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SunoMCP

SunoMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

suno_list_custom_models

List custom music models for the current Suno application, with optional status filtering and pagination controls.

Instructions

List custom music models for the current Suno application.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "suno_list_custom_models"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of custom models to return.
offsetNoNumber of custom models to skip for pagination.
statusNoOptional status filter for custom models.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.16
    • changedInput schema / properties / status / anyOf
      Previous value: -[
-  {
-    "enum": [
-      "pending",
-      "processing",
-      "ready",
-      "failed",
-      "archived"
-    ],
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "enum": [
+      "queued",
+      "uploading",
+      "training",
+      "ready",
+      "failed",
+      "archived"
+    ],
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
  2. Addedv0.1.15

TDQS

B3.3/5.0
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 of behavioral disclosure. It only says 'List custom music models' and reveals nothing about pagination behavior, default sorting, whether archived or failed models are included by default, or the read-only nature of the operation. A tool with pagination parameters (limit/offset) and a status filter should at least mention how defaults behave.

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?

A single, front-loaded sentence with no filler. It states the action, resource, and scope efficiently. There is no redundant information, and the structure is appropriate for a simple list operation.

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?

Given the low complexity and the presence of an output schema, the description covers the core purpose, and the schema covers parameters. However, the complete absence of usage guidelines and behavioral context leaves the agent without enough information to decide when to invoke this tool over alternatives or to anticipate default filtering/pagination behavior. It is minimally viable 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%, with each parameter (limit, offset, status) already documented in the input schema. The tool description adds no additional parameter context, so the baseline of 3 applies. The schema adequately explains the parameters, but the description does not enhance them further.

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 identifies the verb ('List'), the resource ('custom music models'), and the scope ('for the current Suno application'). This distinguishes it from sibling tools like suno_list_models (which likely lists base models) and suno_get_custom_model (which retrieves a single model). The purpose is unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives such as suno_get_custom_model, suno_list_models, or suno_generate_with_custom_model. The description simply states what it does without any context about prerequisites, selection criteria, or when another tool would be more appropriate.

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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