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capcut-mcp

capcut-mcp

by cotlet-connect
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

capcut_click

Clicks a numbered element on the current CapCut page, enabling AI agents to select specific interface controls during CapCut automation.

Instructions

Click a numbered element on the current CapCut page.

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": {
      "element": "<element>"
    },
    "name": "capcut_click"
  }
}

Input Schema

NameRequiredDescriptionDefault
elementYesElement number from the last read.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: not what happens if the element number is stale or invalid, whether the click waits for the page to settle, whether it mutates application state destructively, or what it returns. The only behavioral hint is the statefulness implied by "current page".

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?

A single front-loaded sentence with zero filler; the target and its scope come first. Nothing could be trimmed without losing content.

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 tool is simple (one required integer, no nesting, no output schema), and the schema documents the parameter well, so the definition is minimally viable. However, for a stateful UI-automation step it omits the stale-reference and failure behavior an agent needs before invoking it, leaving a real gap.

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%, and the schema already explains that the integer is an "Element number from the last read" with a minimum of 1. The description adds no meaning beyond that (no range constraints, no re-read-after-state-change guidance), so the baseline 3 applies.

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?

States a concrete verb ("Click") and a concrete target ("a numbered element on the current CapCut page"), which is enough to distinguish it from siblings like capcut_read and capcut_type whose verbs differ. It stops short of naming any sibling explicitly, so it lands at clear-but-undifferentiated rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"On the current CapCut page" implies a prerequisite state (a page must already be open and read), but the description never says when to prefer this over capcut_read or capcut_type, nor when not to use it. Usage is inferable but not stated.

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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