VerifEye

Name: VerifEye
Author: Realeyes

作者：Realeyes版本 1.1.1i★ –i在云端运行

注册名称ai.realeyes/verifeye

安装

概览

作者提供的说明（英文原文）

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i3 项中通过 2 项依据公开信息检查；尚未扫描代码
使用情况i非常新★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在云端运行
传输方式: Streamable HTTP
分类: 其他

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：3 项中通过 2 项
在作者的服务器上运行：你向它提出的内容会经过他们的服务器。
注册中心没有列出需要填写的密钥。

你需要

在云端运行无需安装任何东西，通过互联网连接

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

适用于网页版、桌面版和手机版 Claude：

打开 Settings → Connectors
点击 Add custom connector
粘贴下面的地址，然后点击 Add
如果要求登录，请登录作者的服务

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

在终端中运行这条命令

claude mcp add --transport http verifeye https://verifeye-mcp-server.realeyes.ai/mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

ChatGPT 只能连接互联网上的服务器：

打开网页版 ChatGPT → Settings → Connectors (Apps)
点击 Create 或 Add（部分套餐需要先在 Advanced 中开启 Developer mode）
粘贴下面的地址，起个名字，然后保存
如果要求登录，请登录作者的服务

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

菜单名称可能因套餐和版本不同而略有差异。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

服务器要求先登录，才会列出它的工具。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日

✓ 通过
作者与仓库一致
注册名称已通过域名 realeyes.ai 验证（注册中心会核实域名所有权）
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
✓ 通过
端点有响应
在 403 毫秒内响应（HTTP 401）
! 注意
使用 OAuth 登录
需要你自己复制粘贴密钥或令牌
… 尚未检查
工具描述中没有隐藏指令
尚未检查；我们会在检查端点时读取工具列表

与“其他”中的其他服务器比较i

星标数多于此分类中其他 18695 个服务器的 0%
发布到注册中心的时间比此分类中其他 18695 个服务器的 65% 更新
基础检查结果等于或优于此分类中其他 18695 个服务器的 37%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

VerifEye 安全吗？

它在 3 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在作者的云端运行。通过互联网连接，无需安装，但你发送的内容会经过作者的服务器。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（1.1.1）于23天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接，所以接受远程 MCP 服务器的应用也可以使用，例如开启开发者模式的 ChatGPT。

有什么可以替代它？

同一分类中有：Spec Driven Development, Remote Desktop Commander, Bestax

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

作者：formulahendry起步阶段↓ 66/周★ 44014个月前更新

在你的电脑上运行

安装

Remote Desktop Commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

作者：desktop-commander正在增长★ 2114天前更新

在云端运行✓ desktopcommander.app

安装

Bestax

Props, examples, CSS variables and Agent Skills for bestax-bulma React components (Bulma v1)

作者：allxsmith正在增长↓ 2910/周今天更新

在你的电脑上运行

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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.