CapCut MCP Server

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capcut_add_captions

Add styled captions to a CapCut timeline from timed JSON entries, specifying caption text, start milliseconds, duration, and an optional preset.

Instructions

Add styled captions to the CapCut timeline. captions_json format: [{"text": "...", "start_ms": 0, "duration_ms": 1500}]

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_name": "<draft_name>",
      "captions_json": "<captions_json>"
    },
    "name": "capcut_add_captions"
  }
}

Input Schema

Name	Required	Default
`preset`	No	tiktok_bold
`draft_name`	Yes
`captions_json`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 11, 2026

TDQS

C2.7/5.0

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 behavioral burden. It says 'add' but doesn't disclose whether captions append or overwrite, whether a render is required afterward, or what the 'preset' styling actually changes – only the captions_json shape is given.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short lines, front-loaded with purpose then the required data format. Nothing is wasted, though the brevity contributes to the under-specification rather than being purely efficient.

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?

An output schema exists so return values need not be explained, but for a mutation tool with zero annotations the description should say more about side effects, sibling routing, and the undocumented preset/draft_name parameters to be callable with confidence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for all three parameters. It usefully documents the captions_json format, but leaves draft_name and especially the 'preset' parameter (default 'tiktok_bold') with no explanation of accepted values or effect.

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 states a specific verb (Add), resource (styled captions) and target (CapCut timeline), so the agent knows the operation precisely. However it gives no differentiation from the sibling capcut_add_karaoke_captions, which is a plausible conflicting choice.

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 explicit when-to-use or when-not-to-use guidance. The presence of capcut_add_karaoke_captions as a close sibling makes this omission notable, since nothing tells the agent which caption tool to pick.

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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