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creative-tagger-mcp

creative-tagger-mcp

by stephenlavender
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_taxonomy

Fetch the controlled vocabulary for creative tagging, including 15 standard dimensions, aspect-ratio, and brand-specific fields. Use it to understand available classifications before analyzing creatives.

Instructions

Get Creative Tagger taxonomy v2's 15 controlled dimensions, one derived/open aspect-ratio dimension, and two dynamic, brand-specific dimensions. The package ships a versioned vocabulary because the API schema does not expose enums for every classification field. Use this before analyze_creative when you want to know the vocabulary the system understands. Taxonomy v2: media type (the auto-detected format — static image, video, carousel), asset type (production class), and visual format (execution style) are three separate dimensions; 'Static Image' and 'Carousel' are media types, not visual_format values.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_taxonomy"
  }
}

Input Schema

NameRequiredDescriptionDefault
dimensionNoOptional: fetch one dimension only (e.g. 'hook_type', 'messaging_angle').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

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 burden. It does not explicitly state that this is a read-only operation or disclose any behavioral traits like rate limits or authorization needs. The information about versioned vocabulary is useful but not behavioral.

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 well-structured, front-loading purpose and usage, then clarifying taxonomy details. It is informative without excessive length, though some redundancy exists in the taxonomy explanation.

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?

With no output schema, the description should ideally describe the return format. While it mentions 'versioned vocabulary' and dimensions, it lacks explicit details on output structure or example, making it adequate but not complete.

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 input schema covers 100% of the parameter ('dimension') with an example and description. The tool description adds high-level context about dimensions but does not enhance the parameter meaning beyond what the schema already provides, so baseline 3 applies.

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 clearly states the tool retrieves 15 controlled dimensions, one derived/open aspect-ratio dimension, and two brand-specific dimensions, with versioned vocabulary. It distinguishes from sibling tools by explicitly recommending use before analyze_creative.

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

Usage Guidelines5/5

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

The description explicitly says 'Use this before analyze_creative when you want to know the vocabulary the system understands,' providing clear when-to-use guidance with a named sibling tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

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