原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Lens

作者:Mindola-ai版本 1.0.2i★ –i在云端运行
注册名称ai.mindola/lens

安装

概览

作者提供的说明(英文原文)

Create your digital twin: a public page that answers from your own material, with citations.

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。

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。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

你需要

你用的是哪个应用?

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:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://app.mindola.ai/mcp/lens

在终端中运行这条命令

claude mcp add --transport http lens https://app.mindola.ai/mcp/lens

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": {
    "lens": {
      "url": "https://app.mindola.ai/mcp/lens"
    }
  }
}

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": {
    "lens": {
      "type": "http",
      "url": "https://app.mindola.ai/mcp/lens"
    }
  }
}

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:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://app.mindola.ai/mcp/lens

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

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

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7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 mindola.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

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 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 32700 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32700 个服务器的 21% 更新
  • 基础检查结果等于或优于此分类中其他 32700 个服务器的 100%

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

Lens 安全吗?

它在 1 项适用的基础检查中通过了 1 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(1.0.2)于3个月前进入注册中心。

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, Agent Data Tools: Utilities

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:★ 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

作者:formulahendry

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

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

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

在云端运行★ 211前天更新
安装

Agent Data Tools: Utilities

作者:Nutshell2000

103 tools: JSON repair, CSV, hashes, cron, dates, units, validators. 25 free calls.

在云端运行今天更新
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。

Mindola MCP server

Mindola turns a person's own material (writing, notes, documents, links) into a public AI page that answers questions from that material alone, with citations.

That public AI page is called a lens: one shareable link, like https://mindola.ai/me/your-name, where anyone can ask questions in chat or a live voice call. Every answer is grounded only in the owner's material and shows its sources. If the material does not cover a question, the lens says so honestly instead of guessing, and can hand the question to the real person.

This repository is the public documentation and examples for Mindola's hosted MCP server. The server is remote: there is nothing to install or run. You add one URL to your MCP client (Claude, Cursor, VS Code, Codex, ChatGPT), and your AI assistant can create and fill a lens for you in one conversation. The server itself runs inside the Mindola app, which is closed source; this repo holds the docs and example code.

Try a live lens right now, no account needed: mindola.ai/me/charles-darwin.

What problem Mindola solves

People publish knowledge that nobody reads. Your blog posts, documentation, course material, and notes sit in archives, and visitors are expected to dig through them. Most will not. They have one question and they want one answer.

A generic AI chatbot is not the fix. It answers from whatever it was trained on, so it confidently makes things up about you, your product, or your work. That is worse than no answer.

Mindola sits in between. It gives your material a front door: a page that answers questions from your knowledge base and nothing else, cites where each answer came from, and admits when it does not know. Visitors get answers instead of archives, and you get to see what they asked.

Why Mindola instead of building RAG yourself

Building retrieval-augmented generation (RAG) yourself is a real project. You need ingestion for every source type, chunking that respects document structure, embeddings, a vector store, retrieval tuning, grounding logic so the model stays inside your material, a citation UI, refusal behavior for out-of-scope questions, and then hosting, monitoring, and a front end. Add real-time voice and it roughly doubles.

Mindola gives you the finished product behind one link and one API. You provide the material; Mindola handles knowledge retrieval, grounded answers, citations, refusals, voice, the public page, and the inbox for unanswered questions. You can go from nothing to a working grounded AI page in one conversation with your coding assistant.

Building your own is still the right call in some situations. If you need full control over which models run, where your data lives, or how retrieval is ranked, or you want to embed the pipeline deep inside an existing product, roll your own. Mindola is for everyone who wants the outcome without owning the pipeline.

Core capabilities

  • Grounded answers with citations. Every answer comes from the owner's material only, and shows its sources. Private material never leaks into citations.
  • Honest refusals. Out-of-scope questions get a clear "I don't know" instead of a hallucinated answer.
  • Live voice calls. Visitors can talk to a lens in real time, with barge-in (they can interrupt mid-sentence). Owners can use a cloned voice or a stock voice.
  • Lead capture built in. Questions the lens cannot answer land in the owner's inbox with the visitor attached, so a lens doubles as light CRM.
  • Optional payments. Owners can charge visitors through Stripe Connect, using their own Stripe account with per-lens pricing. Off by default.
  • 10 app languages. The app UI supports English, Dutch, German, Spanish, French, Arabic, Japanese, Korean, Turkish, and Chinese.
  • Many uses from one link. The same lens can answer for your website, your docs, or your coaching practice, depending on what you feed it.

Installation

The MCP server is hosted. There is nothing to run locally; you point your client at a URL.

Claude Code

claude mcp add --transport http mindola https://app.mindola.ai/mcp/lens

Cursor (~/.cursor/mcp.json or project .cursor/mcp.json)

{

"mcpServers": { "mindola": { "url": "https://app.mindola.ai/mcp/lens" } } }

Claude Desktop / claude.ai

Settings -> Connectors -> Add custom connector -> URL https://app.mindola.ai/mcp/lens.

For VS Code, Codex CLI, Windsurf, Gemini CLI, ChatGPT, and troubleshooting, see docs/installation.md. Ready-to-copy client configs live in examples/clients/.

Quick start

With your AI assistant
  1. Connect the server using any snippet above.
  2. Paste a prompt like this:
Create a Mindola lens for me. I'm a nutrition coach specializing in

plant-based diets for endurance athletes. I've been coaching for 8 years. Use a warm tone. Ask me anything you need, then show me the profile before you create it.

  1. Your assistant drafts a profile (name, bio, expertise, facts, boundaries) and shows it to you. The tool's instructions require your assistant to get your explicit confirmation before creating anything, and to use only information you provided or confirmed in the conversation.
  2. Confirm. The assistant calls create_digital_twin_lens and returns:
  • shareUrl: your public lens page, live immediately
  • claimUrl: open it and sign up (free) to make the lens yours
  • manageUrl, expiresAt, factCount, and suggestedPrompts

No account is needed to create. The lens starts out unclaimed: live at its share URL, expiring after 30 days if never claimed. While it is unclaimed, your assistant can keep adding knowledge to it with add_lens_knowledge. Once you claim it, changes go through the app or the authenticated developer API.

  1. Keep going in the same conversation. Ask your assistant to add your articles or pages:
Add my last three blog posts to the lens, then check the ingestion

status and tell me when everything is ready.

The assistant calls add_lens_knowledge with the URLs, then polls get_lens_status until the knowledge counts show everything as ready. Open the share URL and ask your lens a question.

With the REST API

Create an API key in the Mindola app, then create a lens seeded with knowledge in one call:

curl -s https://app.mindola.ai/api/v1/lenses \

-H "Authorization: Bearer mnd_your_api_key_here" \ -H "Content-Type: application/json" \ -d '{ "name": "Product docs assistant", "greeting": "Hi, ask me anything about the product.", "knowledge": [ { "type": "url", "content": "https://example.com/docs/getting-started", "title": "Getting started" }, { "type": "text", "content": "Refunds are available within 30 days of purchase.", "title": "Refund policy" } ] }'

The response is 201 with { id, token, shareUrl, sourcesQueued }. Ingestion runs in the background; poll GET /api/v1/lenses/:id until the knowledge counts show ready. Full reference in docs/api.md.

20 real-world use cases

  1. Coach: an ask-me-anything page that answers from your method and captures leads when a question needs the real you.
  2. Open source maintainer: developer documentation that answers questions with citations instead of making readers search.
  3. Course creator: a course assistant students can ask at 2 a.m., grounded in the syllabus and lessons.
  4. Indie founder: a customer support AI for a small product, answering from your docs and changelog.
  5. Job seeker: a CV that answers recruiters' questions about your experience, in chat or voice.
  6. Small team: internal documentation behind one link that the whole team can ask.
  7. Podcaster: a persona built from episode notes and transcripts that listeners can question between episodes.
  8. Newsletter writer: an archive readers can query instead of scrolling through years of issues.
  9. Conference speaker: a page attendees can keep asking after the talk ends, seeded with your slides and notes.
  10. Consultant: an AI expert page that qualifies inbound leads before the first call.
  11. Author: a book companion that discusses your ideas and cites the chapters they come from.
  12. Agency: a services page that pre-answers scope, process, and pricing questions from your own material.
  13. Teacher: a study helper grounded in class materials, so answers match what was actually taught.
  14. Researcher: a page that answers questions about your papers and points to the exact source.
  15. Product manager: a release-notes lens, so "did you ship X yet" answers itself.
  16. Local business: a lens on your site that answers hours, services, and policy questions from your own pages.
  17. HR team: an onboarding assistant that answers from the employee handbook instead of a shared drive.
  18. Fitness trainer: paid Q&A through Stripe, where visitors pay to ask your lens directly.
  19. Community manager: a rules and guidelines bot that answers moderation questions consistently.
  20. Historical educator: a public-domain figure brought to life, like the Charles Darwin demo.

Ten of these are written out end to end in examples/use-cases/, each with a prompt to paste, the conversation to expect, and the final result.

Example prompts

Paste any of these into Claude, Codex, Cursor, or ChatGPT once the server is connected.

Create a Mindola lens for me. I'm a freelance UX designer with 10 years

of experience in fintech and healthcare. Interview me briefly to fill the gaps, show me the profile, and only create it after I approve.

Read the README and docs folder of this repository, then create a

Mindola lens that answers questions about the project's docs. Show me the proposed profile before creating anything.

Turn my CV into a Mindola lens that answers recruiters' questions.

Here is my CV: [paste CV]. Keep the tone professional and add a boundary that it never discusses salary expectations.

Create a Mindola lens for my online course "Intro to Data Analysis".

It should act as a course assistant for students. I'll paste the syllabus and lesson summaries next.

Add these three articles to my Mindola lens YOUR_LENS_TOKEN:

https://example.com/post-1 https://example.com/post-2 https://example.com/post-3

Check the status of my Mindola lens YOUR_LENS_TOKEN. Tell me how many

knowledge sources are ready, pending, or failed.

Create a Mindola lens for our startup's support. Use our FAQ page at

https://example.com/faq and the refund policy I paste below. Tone: professional. Add suggested prompts about setup, billing, and refunds.

Create a Mindola lens in Dutch (locale nl) for my bakery. It should

answer questions about opening hours, allergens, and custom orders from the text I provide.

One hundred more, organized by role and goal, in docs/prompts.md. For an industry-first view, examples/100-prompts.md holds 100 one-sentence prompts grouped by field, from customer support to online courses.

API overview

The REST developer API v1 lives at https://app.mindola.ai and authenticates with Authorization: Bearer mnd_ . Write endpoints are limited to 30 requests per minute per key.

EndpointWhat it does
POST /api/v1/lensesCreate a lens, optionally seeding up to 50 text or url knowledge items
GET /api/v1/lensesList your lenses, up to 100, newest first
GET /api/v1/lenses/:idGet one lens with its knowledge counts (total, ready, pending, failed)

| POST /api/v1/lenses/:id/knowledge | Add up to 50 more knowledg

只显示了开头部分;其余内容请在仓库中阅读

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