Skip to main content
Glama
gowinston-ai

winston-ai-mcp

Official
by gowinston-ai

AI Image Detection

ai-image-detection
Read-only

Detects AI-generated images by verifying metadata and using machine learning to differentiate human from AI content.

Instructions

Detects AI content in a given image by verifying image metadata and using a machine learning system trained to differentiate between human and AI-generated images. Cost: 300 credits per image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesSpecifies the URL of the image to scan. The URL must be valid, publicly accessible, and point to an image in one of the following formats: JPG, JPEG, PNG, or WEBP. The image must have a minimum resolution of 256x256 pixels.
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds transparency about the credit cost and the dual method (metadata + ML). No contradictions with annotations.

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 concise sentences: first explains the method and purpose, second states the cost. No unnecessary words, front-loaded with key information.

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 could have clarified the return format (e.g., a score or label). The tool is simple, but missing output details slightly reduces completeness.

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% with a detailed description of the url parameter (format, constraints, resolution). The description adds no additional param-level information, so baseline 3 is appropriate.

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 detects AI content in images using metadata verification and machine learning. It is distinct from sibling tools like ai-text-detection which operate on text, making the purpose unambiguous.

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 mentions a credit cost (300 credits per image), guiding usage awareness. While it does not explicitly compare to siblings, the image focus clearly differentiates it from text-oriented tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/gowinston-ai/winston-ai-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server