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Arkeonix CapCut MCP

Arkeonix CapCut MCP

by daviilpzDev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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capcut_set_canvas

Change the project canvas aspect ratio or set custom dimensions to prepare videos for TikTok, Reels, YouTube, or square formats.

Instructions

Change project canvas aspect ratio (e.g. "9:16" for TikTok/Reels, "16:9" for YouTube, "1:1" for Square).

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>",
      "ratio": "<ratio>"
    },
    "name": "capcut_set_canvas"
  }
}

Input Schema

NameRequiredDescriptionDefault
draftYes
ratioYesaspect ratio preset
widthNocustom width in pixels
heightNocustom height in pixels

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior2/5

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

No annotations exist, so the description carries full responsibility for behavior. It only says 'Change project canvas aspect ratio' and omits side effects on existing media (e.g., cropping, stretching, letterboxing) or whether custom dimensions override preset ratio. This is a significant gap for a mutating tool.

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?

One sentence with useful examples and zero filler. The key action is front-loaded, and each clause adds 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?

For a 4-parameter tool with no annotations and no output schema, the description is too thin. It fails to explain custom dimension use, relationship between ratio and width/height, and what 'draft' refers to, leaving an agent to infer required parameter combinations. The examples cover preset ratios only.

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?

The schema already describes ratio, width, and height, covering 75% of params; the description adds value by mapping presets to platforms. However, it doesn't explain the draft parameter or how custom width/height interact with ratio, which an agent needs to construct correct calls.

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?

States a clear verb+resource: 'Change project canvas aspect ratio'. The examples ('9:16' for TikTok/Reels, etc.) reinforce the precise scope. This is distinct from sibling tools like capcut_set_canvas_blur, which targets blur.

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 concrete use-case context via platform-specific ratio examples, telling an agent when to pick a ratio. It does not name alternative tools or explicitly state exclusions, but the domain is so specific (canvas ratio) that confusion is unlikely. Enough guidance to select the tool over unrelated canvas tools.

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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