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Boost Audio - AI Song Generator

boost_audio_song_generator

Generate a full audio track from a text prompt using Boost Audio AI. Returns a mix and optionally separated stems openable in the Boost Audio DAW. Use this when the user wants AI-generated music, an instrumental, a song with lyrics or a quick demo from an idea.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bpmNoOptional tempo in beats per minute (60-180).
styleNoLegacy alias — folded into `inspiration` if provided (e.g. 'lofi hiphop'). Prefer `inspiration` and `styles` instead.
_jobIdNoInternal: job id returned by 'start'. Required when `_action='poll'`.
promptNoIdea for the song. When `lyrics_mode='auto'` the AI uses this as the subject; when `lyrics_mode='write'` the contents become the actual lyrics. Equivalent to the 'Pomysł lub tekst / Idea or lyrics' field on boost.audio.
stylesNoUp to 6 style preset ids from `/tools/song-styles` (e.g. ['lofi-hip-hop','synthpop','ambient']). Use `_action='styles'` to fetch the catalogue.
_actionNoInternal action selector used by the widget. 'start' kicks off generation, 'poll' returns the current status, 'lyrics' asks Boost Audio AI to draft lyrics, 'styles' returns the style preset catalogue.
_inlineNoInternal flag set by the widget when it wants the MCP server to drive the generation pipeline.
durationNoTrack length in seconds (30-180). Defaults to 120.
key_scaleNoOptional musical key, e.g. 'A minor' or 'C major'.
_pollSecretNoInternal: poll secret returned by 'start'. Required when `_action='poll'`.
inspirationNoStyle, inspiration and arrangement notes (e.g. 'modern pop with synths, intimate vocal, wide chorus'). Maps to the 'Styl, inspiracje i instrukcje / Style, inspiration and instructions' field on boost.audio.
lyrics_modeNo'auto' = AI writes lyrics from your idea (default). 'write' = treat `prompt` as ready-to-sing lyrics.
instrumentalNoIf true, no vocals are generated. Defaults to false.

TDQS

A3.9/5.0
Behavior3/5

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

With annotations (readOnlyHint=false) indicating a mutating operation, the description adds that it returns a mix and optionally separated stems. However, it omits the asynchronous job workflow (start/poll) and does not disclose that generation takes time or requires polling, which is important behavioral context not conveyed by the annotations.

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 three sentences, each earning its place: the first states the core action, the second describes the return value, and the third gives usage context. There is no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the rich schema and annotations, the description does not explain the multi-step workflow involving `_action='start'`, `_action='poll'`, and internal secrets. While the schema covers these details, the description alone would not fully guide an agent on how to correctly invoke this tool for a generation task, especially without an output schema.

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

Parameters3/5

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

The schema covers 100% of parameters with detailed descriptions, so the baseline is 3. The description does not add additional parameter meaning except implicitly referencing 'text prompt' which maps to the `prompt` parameter, but this is also clearly described in 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 the tool generates a full audio track from a text prompt, which is a specific verb+resource. It also distinguishes from siblings by explicitly mentioning AI-generated music, instrumentals, songs with lyrics, and demos, which are capabilities unique to this generation tool.

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 provides clear when-to-use guidance: 'Use this when the user wants AI-generated music, an instrumental, a song with lyrics or a quick demo from an idea.' It gives explicit context but does not mention exclusions or alternative tools, so it falls short of a 5.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a unique audio processing task (e.g., BPM/key detection, format conversion, stem splitting) with no functional overlap, ensuring agents can easily distinguish between them.

Naming Consistency5/5

All tool names follow a strict `boost_audio_verb_noun` pattern in snake_case, providing a predictable and clean naming convention across the entire set.

Tool Count5/5

With exactly 8 tools, the server is well-scoped for an audio processing domain—comprehensive enough to cover key tasks without being overwhelming or sparse.

Completeness4/5

The tools cover essential audio operations (conversion, extraction, generation, splitting, trimming, etc.), but a merging or concatenation tool is missing, leaving a minor gap.

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