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Copyseeker MCP Server

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by copyseeker-net
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TypeScript
Local

Detect NSFW image

detect_nsfw
Read-only

Checks an image URL or local file for nudity or sexual content, returning an NSFW verdict to screen images before sharing.

Instructions

Tell whether an image contains nudity or sexual content that is not safe for work. 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_nsfw"
  }
}

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
isNsfwYes
confidenceYesHow sure the verdict is, from 0 to 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.3

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already establish readOnlyHint, destructiveHint=false, and openWorldHint, so the safety profile is covered. The description adds substantive information not in the annotations: a concrete cost of 0.01 credits per call, which matters for an agent deciding whether to batch or avoid redundant invocations. It does not address the non-obvious idempotentHint=false flag or latency/confidence behavior.

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, zero filler, with the classification purpose front-loaded and the cost constraint following. Every sentence earns its place.

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?

The tool is simple: one fully documented parameter, an output schema that carries return values, and annotations covering safety. Cost is disclosed, but nothing is said about the paid nature implying possible quota/auth prerequisites, nor about how to interpret the verdict, leaving a small 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 coverage is 100% and the single 'image' parameter is documented thoroughly (URL vs local path, format, 20 MB limit), so the description need not restate it. The description adds no meaning beyond the schema, which is the expected baseline here.

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 uses a specific verb ('Tell whether') tied to a precise resource and content class ('nudity or sexual content that is not safe for work'), which is clearly distinguishable from the AI-image and reverse-search siblings. It stops short of naming those siblings, so no explicit differentiation is offered.

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?

Usage is only implied by the task description — an agent can infer 'call this when you need an NSFW verdict on an image'. There is no explicit when-to-use framing, no exclusions, and no comparison to detect_ai_image or reverse_image_search for overlapping moderation scenarios.

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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