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suno-mcp

by runapi-ai
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TypeScript
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stitch_audio

Create a Suno task on RunAPI that stitches audio from a completed source task and audio ID. Returns a task ID, status, and output URLs.

Instructions

Create a Suno task on RunAPI (stitch audio). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
audio_idYesAudio ID within the source task. Declared type: string.
timeout_msNo
callback_urlNoWebhook URL for async notifications. Declared type: string.
source_task_idYesCompleted source task ID. Declared type: string.
poll_interval_msNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.4.0
    • addedInput schema / additionalProperties
      Added value: +{}
    • changedInput schema / properties / audio_id / description
      Previous value: -"Audio ID within the source task."New value: +"Audio ID within the source task. Declared type: string."
    • changedInput schema / properties / callback_url / description
      Previous value: -"Webhook URL for async notifications."New value: +"Webhook URL for async notifications. Declared type: string."
    • removedInput schema / properties / model / enum
      Removed value: -[
-  "suno-v4",
-  "suno-v4.5",
-  "suno-v4.5-plus",
-  "suno-v5",
-  "suno-v5.5"
-]
    • changedInput schema / properties / source_task_id / description
      Previous value: -"Completed source task ID."New value: +"Completed source task ID. Declared type: string."
  2. Addedv0.3.2

TDQS

C2.7/5.0
Behavior2/5

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 says a task is created and returns task id, status, and output URLs, but omits side effects, authentication needs, async/polling behavior (wait, callback_url), cost, and reversibility.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Two sentences with purpose front-loaded and return values second. There is no filler, though the parenthetical phrasing is slightly terse.

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 7-parameter task-creation tool with no annotations and no output schema, the description is not complete enough. It mentions return fields but omits async behavior, parameter roles, and usage context.

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 71%, and the description adds no parameter meaning. It does not explain source_task_id, audio_id, model, timeout_ms, poll_interval_ms, or the wait/callback_url semantics beyond what the schema already says.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States the verb 'Create' and resource 'Suno task' with the parenthetical '(stitch audio)', so the core operation is identifiable. It does not differentiate from siblings like convert_audio or create_mashup, leaving the intended scope somewhat ambiguous.

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?

Provides no when-to-use guidance, prerequisites, or alternatives. Usage is only implied by the tool name and the required source_task_id/audio_id parameters.

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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