Hey Product Hunt 👋
I built tweet.md because I kept running into the same annoying problem: X posts are often useful context for AI tools, but copying them usually gives you messy text, embeds, screenshots, or browser clutter.
tweet.md turns X posts and threads into clean, attribution-preserving Markdown.
The workflow is as simple as rewriting the URL to tweet.md:
x.com/ProductHunt/status/2057518338419634198
→ tweet.md/ProductHunt/status/2057518338419634198
There’s also an AI agent skill, so agents can use tweet.md directly in their workflows.
It supports:
* single X posts
* threads
* quoted posts
* articles
* Obsidian-friendly Markdown
The goal is simple: make public X content easier to use with ChatGPT, Claude, Cursor, Codex, Obsidian, and other Markdown/LLM workflows — without scraping HTML or pasting messy copied content.
Would love your feedback, especially from people using X content in research, AI workflows, or note-taking.
This is exactly the kind of tiny utility that becomes more valuable because agents can use it reliably.
One thing I’d want in the Markdown output is a small provenance block: original URL, canonical URL, author handle, fetched-at time, and whether the post/thread was complete at fetch time. For research and AI workflows, that helps distinguish “this is what the post said when I captured it” from “this is the live state of X right now.”
If you ever add LinkedIn or other sources, that same receipt would matter even more because public posts move, disappear, or get reformatted in ways that can quietly change downstream summaries.
this is one of those tools that solves a problem you didn't realise you had until you see it. I copy tweets into docs all the time and the formatting is always a mess. the agent skill is a nice touch too
Concrats Lars! Not sure how often I need it but I can imagine it can be super helpful. Also I like the domain!
The URL-swap trick (x.com to tweet.md) is clever and the decision to output deterministic Markdown with thread structure, quotes, and canonical links intact is what makes this actually useful in LLM pipelines. We've scraped social content before and the noise from raw HTML always breaks downstream parsing. How do you handle X's rate limiting on the API side? Do you cache resolved posts?
Also, any ambition to do this for LinkedIn? I am there recently and it is also a big market to cover :)
Congrats on your launch! very interesting, have myself faced this issue. Does it need X APIs too?
Long threads with images sometimes break copy-paste. Does tweet.md keep image URLs in the Markdown or text-only?
Finally a simple way to turn good X threads into something actually reusable ❤️
About tweet.md on Product Hunt
“X posts as clean Markdown”
tweet.md launched on Product Hunt on May 25th, 2026 and earned 200 upvotes and 36 comments, placing #5 on the daily leaderboard. Get any X post or thread as clean Markdown for LLMs, agents, and research. Swap x.com for tweet.md or use the API.
tweet.md was featured in API (98.2k followers), Social Media (89k followers) and Artificial Intelligence (469.3k followers) on Product Hunt. Together, these topics include over 126.6k products, making this a competitive space to launch in.
Who hunted tweet.md?
tweet.md was hunted by Lars. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how tweet.md stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Lars