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elibarnett

kie-mcp

by elibarnett
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

add_instrumental

Generate instrumental backing for uploaded vocal audio via Suno, using style tags and async polling for long jobs.

Instructions

Add instrumental backing to uploaded vocal audio via Suno.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoStyle tags for the instrumental
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
titleNo
filenameNo
uploadUrlYesURL of vocal 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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv5.5.0
    • changedInput schema / properties / model / enum
      Previous value: -[
-  "V3_5",
-  "V4",
-  "V4_5",
-  "V4_5PLUS",
-  "V4_5ALL",
-  "V5",
-  "V5_5"
-]New value: +[
+  "V4",
+  "V4_5",
+  "V4_5PLUS",
+  "V4_5ALL",
+  "V5",
+  "V5_5",
+  "V6",
+  "V6_MINI",
+  "V6_WILD"
+]
  2. First observedv4.7.0

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 does not disclose that by default the call blocks up to ~300s (watchdog timeouts possible), that async polling with check_task/download_result is required for long runs, or any prerequisite about the uploaded vocal audio. These behaviors are buried in schema field descriptions, not stated in the description.

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?

A single, front-loaded sentence with no waste. Being terse is efficient, though it borders on under-specification given the tool's async complexity.

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 9-parameter audio-generation tool with an async polling workflow, no annotations, and no output schema, the description is far too thin. It omits the blocking-vs-async behavior, failure modes, and parameter semantics that an agent needs to invoke it correctly.

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 coverage is 56%, leaving several parameters (title, filename, negativeTags, model) undocumented. The description adds no parameter meaning at all. With over a third of parameters uncovered and no compensating text, this is weak.

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?

The description states a specific verb ('Add') and resource ('instrumental backing') with the input ('uploaded vocal audio') and provider ('Suno'). This is clear but does not differentiate it from the close sibling add_vocals, which is essentially the inverse operation.

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?

There is no guidance on when to use this versus siblings like generate_music, add_vocals, or extend_music. The async workflow is described inside a parameter schema rather than in the description, and the description gives no context selection criteria.

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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