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Copyseeker MCP Server

Copyseeker MCP Server

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by copyseeker-net
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TypeScript
Local

Detect AI-generated image

detect_ai_image
Read-only

Determine whether an image is AI-generated or a real photo or artwork by analyzing an image URL or local file, with results useful for verification and content checks.

Instructions

Tell whether an image was generated by AI (Midjourney, DALL-E, Stable Diffusion, Flux and similar) or is a real photo or artwork. Costs 0.01 credits.

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": {
      "image": "<image>"
    },
    "name": "detect_ai_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYesDirect URL of the image file (http or https, not the web page showing it), or the absolute path to a local image file up to 20 MB.

Output Schema

NameRequiredDescriptionDefault
confidenceYesHow sure the verdict is, from 0 to 1.
isAiGeneratedYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.3

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely new context: a concrete cost of 0.01 credits and the set of generators it can recognize, which matters for deciding whether to spend credits. It stops short of describing confidence, accuracy limits, or handling of ambiguous images.

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?

Two sentences, front-loaded with the capability and closed with the cost constraint. No filler, no repetition of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

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 no explanation, and the tool is a single-parameter read with a disclosed cost. The only gap is the absence of any note on reliability or what a borderline verdict means, which would matter for an agent interpreting results.

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 coverage is 100% and the single 'image' parameter already documents accepted forms (direct URL vs. absolute local path, 20 MB cap). The description adds no parameter meaning beyond that, so the baseline of 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?

States a specific verb and resource ('Tell whether an image was generated by AI') and enumerates the generator families in scope while contrasting with 'real photo or artwork'. This is clearly distinct from detect_nsfw (content safety) and reverse_image_search (provenance lookup).

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?

The purpose implies when to use it, but the description gives no explicit routing guidance, no prerequisites, and no mention of when to prefer siblings like reverse_image_search. Usage is inferred rather than 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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