Md

Mdpreview – Markdown in the terminal (images, diagrams, big headings)

Hacker News

Mdpreview – Markdown in the terminal (images, diagrams, big headings)

Well, everyday I spend more and more time fully inside the terminal and I noticed the time I spend reading markdown now greatly overshadows the time I spend actually writing it, so this helps render markdown nicely. Mermaid diagrams to an extent look good and somewhat understandable without launching any other app. I tried glow and it felt like end of the day I was still looking at markdown like # titles or *effects* didn't hit the same. Inline images and mermaid diagrams are actually what I wanted the most. Zero dependencies typescript. Gets the job done.

Visit product View on Hacker NewsAug 26, 2026

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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