AI Training Data Collection
Collect and structure large-scale web datasets for fine-tuning and training AI models.
The Problem
Training and fine-tuning AI models requires large, clean datasets from diverse web sources. Collecting this data manually is impractical, and raw HTML is too noisy for model training.
The Solution
CrawlForge batch_scrape processes hundreds of URLs in parallel for scale, while extract_content returns clean, structured text ready for training pipelines. Build datasets from any web source.
Code Example
// Collect training data from documentation sites
const batch = await mcp.batch_scrape({
urls: [
"https://docs.example.com/guide/intro",
"https://docs.example.com/guide/setup",
"https://docs.example.com/guide/advanced",
// ... hundreds more URLs
],
format: "markdown",
});
// Extract clean content for each page
const dataset = await Promise.all(
batch.results.map(page =>
mcp.extract_content({
url: page.url,
format: "text",
remove_navigation: true,
})
)
);
console.log(`Collected ${dataset.length} documents`);Tools Used
batch_scrape5 credits
extract_content2 credits
Estimated cost: ~7 credits per document
Ready to Get Started?
Every new account gets 1,000 free credits. No credit card required.
Start Free with 1,000 Credits