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Wan30 MCP

Wan30 MCP

by NotUsingGithub
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get_model

Read-only

Retrieves details and input options for a selected Wan 3.0 video model, so you can choose the right text-to-video, image-to-video, or reference-to-video workflow.

Instructions

Input options for the selected video model.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "modelId": "<modelId>"
    },
    "name": "get_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelIdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.1/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so only safety is covered. The description adds nothing about what is returned (model metadata? input schema? constraints?), whether all three models share the same options, or any rate or availability behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single short sentence with no wasted words, but the brevity is under-specification rather than efficiency – the one sentence carries almost no information.

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?

With no output schema and no meaningful annotations beyond read-only, the description should explain what the tool returns and how its result feeds generate_video or estimate_generation. It omits all of that, leaving an agent unable to decide between this and list_models.

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 description coverage is 0% and the single required modelId is documented only by its enum. The phrase 'the selected video model' weakly suggests modelId identifies a model, but adds no meaning about the enum values or what selection implies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The sentence 'Input options for the selected video model' restates the title rather than stating what the tool does – it never says it retrieves a model's definition, capabilities, or parameter schema. An agent cannot tell from this how get_model differs from list_models or estimate_generation.

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 call this instead of list_models, or whether it must be called before generate_video. The word 'selected' hints at a prerequisite but never states the workflow.

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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