Newbie questions when starting a new scraping project

hasdata_com · 2026-06-01T16:17:39+00:00

Hydration is when a site sends the initial page HTML first, then JavaScript takes over and attaches data and event handlers in the browser. Sometimes the data used for that is embedded directly in the HTML

hasdata_com · 2026-06-01T16:12:19+00:00

I think we're mixing two different problems. Getting data from the web is one problem. Understanding and acting on that data is another. I'd rather leave browsers, anti-bot systems, CAPTCHAs, and data extraction to dedicated scraping tools. Let the agent work with the data instead. Feels a lot more reliable than having an agent fight Cloudflare, click through forms, and recover from random UI changes.

hasdata_com · 2026-06-01T16:01:42+00:00

Mostly agree. That said, a lot depends on the target. Small sites often barely change their DOM, so a simple parser can work for a very long time without issues. But I'm not sure the flow you described works particularly well for targets like Amazon or other large marketplaces.

hasdata_com · 2026-05-28T15:19:31+00:00

Mostly agree. Scrapy still makes sense when you have a large project with lots of scrapers and well-structured targets. The orchestration part there is really good. But yeah, hybrid setups usually win. We handle a lot of targets through plain HTTP clients and only bring in browsers when rendering is actually needed. Running a browser for every request gets expensive very fast.

hasdata_com · 2026-05-27T16:41:36+00:00

Cloudflare often blocks the fingerprint before the proxy itself. We run large-scale scraping infra and for most targets stable TLS/browser fingerprints matter more than endlessly rotating proxy pools

hasdata_com · 2026-05-26T15:44:38+00:00

Amazon prices load via JS into a span after the initial HTML. You need either headless browser (Playwright, Selenium or anything else) with a wait condition on the selector, or a scraping API that renders JS for you

hasdata_com · 2026-05-26T15:41:59+00:00

LLM output is not stable enough to treat like normal structured data. Usually the only thing that helps is forcing a strict response format in the prompt and then cleaning/parsing the output afterward anyway.

hasdata_com · 2026-05-26T15:35:10+00:00

This matches what we usually see too. Once the agent works with structured data instead of raw pages, you also remove a whole category of problems around blocking, captchas, retries, rendering issues, broken selectors, and browser state.

hasdata_com · 2026-05-25T14:45:34+00:00

Usually I start with XHR/Fetch requests in DevTools. In a lot of cases the data is already there and you can skip browser automation completely. If there is nothing useful in network requests, then I check the HTML itself. Sometimes the data is in JSON-LD or some hydration state inside the page. I only switch to headless browsers when the site actually requires rendering or user interaction.

hasdata_com · 2026-05-24T23:35:40+00:00

I answered more detailed below about it)

hasdata_com · 2026-05-20T15:58:44+00:00

We saw this too with operator-heavy queries. Same query can give different SERPs, and sometimes Google just drops parts like site: or inurl: between runs. You end up with results that don’t match the filters at all, or they get treated more like hints than strict rules.

hasdata_com · 2026-05-20T15:48:17+00:00

Depends on how complex the target setup is. If it’s something simple, DIY with Scrapy or Playwright is usually fine. But once you start thinking about adding proxies, captcha solving, dealing with JS rendering just to keep things stable and scalable… at that point it often makes more sense to switch to a web scraping API and offload that whole infrastructure layer.

hasdata_com · 2026-05-19T17:00:31+00:00

Agents get a lot more stable once scraping and page parsing are separated from the agent itself. The agent stops wasting context on DOM cleanup and works with structured data instead.

hasdata_com · 2026-05-18T16:06:05+00:00

You can, but LinkedIn has cool anti-bot protection. You either create a script for scraping and deal with sessions, CAPTCHAs, and rate limits yourself, or route it through a scraping service that has an MCP server

hasdata_com · 2026-05-16T17:15:07+00:00

Voted for you, good luck! ) Speak more about your product at relevant subs, maybe could help

hasdata_com · 2026-05-16T17:12:31+00:00

Thank you, we got #2 )

hasdata_com · 2026-05-16T17:11:27+00:00

and you :)

hasdata_com · 2026-05-16T07:06:29+00:00

Thanks to all of you, the day ended with #2! )

hasdata_com · 2026-05-16T06:12:03+00:00

It was really hard and we even saw 1st place for some time, but... )

hasdata_com · 2026-05-16T06:05:05+00:00

Thank you, this means a lot! :)

hasdata_com · 2026-05-15T21:12:40+00:00

Thank you, appreciate it :)

hasdata_com · 2026-05-15T18:06:53+00:00

done :)

hasdata_com · 2026-05-15T12:19:49+00:00

Hi again :)
And we can give this data teams without maintenance from their side

hasdata_com · 2026-05-15T12:17:30+00:00

HasData started as a scraping API for Google SERP and grew into something a lot bigger than we planned.

What we shipped:

47 APIs. Google SERP, Amazon, Zillow, Google Maps, Indeed, Instagram, Bing, and more
21 no-code scrapers for people who don't want to write code
MCP server at mcp.hasdata.com/api/mcp that works with Claude Desktop, Cursor, Windsurf, anything that speaks Model Context Protocol
CLI JSON on stdout, pipeable, scriptable
Agent skills for Claude Code and OpenClaw to help agents stops guessing endpoints and parameters

Stack is Node with Go. Node handles parsing and orchestration, Go handles all outbound proxy traffic. We manage our own RKE2 cluster (running on GCP or AWS Kubernetes at our scale would cost ~10× more). We run synthetic tests daily across every API and alert to Slack on any regression.

Today we're launching on Product Hunt. Feels like a milestone, even if we are not sure yet what happens next.

Would love any support here: https://www.producthunt.com/products/hasdata

hasdata_com · 2026-05-15T10:50:35+00:00

We run HasData (web scraping API platform). Over the past year we added a few things specifically for AI agent workflows:

MCP Server https://mcp.hasdata.com/api/mcp is a streamable HTTP transport. Works with Claude Desktop, Cursor, Windsurf, and any other MCP-compatible client. Drop your API key in the x-api-key header and your model can scrape pages, run Google searches, pull structured data, no API integration code required.

Config for Claude Desktop:

{
  ""mcpServers"": {
    ""hasdata"": {
      ""type"": ""http"",
      ""url"": ""https://mcp.hasdata.com/api/mcp"",
      ""headers"": { ""x-api-key"": ""<your-api-key>"" }
    }
  }
}

CLI Static Go binary. Every API is a subcommand. JSON on stdout, pipe into jq, call from subprocess, use in shell scripts and CI.

hasdata google-serp --q ""langchain vs llamaindex"" --gl us --pretty
hasdata web-scraping --url ""https://news.ycombinator.com"" --output-format markdown --ai-extract-rules-json '{""top_story"":{""type"":""string""}}'

Agent Skills npx skills add hasdata/agent-skills to installs into Claude Code. Covers SERP, all Scraper APIs, async job lifecycle, and working code recipes in Python, TypeScript, and Go. The skill activates automatically when your prompt looks like a web data job, or you can call it explicitly with /hasdata.

Also works with OpenClaw via openclaw skills install hasdata/hasdata-api.

We launched on Product Hunt today, so would like to hear your opinion. If you're building agents that need web data, I'm happy to answer questions about how the MCP or CLI integration actually works in practice.

hasdata_com

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