Data Source Finder — stop guessing where to scrape

The hardest part of scraping isn't the scrape. It's knowing where the data actually lives. You waste hours Googling, wading past blogs and Pinterest, hunting for the one directory or registry that actually has what you need at scale.

Tell Data Source Finder what you want — it hands you the sources, ranked. Describe the data in plain English and it returns the richest directories, government registries, downloadable datasets, and listing sites that hold it, each scored by how extractable and how fresh it is, with the exact way to pull it.

"med spa businesses in Texas with emails" → americanmedspa.org (association directory), tdlr.texas.gov (state license registry), texmed.org… ranked, typed, and ready to scrape.

Why it finds what plain search can't: clever dorking

Anyone can search. This runs a library of advanced queries against every need — inurl:directory, inurl:members, filetype:csv, site:.gov, registry/license, "list of…", owner/contact patterns with the junk sites subtracted — then ranks the domains that recur across all of them. Recurrence is authority: the source that shows up for eight different expert queries is the one that actually holds the data. It surfaces the structured, bulk-extractable sources that keyword search buries under content farms.

What you get, per source

• type — registry (official, authoritative, bulk records) · dataset (a file/API — already structured) · directory (a member/listing page — many entities at once) · listing (single-entity page or seed).
• score (0–100) — structure × authority (recurrence) × freshness.
• freshness + live — is it up, and when was it last updated (so you don't scrape a graveyard).
• suggestedApproach — how to actually extract it (bulk export, crawl the directory, hit the API…).

Plus a SUMMARY: the top sources, a breakdown by type, and how many queries ran.

The scout for your whole pipeline

Data Source Finder is the top of the funnel: describe the need → find the sources → point a scraper at them → score the result with Trust Score → act.

• Chain it (MCP / Zapier / Make / n8n): feed the top domain/url straight into a scraper like Contact Email Finder or YouTube Email Finder, then run the result through Scrape Trust Score before you act.
• For AI agents: an agent that needs data first asks where to get it — exposed via the Apify MCP server.

Integrations

curl -X POST "https://api.apify.com/v2/acts/apricot_blackberry~data-source-finder/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"need":"solar installers in California"}'

Also apify-client (JS/Python), the Apify MCP server, and the official Apify app in n8n / Make / Zapier.

Honest about the method

It searches public results with advanced operators and ranks by recurrence, source structure, and freshness — it points you at the best places to get data and how to pull them. It does not itself bypass logins or extract records (that's your scraper's job); it makes sure you aim it at the right target.