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suno_get_task

Check if a music generation task has finished and retrieve the resulting audio URLs, title, lyrics, and metadata from the task ID.

Instructions

Query the status and result of a music generation task.

Use this to check if a generation is complete and retrieve the resulting
audio URLs, titles, lyrics, and other metadata.

Use this when:
- You want to check if a generation has completed
- You need to retrieve audio URLs from a previous generation
- You want to get the full details of a generated song

Task states:
- 'pending': Generation is still in progress — KEEP POLLING
- 'processing': Generation is being processed — KEEP POLLING
- 'complete': Generation finished successfully
- 'failed': Generation failed (check error message)

The API may omit its top-level state. The MCP normalizes response.success=true to
complete and response.success=false to failed; responses without a success field
remain pending.

Returns:
    Task status and generated audio information including URLs, title, lyrics, and task timing metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYesThe task ID returned from a generation request. This is the 'task_id' field from any suno_generate_*, suno_extend_*, suno_cover_*, or suno_concat_* tool response.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.1.5
  2. Removedv0.1.3
  3. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and excels: it documents task states, clarifies polling behavior, and explains the MCP's normalization of omitted success fields. This gives agents a detailed model of the tool's runtime behavior beyond the basic read/edit nature.

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 leading purpose sentence, 'Use this when' bullets, task state definitions, and a returns summary. It is front-loaded, scannable, and every sentence contributes value without redundancy.

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 simple polling nature and the presence of an output schema, the description covers all necessary context: when to use, states to expect, normalization behavior, and what results are returned. It fully equips an agent to correctly invoke and interpret the tool.

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 input schema already provides 100% parameter coverage and a detailed description of task_id, including its source from generation tools. The description adds minimal extra parameter nuance, mostly reiterating 'previous generation' and 'task_id' provenance, so it meets the baseline without significantly enhancing schema semantics.

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 ('Query') and resource ('a music generation task'), and clearly distinguishes it from sibling generation/composition tools by focusing on status polling and result retrieval. The opening line and subsequent details unambiguously identify the tool's function.

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?

Provides explicit 'Use this when' bullets covering polling and result retrieval, which gives clear contextual signals. However, it does not mention when not to use it or alternative tools (e.g., suno_get_tasks_batch for batch queries), so it lacks exclusionary guidance.

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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