Azure-Samples/azure-ai-vision-face-mcp-server
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Azure AI Vision Face MCP-Server is designed to integrate face liveness detection into AI workflows, ensuring proof of presence.
Azure AI Vision Face MCP-Server
Introducing a Face Liveness MCP Server to allow the embedding of proof of presence during Agentic AI workflows.
Preview of Single Tool with Progress
Here's a preview of the MCP server in liveness-server-typescript-tool-with-progress folder, using the “Tool with Progress” feature to consolidate the liveness-check workflow into a single step, removing the need for users to type “Done.” Support for this feature in Claude Desktop is not yet available.
Face Liveness Detection
For more information, visit Face Liveness Detection
Running MCP Server
add dependency
go to liveness-server-typescript folder, run
$ npm install --save-dev typescript @types/node
$ npm install
$ npm run build
then in the build folder, you have index.js
sample for vs code
add .vscode/mcp.json
{
"servers": {
"liveness-server": {
"type": "stdio",
"command": "node",
"args": [
"${workspaceFolder}/liveness-server-typescript/build/stdio.js"
],
"env": {
"FACEAPI_ENDPOINT": "apiendpoint",
"FACEAPI_KEY": "apikey",
"FACEAPI_WEBSITE": "https://liveness-webapp.azurewebsites.net",
"SESSION_IMAGE_DIR": "${workspaceFolder}/liveness-server-typescript/build/"
}
}
}
}
Sample Claude config should be:
{
"mcpServers": {
"liveness-server": {
"command": "node",
"args": ["YOUR_PATH/build/stdio.js"],
"env": {
"FACEAPI_ENDPOINT": "apiendpoint",
"FACEAPI_KEY": "apikey",
"FACEAPI_WEBSITE": "https://yourexample.azurewebsites.net",
"SESSION_IMAGE_DIR": "D:\somePATH"
}
}
}
}
Localation of session image
If you don't set the variable for SESSION_IMAGE_DIR, images will not be saved.
Liveness with verify
When you have a verify image set, it will switch liveness with verify mode. sample:
"VERIFY_IMAGE_FILE_NAME": "${workspaceFolder}/liveness-server-typescript/build/0b5db043-951c-49d4-9109-e11cb558bb79/sessionImage.jpg",
