---
title: "Frequently Asked Questions"
url: https://mdfy.app/SfYEsN5E
updated: 2026-05-09T16:24:56.831Z
source: "mdfy.app"
---
# Frequently Asked Questions

## What is mdfy and what problem does it solve?

mdfy is a "Markdown Hub" designed to help users own their AI memory by providing a permanent, portable layer for curated knowledge. It allows users to collect information from various sources, edit it using AI-powered tools, and publish it to permanent URLs [doc-4, doc-7]. Unlike tools that focus on automated AI extraction, mdfy emphasizes "Human-in-the-Loop" curation, betting that quality memory requires intentional authorship rather than just automated logs [Bundle Signals, doc-4].

## How do I capture and save information from AI chat platforms?

The most efficient way to capture content is via the mdfy Chrome Extension. When installed, a floating mdfy button appears in the bottom-right corner of ChatGPT, Claude, and Gemini conversations. Clicking this button captures the entire conversation, formats it with User/Assistant roles, and generates a shareable URL [doc-3]. Users can also capture generic web pages or specific text selections directly from the browser toolbar [doc-3].

## What editing and AI-assisted tools are available?

mdfy provides a "Live" WYSIWYG editing mode where users can click any text in the rendered view to edit it directly [doc-7]. It also offers "Split" and "Source" modes for those who prefer working with raw Markdown [doc-6]. Integrated AI tools include:
*   **Polish:** Improves writing quality.
*   **Summarize/TL;DR:** Generates quick overviews.
*   **Translate:** Converts text to different languages.
*   **Ask AI:** Allows users to describe specific edits in natural language [doc-6, doc-7].

## What platforms and integrations does mdfy support?

mdfy is designed for "multi-surface" use across several environments:
*   **Web:** A browser-based hub at mdfy.app [doc-7].
*   **Mac:** A native app with a sidebar for managing local and cloud files [doc-6].
*   **Chrome Extension:** For capturing AI chats and web content [doc-3].
*   **VS Code:** An extension providing previews via Cmd+Shift+M [doc-7].
*   **CLI:** A command-line tool (`mdfy-cli`) for piping data to a URL [doc-7].
*   **MCP:** A Model Context Protocol bridge that allows different AI ecosystems (like Claude and ChatGPT) to read and update the same documents [doc-1, Bundle Signals].

## How does mdfy differ from other AI memory tools like Mem0 or Letta?

While competitors like Mem0 and Letta focus on automated extraction for conversation memory, mdfy is positioned for **curated knowledge**. It follows the "Author-first" principle, treating the document as a primitive unit that a human intentionally selects and organizes, rather than an automated log of every interaction [doc-4].

## Can I manage the privacy of my documents?

Yes. Documents can be toggled between public and private states. For example, using the toolset, a user can call `mdfy_publish({published: false})` to turn a document into a private draft [doc-1]. Captures from the Chrome extension are also private by default [doc-3]. However, the documents do not provide specific technical details regarding the underlying security architecture or detailed permission models for shared vs. private files [Bundle Signals].

## How do I use mdfy to manage local files on macOS?

The mdfy Mac app includes a **QuickLook** extension. Once enabled in System Settings, users can press **Space** on any `.md` file in Finder to see a rendered preview featuring syntax highlighting, KaTeX math, and tables [doc-2]. Within the Mac app, users can drag and drop local files to edit them or use "Cloud Sync" to push local changes to mdfy.cc for access on other devices [doc-6].

## What are the costs or subscription models for mdfy?

The documents mention that mdfy is currently "free during beta" [doc-7] and follows a "Start free" philosophy where the basic experience is accessible to everyone [doc-5]. While there are references to a "Pro" transition for curation features and "Build" tiers for AI integration, the specific pricing details, subscription costs, or the sustainability model for the hosted MCP service are not explicitly stated in the provided documentation [doc-4,