malvads

malvads / mojo

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Non sucking cross-platform extremely fast C++ crawler to convert entire websites into LLM readable data

crawler llm rag
12
1
100% credibility
Found Feb 03, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
C++
AI Summary

Mojo is a high-performance web crawler that fetches entire websites and converts HTML into structured Markdown files optimized for AI and LLM training datasets.

How It Works

1
📰 Discover Mojo

You hear about Mojo, a speedy tool that grabs website content and turns it into clean notes for AI projects.

2
📦 Download easily

Pick the ready-to-run file for your computer from the download page and save it.

3
⚙️ Set your preferences

Run it to see simple choices, like how many pages deep or helper addresses to avoid blocks.

4
🚀 Launch the grab

Give it a website address and hit go – it starts zipping through pages super fast.

5
⏳ Watch it work

Sit back as it politely collects pages, skips junk, and saves everything neatly.

📁 Get perfect files

Open your new folder of clean, ready-to-use notes for feeding your AI brain.

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Star Growth

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AI-Generated Review

What is mojo?

Mojo is a high-speed C++ crawler that slurps entire websites into clean, LLM-ready Markdown datasets. Fire it up with `./mojo -d 2 https://docs.example.com` to crawl docs or blogs, respecting robots.txt while dumping structured output for RAG pipelines or vector stores like Pinecone. Cross-platform binaries for Linux, macOS, and Windows mean no compile fights—search github mojo launcher download if you want quick setup.

Why is it gaining traction?

It laps Python tools like Scrapy on throughput via C++20 coroutines and async I/O, especially with JS rendering: a reverse proxy gateway rotates IPs per-request without restarting Chromium, slashing overhead. Auto-prunes dead proxies (SOCKS5 prioritized) and converts HTML to token-efficient Markdown. Beats Selenium/Puppeteer for SPAs without the reboot tax.

Who should use this?

AI engineers harvesting sites for LLM training data or RAG bases. Data teams scraping dynamic docs/SPAs for tools like Claude or NotebookLM. Devs ditching slow scripts for bulk crawls—pairs well with Milvus/Weaviate, not casual one-offs.

Verdict

Grab it if you need raw speed for AI datasets; MIT-licensed binaries and CLI shine. But 12 stars and 1.0% credibility scream "prototype"—light tests, no heavy prod yet. Solid start over bloated alternatives.

(178 words)

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