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add_vocals

Add AI-generated vocals to an uploaded instrumental audio track using Suno models. Provide lyrics or a vocal description to customize the output.

Instructions

Add AI vocals to uploaded instrumental audio via Suno.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoSet false to submit and return immediately with the task_id (async mode) — then poll with check_task and fetch with download_result. Recommended for long generations to avoid client-side watchdog timeouts.
modelNoV5
styleNo
titleNo
promptYesLyrics or vocal description
filenameNo
uploadUrlYesURL of instrumental audio
download_dirNoAbsolute directory to save the file(s) into (created if missing). Defaults to the server's kie/assets/raw/. Must be absolute — the MCP server's working directory is not the caller's.
negativeTagsNo
max_wait_secondsNoOverride the blocking-mode polling budget in seconds (default: audio 300). Ignored when wait=false.
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It does not mention authentication needs, rate limits, whether the operation is destructive, or the possibility of asynchronous execution (despite 'wait' and 'max_wait_seconds' parameters existing in 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (one sentence), which is concise, but it is also incomplete for a tool with 10 parameters and async behavior. It does not effectively use the limited space to convey critical information.

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

Completeness2/5

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

For a complex tool with 10 parameters, no output schema, and async mode, the description is severely lacking. It does not describe return values, how to handle async results, or the purpose of key parameters like 'wait' and 'model'.

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

Parameters2/5

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

Schema description coverage is only 50%, but the description adds no parameter information beyond what the schema already provides. It does not explain the meaning of 'prompt', 'uploadUrl', 'model', or the async mode behavior, which would be valuable.

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 uses a specific verb ('Add'), a clear resource ('AI vocals'), and context ('to uploaded instrumental audio via Suno'). It effectively distinguishes from sibling tools like generate_music (creates music from scratch) or add_instrumental (adds instrumental to vocals).

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?

The description provides no guidance on when to use this tool versus alternatives (e.g., generate_music, separate_vocals). No when-to-use or when-not-to-use information is included.

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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