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Arkeonix CapCut MCP

Arkeonix CapCut MCP

by daviilpzDev
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capcut_apply_animation

Apply in, out, or loop animations to a video clip, image, or text overlay by providing the segment ID, animation name, and optional duration.

Instructions

Apply an in/out/loop animation to a video clip, image, or text overlay.

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": {
      "draft": "<draft>",
      "segmentId": "<segmentId>",
      "animation": "<animation>"
    },
    "name": "capcut_apply_animation"
  }
}

Input Schema

NameRequiredDescriptionDefault
draftYes
startSecNostart offset within the segment in seconds
animationYesanimation name, English label, or effect ID (e.g. "Fade In", "渐显", "Zoom In")
segmentIdYestarget segment ID (video clip, image, or text overlay)
durationSecNoanimation duration in seconds
animationTypeNoanimation type (defaults to catalog type)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, yet it only states the basic operation. It does not mention whether applying an animation overwrites an existing one, how the animation type defaults work, or what happens when 'group' is used.

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 clear sentence with no filler. It front-loads the action and then states the applicable targets, making it easy for an agent to parse quickly.

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?

The description plus schema is minimally sufficient for calling the tool, but it lacks usage context such as referencing capcut_list_animations for valid animation names and does not describe return behavior. For a 6-parameter tool with no annotations and no output schema, more contextual detail would be expected.

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 high at 83%, and the schema already documents segmentId, animation, animationType, startSec, and durationSec. The description adds no parameter meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Apply') and resource ('an in/out/loop animation') and explicitly names the target types: video clip, image, or text overlay. This clearly distinguishes it from sibling tools like capcut_apply_effect or capcut_apply_transition.

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 use this tool versus alternatives such as capcut_list_animations, capcut_apply_effect, or capcut_apply_transition. An agent is not told how to discover valid animation names or when animation application is preferred over effects/transitions.

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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