Azure AI Vision Face Liveness MCP Server

The Azure AI Vision Face MCP‑Server is a specialized tool that embeds face liveness verification into Agentic AI workflows. In many applications—such as secure logins, identity proofing, or compliance‑driven user onboarding—the system must confirm that a live human is presenting their face rather than a photo or replay. This server addresses that need by integrating Microsoft Azure’s Face Liveness API directly into the MCP ecosystem, allowing AI assistants to prompt users for a quick live‑capture and immediately receive a validated result without leaving the conversation.

At its core, the server exposes a single MCP tool that accepts an image or video stream and returns a structured response indicating whether the content is live, along with confidence scores. Developers can invoke this tool as a standard MCP call, enabling seamless branching in the assistant’s reasoning: if liveness is confirmed, proceed to the next step; otherwise, request a new capture or abort. The server also supports a “Tool with Progress” mode, consolidating the entire liveness‑check workflow into one step and eliminating the need for users to manually confirm completion—a feature that streamlines user experience in desktop clients.

Key capabilities include:

• Real‑time liveness assessment using Azure’s proven computer‑vision models.
• Optional verification mode, where a pre‑stored image is compared against the live capture to confirm identity.
• Session image persistence through configurable directories, allowing downstream processes (e.g., facial‑recognition matching) to access the captured media.
• Progress reporting for long‑running checks, giving agents feedback while the verification is underway.

Typical use cases span secure authentication portals, remote banking verifications, and any scenario where proving presence is critical. By exposing these functions via MCP, developers can weave liveness checks into complex AI workflows—such as a multi‑step onboarding assistant that first verifies identity before granting access to sensitive data. The server’s tight integration with Azure ensures scalability, compliance, and ease of maintenance, making it a robust choice for any team that needs to safeguard user interactions with AI.