AIGigLab MCP Server

replicate_wan_t2v

Generate high-quality videos from text prompts using Wan 2.5. Customize resolution, duration, and negative prompts; optionally add audio or expand prompts automatically.

Instructions

Generate a high-quality video from text using Wan 2.5 Text-to-Video.

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": {
      "prompt": "<prompt>"
    },
    "name": "replicate_wan_t2v"
  }
}

Input Schema

Name	Required	Description	Default
`seed`	No	Random seed for reproducibility
`size`	No	Video resolution	1280*720
`prompt`	Yes	The text prompt for video generation
`duration`	No	Duration in seconds (5 or 10)
`audioPath`	No	Absolute path to a local audio file to drive the video
`negative_prompt`	No	What to avoid in the video
`enable_prompt_expansion`	No	Enhance prompt automatically

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.3.0Jul 15, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations provided, and the description does not disclose behavioral traits such as cost, processing time, or effects on system state. The 'generate' verb implies creation but no further details.

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?

Single sentence is concise but under-specified. It could include more detail without being verbose.

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 7 parameters, no output schema, and no annotations, the description is too minimal. It does not explain return values or behavior, leaving the agent underinformed.

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 covers 100% of parameters with descriptions, so baseline is 3. Tool description adds no extra meaning beyond the schema; it does not clarify parameter relationships or usage nuances.

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?

Description clearly states 'Generate a high-quality video from text using Wan 2.5 Text-to-Video', specifying verb, resource, and model. However, it does not distinguish from sibling tools like 'replicate_latentsync' or 'replicate_ltx_fast' which may also generate videos.

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 on when to use this tool versus alternatives. Lacks any context about prerequisites, ideal scenarios, or exclusions.

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