list_modelsFind available video and image generation models, including Veo 3.1, Grok Imagine, and Nano Banana, to choose the right one for text-to-video, image-to-video, image generation, or editing.
List the video and image models this server can generate with, and what each is for.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. 'List' implies a read-only operation, but the description does not explicitly state that it has no side effects or describe the shape of the returned model list. This is adequate but leaves the safety profile implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the action and resource. Every word adds meaning, and there is no wasted or redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, the description covers the core return value and purpose: available models and what each is for. It does not explicitly state that the returned model identifiers can be used as inputs to generate_video/generate_image, which would make it slightly more actionable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema description coverage is 100%, so there are no parameter semantics for the description to clarify. With no parameters, the baseline is 4, and the description appropriately focuses on the tool's output and purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific action ('List') and a specific resource ('video and image models this server can generate with'), and it adds the purpose of each model. This clearly distinguishes it from the siblings generate_video, generate_image, and check_job.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'models this server can generate with' clearly implies this tool is for discovering generation capabilities before using generate_video or generate_image. It gives clear usage context, though it stops short of explicitly saying 'use before generating' or naming non-use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.