Copyseeker MCP Server
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| COPYSEEKER_API_KEY | Yes | Your Copyseeker API key. Create one under Account → Developers at copyseeker.net/account. A paid Copyseeker plan is required. | |
| COPYSEEKER_API_URL | No | Points the server at another API base URL. | https://api.copyseeker.net |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
Copyseeker tools work on one image each, given as a direct image URL (http/https) or the path to a local image file. Each call is charged to the user's Copyseeker credits: reverse_image_search 1 credit, detect_ai_image 0.01, detect_nsfw 0.01. Call a tool once per image and question; do not repeat a call that already succeeded.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| reverse_image_searchA | Find the web pages that show this image, with the copies of it each page uses, ranked by how prominent the page is. Use it to find where an image came from, who published it first, or where it is reused without permission. Costs 1 credit. |
| detect_ai_imageA | 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. |
| detect_nsfwA | Tell whether an image contains nudity or sexual content that is not safe for work. Costs 0.01 credits. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool targets a clearly different question about an image: provenance/reuse, AI generation, and NSFW content. There is no plausible scenario where an agent would confuse one for another, and the descriptions reinforce the boundaries.
All three names follow a predictable snake_case verb_noun pattern (reverse_image_search, detect_ai_image, detect_nsfw). The verb-first convention is uniform and readable.
Three tools is exactly right for a focused image-analysis API wrapper; each covers a distinct capability with no filler. Nothing feels padded or missing at the surface level.
The core image-intelligence operations are covered, but supporting operations implied by the credit-based pricing (e.g., checking credit balance, batch submission) are absent. Agents can still complete the primary workflows without them.