mcp-face-transform
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-face-transformCartoonize the face in this image"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Face Transform Server
A Model Context Protocol (MCP) server that exposes the AceDataCloud Face Transform API — face keypoint detection, beautification, age/gender transform, face swap, cartoonization, and liveness detection.
Status: All Face APIs are currently in Alpha. Interfaces may evolve.
Features
Keypoint detection — 90+ landmarks per face, multi-face supported
Beautification — smoothing, whitening, face slimming, eye enlarging
Age transform — age or de-age a portrait
Gender transform — swap perceived facial gender characteristics
Face swap — move a source face onto a target image (with optional async webhook)
Cartoonize — render a portrait in animated / cartoon style
Liveness detection — distinguish live captures from printed / screen photos
Related MCP server: MidjourneyMCP
Installation
pip install mcp-face-transformConfiguration
Set your AceDataCloud API token:
export ACEDATACLOUD_API_TOKEN=your_token_hereGet your token from https://platform.acedata.cloud.
Usage
stdio mode (default)
mcp-face-transformHTTP mode
mcp-face-transform --transport http --port 8000Tool Reference
Tool | Description |
| Detect 90+ keypoints per face (multi-face supported). |
| Smoothing, whitening, face slimming, and eye enlarging. |
| Age or de-age a portrait. |
| Swap perceived facial gender characteristics. |
| Move a source face onto a target image (with optional async webhook). |
| Render a portrait in cartoon / animated style. |
| Distinguish a live capture from a printed / screen photo. |
| Concise client-side tool usage reference. |
Example
"Detect all faces in https://example.com/group.jpg and return their keypoints."
→ face_detect_keypoints(image_url="https://example.com/group.jpg")
"Lighten and smooth my portrait."
→ face_beautify(image_url="https://example.com/me.jpg", smoothing=15, whitening=25)
"Replace the face in the scene with the headshot."
→ face_swap(
source_image_url="https://example.com/headshot.jpg",
target_image_url="https://example.com/scene.jpg",
)Configuration in Claude Desktop / Claude Code
{
"mcpServers": {
"face-transform": {
"command": "uvx",
"args": ["mcp-face-transform"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_api_token_here"
}
}
}
}Or use the hosted endpoint with bearer auth:
{
"mcpServers": {
"face-transform": {
"url": "https://face.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer your_api_token_here"
}
}
}
}Development
pip install -e ".[dev,test]"
pytest --cov=core --cov=tools
ruff check .License
MIT — see LICENSE.
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