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SunoMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

suno_underpainting

Add AI-generated instrumental backing to an uploaded vocal track, turning an acapella recording into a full arrangement with control over where the music starts and ends.

Instructions

Add AI-generated accompaniment/instrumental background to uploaded audio.

Takes your uploaded vocal track and adds an AI-generated instrumental
accompaniment beneath it (underpainting = adding music under vocals).

Use this when:
- You have a vocal recording and want to add music behind it
- You want to give an acapella track a full musical arrangement
- You need to add instrumental backing to existing vocals

Returns:
    Task ID and the audio with accompaniment added.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel version to use.chirp-v5-5
audio_idYesID of the uploaded audio to add accompaniment to. Must be uploaded via suno_upload_audio.
callback_urlNoWebhook callback URL for asynchronous notifications.
underpainting_endNoEnd time in seconds for adding accompaniment. Must be less than total song duration.
underpainting_startNoStart time in seconds for adding accompaniment. Default is 0.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.18
    • changedInput schema / properties / model / enum
      Previous value: -[
-  "chirp-v3-0",
-  "chirp-v3-5",
-  "chirp-v4",
-  "chirp-v4-5",
-  "chirp-v4-5-plus",
-  "chirp-v5",
-  "chirp-v5-5"
-]New value: +[
+  "chirp-v6",
+  "chirp-v6-wild",
+  "chirp-v6-mini",
+  "chirp-v3-0",
+  "chirp-v3-5",
+  "chirp-v4",
+  "chirp-v4-5",
+  "chirp-v4-5-plus",
+  "chirp-v5",
+  "chirp-v5-5"
+]
  2. Addedv0.1.5
  3. Removedv0.1.3
  4. Addedv0.1.1

TDQS

A3.7/5.0
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 discloses that the tool returns a 'Task ID and the audio with accompaniment added,' implying asynchronous operation, and requires prior upload via suno_upload_audio. However, it does not explain side effects (whether the original is modified), how to poll for completion using the Task ID, or any rate limits/auth requirements. The description adds some value but is not rich in behavioral disclosure.

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 relatively concise but contains redundancy: the three 'Use this when' bullets essentially restate the same idea (adding instrumental backing to vocals). The Returns section adds useful info but could be merged. It's not excessively long, but the redundancy detracts from conciseness.

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?

The tool has 5 parameters, an async return (Task ID), and an output schema (not shown here). The description explains the core purpose and return shape, but omits practical details like how to retrieve the result using the Task ID, or when callback_url should be used. Given the complexity and reliance on output schema, the description is adequate but not complete.

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?

Schema description coverage is 100%, so the parameters are fully documented in the schema. The description adds minimal extra meaning beyond the schema—it implicitly explains audio_id's role ('uploaded vocal track') and the underpainting concept, but does not elaborate on underpainting_start/end or callback_url beyond their schema descriptions. At 100% coverage, the baseline 3 is appropriate.

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 specific verb and resource: 'Add AI-generated accompaniment/instrumental background to uploaded audio.' It distinguishes the operation from the sibling suno_overpainting by explicitly defining underpainting as 'adding music under vocals,' which disambiguates what this tool does.

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 a clear 'Use this when' list with three concrete scenarios (vocal recording needs backing, acapella needs arrangement, instrumental backing needed). However, it lacks any when-not-to-use guidance or explicit mention of alternatives like suno_overpainting or suno_extend_music. It gives clear context but no exclusions, earning a 4.

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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