VerifEye

ai.realeyesPublished by realeyes.aiOfficial publisherv1.1.1Updated Oct 24, 2026

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

VerifiedStreamable HTTPWeb executableSecurity & Monitoring AI & ML

Server details

Identifier: ai.realeyes/verifeye
Transport: Streamable HTTP
Runtime: Web executable
Trust: Verified
Published: Oct 11, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

The registry verified that this server's namespace belongs to realeyes.ai, which also runs its endpoint. That identifies the publisher; it does not make the server's tools safe.

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Overview

AI-generated overview

Remote Realeyes VerifEye server that lets an assistant analyze faces for apparent age, gender, emotions and attention, and onboard, compare and manage face…

What you can do: Analyze faces in an image for apparent age, gender, momentary emotions and attention, optionally identifying against a collection
Onboard faces into a collection and compare a new image against one onboarded face
List, create, describe, reset and delete collections
Find onboarded faces by your own key, attach or remove that key, and delete a face
Get a short-lived upload URL for submitting an image
When to use it: Useful when you want an assistant to run face analysis or face matching through the VerifEye Face API without writing integration code, for example estimating audience attributes from photos or checking whether a visitor is already enrolled in a collection.
Requirements: A remote endpoint at the documented VerifEye server URL over Streamable HTTP; no local install. A VerifEye Developer Console account and an MCP client that supports remote servers with OAuth 2.1 (authorization code with PKCE); some clients need a pre-registered client ID. Images must be given as public JPEG or PNG links, or uploaded via the upload URL tool. Each call runs in the EU unless the US region is requested.

Before you install

Processes facial biometric data: you are responsible for informed consent and for privacy and biometric-data rules such as GDPR, BIPA and CCPA. Onboarding stores a persistent face template; deleting a face, resetting or deleting a collection is irreversible. Age and gender are estimates, and a match is similarity evidence, not an identity check. Images are fetched by VerifEye from a link you provide, so prefer short-lived pre-signed links. Calls run as your account and count against its usage…

Installation

In SourceWeft

Open VerifEye in the dashboard and add it to a workspace.
Connect the required credentials. They are stored privately and never shown on public pages.
Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.realeyes%2Fverifeye/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

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

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

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:

json

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

{  "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.

Tools

This server asks you to sign in, so SourceWeft could not read its tools without an account and has not indexed them. What a connected account sees can depend on that account and its permissions.

Version history

v1.1.1LatestOct 16, 2026
v1.1.0Oct 11, 2026

Score

75% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

Reached in the last 30 daysRequired25 pts
Auth declaredRequired10 pts
Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
DescriptionRequired15 pts
Logo10 pts
Documentation15 pts
License10 pts
Declare a license in the repository or the registry entry.

VerifEye

Overview

Installation

In SourceWeft

Use with an agent

Other MCP clients

README

VerifEye MCP Server

Server URL

Requirements

Authentication

Connecting a client

Using the server

Example prompts

Tools

Biometric data and consent

Links

Tools

Version history

Score