reprise
Un-flatten any flat AI design into editable layers, reproduce it bit-perfect, from your agent.
Should I use this
Quality & Safety
Findings (2)
- LOWin reproduce
- LOWin diagnose
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"reprise": {
"url": "https://tepesama-reprise-mcp.hf.space/gradio_api/mcp/http"
}
}
}Remote endpoints
https://tepesama-reprise-mcp.hf.space/gradio_api/mcp/httpstreamable-httpWhat it can do
Tool inventory
Tools (3)
⚪reproduce(image)
Un-flatten a flat design image into editable layers and reproduce it bit-perfect, returning the fidelity score. Returns: A JSON string with a bit_perfect flag and fidelity metrics (mae, psnr, exact-match %, stray px).
Input Schema
{
"type": "object",
"properties": {
"image": {
"type": "string",
"description": "The source design image as an http(s) URL or a base64 data URL."
}
}
}⚪autodetect(image)
Auto-detect the elements (subjects and text) in a design image as relative bounding boxes. Returns: A JSON string with the detected elements (relative bboxes) and their count.
Input Schema
{
"type": "object",
"properties": {
"image": {
"type": "string",
"description": "The design image as an http(s) URL or a base64 data URL."
}
}
}⚪diagnose(original, reproduction)
Score how faithfully a reproduction matches an original (MAE / PSNR / exact-match % / stray px). Returns: A JSON string with the fidelity metrics.
Input Schema
{
"type": "object",
"properties": {
"original": {
"type": "string",
"description": "The original image as an http(s) URL or a base64 data URL."
},
"reproduction": {
"type": "string",
"description": "The reproduced image to compare, as an http(s) URL or a base64 data URL."
}
}
}Community
Evidence