Is VerifEye Face free?

Yes, VerifEye Face is free to use.

How do I install VerifEye Face?

VerifEye Face is a remote plugin. You do not need to install anything locally. Add the server URL to your AI app's MCP configuration and you are ready to go.

Is VerifEye Face safe to use?

Yes. VerifEye Face passed MCP Marketplace's automated security scan with a score of 10/10 (low risk). Every server on MCP Marketplace is security-scanned before it's listed; see the full security report on this page for the findings and permissions.

What AI apps work with VerifEye Face?

VerifEye Face uses the Model Context Protocol (MCP) and works with any MCP-compatible AI app, including Claude, ChatGPT / Codex, Gemini, Copilot, Cursor, and more.

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VerifEye Face MCP Server

by Realeyes

Developer ToolsLow Risk10.0MCP RegistryRemote

Free

Server data from the Official MCP Registry

VerifEye Face API: Identify (apparent age, gender, emotions, attention), Onboard and Compare faces.

About

VerifEye Face API: Identify (apparent age, gender, emotions, attention), Onboard and Compare faces.

Remote endpoints: streamable-http: https://verifeye-mcp-server.realeyes.ai/mcp

Security Report

10.0

Low Risk10.0Low Risk

Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.

Endpoint verified · Requires authentication · 1 issue found

Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.

Permissions Found in Source Code

Found by scanning the linked source code. This listing connects to a hosted endpoint, so none of this runs on your machine: it describes what the server software does where it is hosted.

HTTP Network Access

Connects to external APIs or services over the internet.

How to Connect

Remote Plugin

No local installation needed. Your AI client connects to the remote endpoint directly.

Add this to your MCP configuration to connect:

{
  "mcpServers": {
    "ai-realeyes-verifeye": {
      "url": "https://verifeye-mcp-server.realeyes.ai/mcp"
    }
  }
}

Documentation

View on GitHub

From the project's GitHub README.

VerifEye MCP Server

The VerifEye MCP Server is a remotely hosted Model Context Protocol (MCP) server from Realeyes. It exposes the VerifEye Face API as tools an AI assistant can call: analyze a face for apparent age and gender plus momentary emotions and attention (Identify), onboard a face so the same person is identified later (Onboard), compare an image against one onboarded face (Compare), and manage the collections onboarded faces live in.

The server is hosted by Realeyes, so there is nothing to install or run. This repository holds its public listing metadata for MCP registries: server.json.

Full documentation: https://verifeye-docs.realeyes.ai/verifeye-apis/mcp-server/

Server URL

https://verifeye-mcp-server.realeyes.ai/mcp

Transport: Streamable HTTP. This is the server's only address. If a registry or directory lists a different one, do not connect to it, and contact us.

Requirements

A VerifEye Developer Console account.
An MCP client that supports remote MCP servers with OAuth.

Authentication

The server uses OAuth 2.1 (authorization code with PKCE). When you connect, a VerifEye sign-in and consent screen opens in your browser. You never put an API key into your MCP client: your account's API key is resolved on the server side and is never exposed to the client.

The server offers no dynamic client registration. ChatGPT, VS Code and Codex identify themselves with a Client ID Metadata Document, so there is nothing to enter. Claude, Claude Code, Cursor and the Gemini CLI use a pre-registered client ID.

Connecting a client

Step-by-step setup for Claude Code, Claude, ChatGPT, VS Code, Cursor, the Gemini CLI and Codex, including the client ID each one needs, is in the documentation: Connecting a client.

For example, in VS Code add .vscode/mcp.json to your project root:

{
  "servers": {
    "verifeye": { "type": "http", "url": "https://verifeye-mcp-server.realeyes.ai/mcp" }
  }
}

Start the server from the MCP: List Servers command, then sign in when the browser opens.

Using the server

Once the server is connected and you have signed in, ask in plain language and the assistant picks the tools.

Give the image as a link. The image tools take a public URL of a JPEG or PNG image, which VerifEye fetches itself. An image attached to the conversation cannot be passed to a tool, so put the image somewhere reachable and give the assistant that link. Prefer a pre-signed link that expires in minutes to a durably public URL. Where the server offers verifeye_get_upload_url and your client can make HTTPS requests of its own, the client can upload the image instead. Image requirements: documentation.

Choose the region. Every call runs in the EU (eu) unless you ask for the US (us). Collections are per region, so ask for the same region each time you work with a collection.

Example prompts

The image links are placeholders: use a link to your own image. Prompts 2 to 5 build on each other and use the collection and the face that prompt 2 creates.

#	Prompt	What happens
1	"Estimate the apparent age and gender of the face in https://example.com/photos/visitor.jpg."	`verifeye_identify_face` analyzes the face and returns the estimates. No face or image is stored.
2	"Create a VerifEye collection called front-desk-visitors, then onboard the face in https://example.com/photos/visitor-1042.jpg into it with the external key visitor-1042."	`verifeye_create_collection` creates the collection, and `verifeye_onboard_face` stores the face template with that key. Onboarding stores biometric data: see Biometric data and consent.
3	"Is the person in https://example.com/photos/today.jpg already in my front-desk-visitors collection?"	`verifeye_identify_face` with that collection answers `Existing`, with the `faceId` and the key, when the photo shows the person onboarded in prompt 2, and `NotExisting` for anyone else. Nothing is onboarded.
4	"Compare the face in https://example.com/photos/check-in.jpg with visitor-1042 in front-desk-visitors."	`verifeye_get_face_by_key` finds the `faceId`, and `verifeye_compare_face` returns the similarity and VerifEye's `isMatch` verdict.
5	"Delete visitor-1042's face from front-desk-visitors."	`verifeye_get_face_by_key` finds the face, and `verifeye_delete_face` destroys its template. This cannot be undone.

Many clients ask you to approve a call before it runs, for example before a face is onboarded or deleted.

Tools

Every tool takes region (eu or us, eu by default), which selects where the image is processed and where a collection lives. Collections are per region: one created in eu is not visible from us.

Tool	What it does	Stores or destroys data
`verifeye_identify_face`	Analyzes the face(s) in an image, and identifies them against a collection if you name one	No
`verifeye_onboard_face`	Onboards the face(s) in an image into a collection so the person is identified later	Stores a face template
`verifeye_compare_face`	Compares the face(s) in an image against one onboarded face	No
`verifeye_delete_face`	Deletes one onboarded face	Irreversible
`verifeye_list_collections`	Lists the collections on the account, or checks whether one exists	No
`verifeye_create_collection`	Creates an empty collection	No
`verifeye_set_collection_description`	Replaces a collection's description	No
`verifeye_reset_collection`	Deletes every face in a collection, keeping the collection	Irreversible
`verifeye_delete_collection`	Deletes a collection and every face in it	Irreversible
`verifeye_get_face_by_key`	Finds an onboarded face by your own identifier	No
`verifeye_set_face_key`	Attaches your own identifier to an onboarded face	No
`verifeye_delete_face_key`	Removes your identifier from an onboarded face	Loses the way of finding the face
`verifeye_get_upload_url`	Hands back a short-lived form for uploading one image	No

Parameters, results and error codes for each tool are in the documentation.

Biometric data and consent

These tools process facial (biometric) data. You are responsible for obtaining valid, informed consent before a call runs, and for meeting the privacy and biometric-data regulations that apply to the people in your images (for example GDPR, BIPA and CCPA).

verifeye_onboard_face stores a face template that persists until it is deleted.
verifeye_delete_face, verifeye_reset_collection and verifeye_delete_collection destroy face templates permanently.
Age is an apparent-age estimate, not a legal proof of age. Gender is a demographic estimate, not a self-declared identity attribute. A face match is evidence of similarity, not an identity check on its own.
Tool calls run as your VerifEye account and count against your account's usage limits.

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VerifEye Face MCP Server

About

Security Report

Findings (1)

Permissions Found in Source Code

How to Connect

Documentation

VerifEye MCP Server

Server URL

Requirements

Authentication

Connecting a client

Using the server

Example prompts

Tools

Biometric data and consent

Links

Reviews

No reviews yet

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Rea

Paperclip

Git

Toleno

MCP Marketplace

mcp-creator-python