Skip to main content
Glama

suno_list_models

List and compare Suno AI music models to check version limits, features, and capabilities. Choose the right model for your music generation needs based on duration and quality.

Instructions

List all available Suno models and their capabilities.

Shows all available model versions with their limits, features, and
recommended use cases. Use this to understand which model to choose
for your music generation.

Model comparison:
- chirp-v5-5: Latest, highest quality, 8-minute max duration
- chirp-v5: High quality, 8-minute max duration
- chirp-v4-5-plus: High quality with 8-minute duration
- chirp-v4-5: Recommended balance of quality and speed, 4-minute duration
- chirp-v4: Good quality, 150 seconds max
- chirp-v3-5/v3: Legacy models, 120 seconds max

Returns:
    Table of all models with their version, limits, and features.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. Discloses return value structure ('Table of all models with their version, limits, and features') and enumerates specific model versions with capabilities, which is essential behavioral context for this domain.

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?

Well-structured with front-loaded purpose, followed by usage context, detailed model comparison bullets, and return specification. Every element serves the agent's decision-making process; model specs are essential data despite length.

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 complex model ecosystem (6+ versions), the detailed comparison table provides critical contextual completeness. Output schema exists but description appropriately summarizes it while adding rich domain-specific details (duration limits, quality tiers).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters present with empty input schema. Per guidelines, baseline score is 4 for zero-parameter tools. Description appropriately focuses on return value semantics rather than non-existent parameters.

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?

Explicitly states 'List all available Suno models and their capabilities' with specific verb and resource. Clearly distinguishes from action-oriented siblings (generate, extend, cover) by focusing on metadata/discovery rather than music manipulation.

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 clear when-to-use guidance: 'Use this to understand which model to choose for your music generation.' Implicitly contrasts with generation tools but lacks explicit 'when not to use' or direct references to sibling dependencies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AceDataCloud/MCPSuno'

If you have feedback or need assistance with the MCP directory API, please join our Discord server