The Azure AI Vision Face Detection and Recognition MCP Server, bringing the power of Face API to your agents.
{
"mcpServers": {
"azure-ai-vision-face-api-mcp-server": {
"command": "<see-readme>",
"args": []
}
}
}No install config available. Check the server's README for setup instructions.
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The Azure AI Vision Face Detection and Recognition MCP Server, bringing the power of Face API to your agents.
Is it safe?
No package registry to scan.
No authentication — any process on your machine can connect.
MIT. View license →
Is it maintained?
Last commit 47 days ago. 9 stars.
Will it work with my client?
Transport: stdio. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.
No automated test available for this server. Check the GitHub README for setup instructions.
No known vulnerabilities.
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Introducing a Face Detection and Recognition MCP Server to allow the embedding of face attribute detection and face recognition during Agentic AI workflows.
https://github.com/user-attachments/assets/dac4ef24-2043-47a2-8858-c965970254f9
For more information, visit Face API
Refer to the Installation Guide for instructions on installing uv.
We provide several example images in the example folder. Please clone this project to try the example prompts below.
git clone https://github.com/Azure-Samples/azure-ai-vision-face-api-mcp-server.git
Azure AI Face API Endpoint: The endpoint URL of your Azure Face API deployment.Azure AI Face API Key: The API key for your Azure Face API resource.Azure OpenAI Endpoint: The endpoint URL of your Azure OpenAI deployment.Azure OpenAI API Key: The API key for your Azure OpenAI resource.AZURE STORAGE ACCOUNT: The name of your Azure Storage account.AZURE STORAGE CONTAINER: The name of your image container.AZURE STORAGE SAS TOKEN: The SAS token for your storage container..vscode/mcp-bp.json to .vscode/mcp.json (or copy .vscode/mcp-bp.json to your existing .vscode/mcp.json) and press Start above the azure_ai_vision_face_api_mcp_server in .vscode/mcp.json..env.example to .env