Every line adds necessary information, and the effect-name enumeration is repetitive but essential for correct invocation.

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 6 parameters, no annotations, and an output schema present, the description is complete enough for correct invocation. It covers all parameter meanings, valid values, and insertion semantics. Error behavior is not described, but all invocation-critical details are present.

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%, so the Args block must compensate, and it does. It documents all six parameters with concrete semantics: target_type values, target_index meaning, the complete list of valid effect names, wet range, enabled flag, and position insertion behavior. This goes well beyond the bare schema types and defaults.

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 starts with a specific action and resource: 'Add an effect to a track's or mixer channel's effect chain.' The sibling tools remove_effect, toggle_effect, and get_effect_chain make the differentiation clear, so an agent can immediately understand what this tool does versus its alternatives.

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

Usage Guidelines3/5

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

The description gives clear context about target type ('track' or 'mixer') but does not explicitly state when to use this tool instead of remove_effect, toggle_effect, or get_effect_chain. The intended usage is implied by the verb and sibling names rather than stated with exclusion criteria.

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