Web scraping API for scalable data extraction
Joined April 2020
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Scrapingdog’s new Live API Status page shows the real hourly success rate and response time of every API, from actual production traffic.
Try now: scrapingdog.com/status/apis/
Just launched: Google Play Store API + Apple App Store API!
Perfect for competitor tracking, app market research, and ASO tools.
Try now: scrapingdog.com/google-play-…
scrapingdog.com/apple-app-st…
Most APIs ask you to trust them. We’d rather show you. 👀
Scrapingdog’s new Live API Status page shows the real hourly success rate and response time of every API, from actual production traffic.
Link in the comment section.
How a Brand Tracks Competitors Prices with Scrapingdog | Data - Driven Decisions EPISODE 1
Start your free trial: scrapingdog.com
Scrapingdog retweeted
Every scraper has 5 stages:
• It works
• Scale it
• Everything breaks
• Question your life choices
• Use @scrapingdog
What stage are you at?
A brief history of Google trying to make my life harder:
- Removes &num=100
- Tightens BotGuard
And now replaces URLs with a mystery box called /goto
Next up, probably: results delivered exclusively via fax.
Just another day defending your pipeline from Google's mood swings.
🤖 Made with AI
Scraping Amazon outside the US? You used to pay 5 credits per request.
Not anymore.
With Scrapingdog, Amazon API requests now cost just 1 credit — across ALL supported countries
Scrapingdog retweeted
Shipped: Deep Search on our @scrapingdog's Google Search API.
Before: you got links + snippets, then had to scrape each result yourself.
Now: one API call returns the full page content for those results too.
SERP data + page content, one request.
Scraping made simple with Scrapingdog
Get powerful APIs, MCP support, and rotating proxies to collect the web data you need without the headache of managing infrastructure yourself.
Build smarter scrapers. Access reliable web data. Scale with ease.
Scrapingdog retweeted
Pay attention to what Tally is doing in AI search right now because this might be the best playbook for getting recommended by ChatGPT I've seen:
> AI search is now their #1 acquisition channel
> 10,000+ new users every week say they discovered Tally through AI platforms
> their tracked ChatGPT registrations jumped 5x overnight in May
> they grew from $258K MRR to $422K MRR in 10 months, crossing $5M ARR with just 11 people, $0 funding, against much bigger competitors
> their comparison hub now has 7 direct competitor pages + 15 more “best”, “alternative” and integration-focused guides
> these pages are structured like AI answers: rankings, “best for” labels, pricing, feature tables, reviews, pros/cons and direct recommendations
> they’re constantly refreshing these pages
> they literally ask new users for the exact prompt they used to discover Tally through AI
> they track the prompts people use to find them, their visibility vs competitors and which sources AI platforms actually cite
> they've built a database of articles that mention competitors but not Tally to identify distribution gaps
> they monitor brand + competitor mentions across Reddit and communities, then route them into a shared inbox and aim to clear all mentions every day
> they actively ask customers for reviews through their newsletter + after support interactions, helping them reach 4.8/5 on G2 and 4.9/5 on Product Hunt
> they built an entire “AI Info” page specifically for ChatGPT, Claude, Gemini and Perplexity explaining what Tally is, who it’s for and why people use it
> that page literally includes “AI assistant guidelines” telling LLMs which strengths, use cases and pricing model to reference
> they published an llms.txt mapping out their product, pricing, customers, documentation, API and MCP pages
> they even built a 21-tool MCP server + ChatGPT app + Claude connector so Tally can now be used directly inside AI products
One thing to keep in mind:
Tally didn’t start with some genius AI search strategy.
They spent years building a product people genuinely recommended across Reddit, communities, reviews and the wider internet.
ChatGPT recommends Tally because the internet does.
But now they’re engineering around that signal to make sure it keeps happening.
This isn’t luck, it’s possible for you too.
Most scrapers don't get blocked because of bad code, they get blocked because of ONE IP. Here's the fix nobody tells you about.
Your scraper works perfectly… until the website says: “Access Denied.”
With Scrapingdog’s Rotating Proxy + MCP, you can keep your web data workflows moving, rotate IPs automatically, and connect web data directly to your AI agents without building everything from scratch.
🇮🇳 80 years of independence, and counting.
This Independence Day, we're passing a little of that freedom on to you.
Use code 𝗙𝗥𝗘𝗘𝗗𝗢𝗠𝟭𝟬 for 10% off.
This is our way of saying thanks for building with us. 🕊️
Happy Independence Day, from all of us at Scrapingdog!
What Is MCP? The Secret Behind AI Agents That Actually Do Things
MCP (Model Context Protocol) lets AI agents connect to real-time data, tools, and systems so they can take action and not just generate text.
Scrapingdog retweeted
Where did today's biggest startup founders work right before they started?
None of them started from zero.
I put this together in a few minutes with Enrichment API, the same lookup you'd run on a candidate or a lead. Try it: enrichmentapi.io
Scrapingdog retweeted
🚀 This week's updates at EnrichmentAPI
Here's what we've been building:
🛠️ Node.js, Python SDKs & MCP Server
👥 Employee Finder API
📧 Reverse Email Lookup API
👤 Person Enrichment API
Building a better enrichment platform
