ScraperAPI MCP. Get structured data from Google, Amazon, and SPAs.

Look, if you're scraping data at scale, you know the drill: websites fight back. IP bans, CAPTCHAs, anti-bot systems—they’ll shut down your little script faster than you can say 'Rate Limit.' This MCP server equips your AI client with everything needed to bypass those roadblocks automatically. You get proxy rotation and headless browser power so you can pull structured data from almost any corner of the web.

When you need to scrape standard, static HTML from a URL, use scrape_html. It handles automatic proxy rotation, keeping your requests clean while pulling down the basic content. If the site is semi-dynamic or just needs general scraping, custom_scrape lets you define specific parameters for any target you're hitting.

For modern websites—the ones built on Single Page Applications (SPAs) like React or Vue—you can’t just scrape the raw HTML; the content loads after JavaScript runs. That's where scrape_js_rendered comes in. You run it, and your agent executes all the necessary JavaScript to load the dynamic content before pulling down the final, usable HTML.

When you hit sites with serious security measures—the kind that trip up standard scrapers—you use scrape_premium. This function cycles through high-quality residential proxies, letting you bypass even the most aggressive anti-bot systems and those notorious cloudflare setups.

When it comes to specific, structured data sets, this thing is killer. If you're pulling product information from Amazon, scrape_amazon pulls parsed metadata—you get the price, the rating, all that good stuff—just by using an ASIN or a general URL. For market research, if you need Google Search Engine Results Pages (SERPs), use scrape_google_serp.

You give it a keyword, and your client gets structured, machine-readable data detailing the top results and snippets for that query. This raw JSON feeds right back into your conversation context.

You wanna capture an entire page layout—not just the text—for visual proof? get_screenshot_link generates a temporary URL that gives you a high-resolution screenshot of the whole thing, so you can show someone exactly what you saw.

For massive scraping jobs—say, pulling down thousands of records for an archive project—don't let your agent hang up waiting. You use create_async_job to start a background scrape and get back an ID. Later, you check the status with get_async_job using that ID until the results are ready. It runs in the background so your chat thread never freezes.

You also keep tabs on usage. To know how much bandwidth you're burning through, run get_account_stats, and if you need to test a specific setup with unique rules, you can use custom_scrape parameters. This whole server turns your AI agent into a professional data extraction machine that doesn't sweat the dirty work of proxies or JavaScript rendering.