Snitchmd – Cloudflare-protected URLs into clean Markdown via Docker

Hacker News

Shmauthor here. Built this for myself, putting it out in case it's useful. Needed any URL as clean Markdown for LLM context — including Cloudflare/anti-bot sites. curl gets HTTP 403 on those, raw HTML is 80%+ nav noise eating context, paid SaaS (Firecrawl, Jina) wasn't an option for me. It's a Docker wrapper around two existing OSS tools — CloakBrowser (stealth Chromium that passes Cloudflare) and rs-trafilatura (HTML → Markdown). No new scraper, just glue. Runs locally, my URLs stay on my box Token reduction (raw curl HTML vs snitchmd, tiktoken cl100k_base): - cloudflare.com/learning/bots — curl: HTTP 403 → snitchmd: 0.8k - docs.docker.com/engine/install — 187k → 0.9k - en.wikipedia.org/wiki/LLM — 222.7k → 29.7k Heads up: passes Cloudflare, can't solve "click traffic lights" captchas (reCAPTCHA v2, hCaptcha) MIT. Happy to answer questions

Visit product View on Hacker NewsApr 29, 2026

Share card

Actual performance

8points

1comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: dock, new, context · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

42%42% 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

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

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

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

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

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

Correct prediction on native model

Similar products

Bridgeflare – Replace Docker with Cloudflare48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bridgeflare – Replace Docker with Cloudflare

Hacker News1

MarkyDown – get clean Markdown from URL or HTML59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

MarkyDown – get clean Markdown from URL or HTML

Hacker News6

Django on Docker45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Django on Docker

Hacker News3

Docker NGINX container68%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Docker NGINX container

Hacker News1

Apache Beam with Docker42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Apache Beam with Docker

Hacker News2

Apache Beam with Docker42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Apache Beam with Docker

Hacker News1

Softcover gem Docker container38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Softcover gem Docker container

Hacker News1

Docker: Taming the Beast (Part I)48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Docker: Taming the Beast (Part I)

Hacker News4

Rubymine docker48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Rubymine docker

Hacker News1

Docker Conductor48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Docker Conductor

Hacker News1

Browse all products Analyze your launch