MarkFlowy – A Markdown editor, which is lighter, smarter and purer

Hacker News

Why develop it? First of all, I don't like the idea of all in one. In particular, I almost only need words. I have used Typora. It is really good, but it can hardly satisfy me except editing. So I wonder if there is a simple Markdown editor that can manage files and has a good editing experience? Then there is MarkFlowy. Features: MarkFlowy has been independently developed for 2.5 years.Based on the design philosophy of being lightweight, simple, and highly available, it now boasts a considerable number of functions such as: - Local Priority : MarkFlowy is a pure editor designed to edit your local content. The synchronization method is left to the user's choice. Currently, it provides a Git manager and will later integrate with other similar cloud storage services for synchronization. Feel free to provide feedback on this. - User Experience First : It offers multiple editing modes, including source code and WYSIWYG (What You See Is What You Get). Additionally, it supports custom themes. Furthermore, high performance is the foundation of a good user experience. MarkFlowy has a lightweight package size and specialized performance optimization. Real-world testing shows that on an M1 Mac device, editing documents with over 200,000 characters can still ensure smooth writing in both Chinese and English. - AI Support : MarkFlowy integrates with multiple AI vendors such as Deepseek, Openai, and Ollama. It also supports using their features within the editor for tasks like Q&A, summarization, translation, etc., to enhance your writing efficiency. - Simplicity : Out-of-the-box usability. You only need to familiarize yourself with Markdown syntax to use it easily. It also provides synchronization methods such as Git and a powerful file management tree. Apart from these features, MarkFlowy can edit text files (txt), JSON files, and view image files, among other useful functions. We welcome everyone to experience, exchange ideas, and participate.

Visit product View on Hacker NewsAug 28, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, including · Missing: reddit linkedin, podcasting, created

95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, openai · Missing: agents, macos, agent

89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: llama, ide, 000 · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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