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if530770

redfox-mcp-server

by if530770

seedance-video-gen

Generate videos from text prompts or reference images, automatically wait for completion, and return a video link with customizable duration, resolution, and audio.

Instructions

AI视频生成工具,基于豆包 Seedance 2.0 模型,输入文字提示词生成视频(自动等待任务完成并返回视频链接)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo随机种子,-1为随机
ratioNo画面比例16:9
promptYes视频内容描述提示词
durationNo视频时长(秒)
imageUrlNo参考图片URL(图生视频)
watermarkNo是否带水印
resolutionNo分辨率720p
generateAudioNo是否生成音频
returnLastFrameNo是否返回最后一帧图片

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.4

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It does disclose an important runtime behavior: the tool automatically waits for the task to complete and then returns a video link. However, it does not mention potential wait duration, failure modes, pricing, or credit implications, so the disclosure is partial.

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?

The description is a single compact sentence with no filler. It front-loads the tool purpose, adds the model identity, and ends with the most operationally relevant behavior: waiting for completion and returning the link.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, and the description does state the return type: a video link. It also covers the key operational behavior of automatic waiting, which is the main uncertainty an agent would face. Detailed parameter choices are left to the fully described schema, so the description is sufficient even though it does not summarize image-to-video support.

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 description coverage is 100%, so the baseline is 3. The description adds little parameter-level meaning beyond restating that text prompts are the input, and it omits the image-to-video capability obvious from the imageUrl parameter, though the schema already documents that.

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?

The description states a specific action and resource: generate video from a text prompt using the Doubao Seedance 2.0 model. It clearly distinguishes this tool from the sibling set, which contains mostly downloaders, search tools, feed aggregators, and content writers rather than video generators.

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?

The description provides clear context: use this tool when the agent needs to generate a video from a prompt. It does not explicitly name alternatives or when-not conditions, but no sibling tool appears to offer the same video generation capability, so an explicit exclusion is less critical.

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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