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PopNx MCPMCP servers for people who use AI · explained in plain words

Lens

by Mindola-aiversion 1.0.2i★ –iRuns in the cloud
Registry nameai.mindola/lens

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • The registry lists no key to fill in.

You need

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Works in Claude on the web, desktop and mobile:

  1. Open Settings → Connectors
  2. Press Add custom connector
  3. Paste the address below and press Add
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Add2https://…3
https://app.mindola.ai/mcp/lens

Run this in your terminal

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

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

ChatGPT connects only to servers on the internet:

  1. Open ChatGPT on the web → Settings → Connectors (Apps)
  2. Press Create or Add (some plans need Developer mode under Advanced first)
  3. Paste the address below, give it a name and save
  4. If it asks you to sign in, sign in with the maker
SettingsConnectors1+ Create2https://…3
https://app.mindola.ai/mcp/lens

Menu names can differ slightly by plan and over time.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified against the domain mindola.ai (the registry checks domain ownership)

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • … Not checked yet

    Endpoint responds

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    Sign-in with OAuth

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Otheri

  • More stars than 0% of the other 32696 servers in this category
  • Published to the registry more recently than 21% of the other 32696 servers in this category
  • Basic checks equal to or better than 100% of the other 32696 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Lens safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.0.2) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, LexPact UK Contracts

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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

Runs in the cloud★ 211Updated 2 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

Only the beginning is shown; read the rest in the repo

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