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hailuo_list_models

Retrieve all Hailuo video generation models with descriptions and use cases to select the right model for your video.

Instructions

List all available models for Hailuo video generation.

Shows all available model options with their descriptions and use cases.
Use this to understand which model to choose for your video.

Returns:
    Table of all models with their descriptions and use cases.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the hailuo_list_models tool. It is decorated with @mcp.tool() and returns a string table of available Hailuo (MiniMax) video models (minimax-t2v, minimax-i2v, minimax-i2v-director) with descriptions and use cases.
    @mcp.tool()
    async def hailuo_list_models() -> str:
        """List all available models for Hailuo video generation.
    
        Shows all available model options with their descriptions and use cases.
        Use this to understand which model to choose for your video.
    
        Returns:
            Table of all models with their descriptions and use cases.
        """
        # Last updated: 2026-04-05
        return """Available Hailuo (MiniMax) Video Models:
    
    | Model                  | Type            | Description                                      | Requires Image |
    |------------------------|-----------------|--------------------------------------------------|----------------|
    | minimax-t2v            | Text-to-Video   | Generate video from text prompt (default)        | No             |
    | minimax-i2v            | Image-to-Video  | Generate video from a reference image            | Yes            |
    | minimax-i2v-director   | Director Mode   | Image-to-video with more creative control        | Yes            |
    
    Recommended:
    - Use minimax-t2v for pure text-to-video generation (no image needed)
    - Use minimax-i2v when you have a reference image to animate
    - Use minimax-i2v-director for director-style control over image-to-video
    """
  • The tool is registered via the @mcp.tool() decorator, which comes from the FastMCP instance in core/server.py (line 48).
    @mcp.tool()
    async def hailuo_list_models() -> str:
  • The FastMCP server (mcp) is initialized here. The @mcp.tool() decorator used in info_tools.py references this mcp instance, which is what registers the tool with the MCP framework.
    mcp = FastMCP(
        settings.server_name,
        icons=[Icon(src="", mimeType="image/png")],
        **mcp_kwargs,
    )
    
    logger.info(f"Initialized MCP server: {settings.server_name}")
  • main.py:176-179 (registration)
    The tool name 'hailuo_list_models' is listed in the server card JSON for HTTP transport mode (line 176-179).
    {
        "name": "hailuo_list_models",
        "description": "List available models",
    },
  • main.py:124-124 (registration)
    The tool name is printed in the 'Available tools' list during server startup (line 124).
    safe_print("    - hailuo_list_models")
Behavior2/5

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

With no annotations provided, the description carries the full burden. It only states that it 'shows all available model options with their descriptions and use cases' and returns a table. It lacks any disclosure about side effects, safety, or performance implications, leaving behavioral aspects largely untransparent.

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?

The description is relatively short but contains some redundancy. The second sentence ('Shows all...') partially duplicates the first, and the 'Returns' line restates the output. A single concise sentence would be sufficient.

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 tool has no parameters and an output schema exists, the description covers its purpose and return value adequately. However, it could hint at whether the model list is static or dynamic, making it slightly incomplete.

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?

There are no parameters (0 params), and the schema description coverage is 100%. Per the guidelines, baseline for 0 params is 4. The description does not need to add parameter info, and it mildly adds context about what the output includes.

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 clearly states the action ('List all available models') and the resource ('Hailuo video generation'). It is specific and distinguishes from siblings by its listing purpose, though it does not explicitly differentiate from other sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a usage hint ('Use this to understand which model to choose for your video'), providing context. However, it does not specify when not to use it or mention alternatives, leaving implicit guidance.

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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