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AceDataCloud

ProducerMCP

by AceDataCloud
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

producer_generate_music

Generate music from a text prompt. Describe genre, mood, and theme to get AI-composed music with lyrics, melody, and arrangement.

Instructions

Generate AI music from a text prompt using Producer/Riffusion.

This is the simplest way to create music - just describe what you want and
Producer will automatically generate appropriate lyrics, melody, style, and
arrangement.

Use this when:
- You want quick music generation with minimal input
- You don't have specific lyrics in mind
- You want the AI to be creative with the arrangement

For full control over lyrics and style, use producer_generate_custom_music instead.

Returns:
    Task ID and generated audio information including URLs, title, lyrics, and duration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoSeed for reproducible generation. Reuse the same seed to reproduce a result.
modelNoProducer model version. 'FUZZ-2.0' is the default and recommended for most use cases. 'FUZZ-2.0 Pro' offers the highest quality. 'FUZZ-2.0 Raw' provides raw unprocessed output.FUZZ-2.0
promptYesDescription of the music to generate. Be descriptive about genre, mood, instruments, and theme. Examples: 'A happy birthday song with acoustic guitar', 'Epic orchestral battle music with dramatic choir', 'Chill lo-fi hip hop beat for studying'
weirdnessNoCreative control for how experimental/unusual the generation is. Range 0-1.
callback_urlNoWebhook callback URL for asynchronous notifications. When provided, the API will call this URL when the audio is generated.
instrumentalNoIf true, generate instrumental music without vocals. Default is false (with vocals).
sound_strengthNoCreative control for how strongly the sound/style drives the generation. Range 0-1.
lyrics_strengthNoCreative control for how strongly the lyrics drive the generation. Range 0-1.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It explains that the tool auto-generates lyrics, melody, style, and arrangement, and returns a Task ID and audio info. However, it does not disclose potential quirks like generation time limits, quota, or how to handle the async task lifecycle, leaving some gaps.

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 well-structured with a clear first sentence, bullet points for when to use, and a separate returns section. No redundant information; every sentence contributes to clarity.

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 tool's complexity (8 params, generative, async) and the presence of an output schema, the description fully addresses the necessary context: purpose, usage guidance, return type (Task ID and audio details), and alternative tool. It does not need to explain the full lifecycle because that is covered by sibling tools like producer_get_task.

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?

Schema coverage is 100% with good parameter descriptions. The description adds value by grouping parameters (creative controls like weirdness, sound_strength, lyrics_strength) and contextualizing the prompt as the main input with examples. This enhances understanding beyond the schema's individual field descriptions.

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?

Clearly states 'Generate AI music from a text prompt', with specific verb and resource. Distinguishes from sibling tool 'producer_generate_custom_music' by noting it's for quick generation with minimal input, and explicitly tells when to use the alternative for full control.

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

Usage Guidelines5/5

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

Provides explicit 'Use this when' bullet points (quick generation, no specific lyrics, AI creativity) and a direct alternative for full control. Clearly tells the agent when to select this tool versus the custom music variant.

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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