How to verify lead domains and scrape metadata without paying SaaS credit markups (Python + n8n)

Description and use

A zero‑cost pipeline using Python and n8n filters out inactive domains, extracts lightweight metadata, and generates contextual openers with gpt‑4o‑mini, cutting enrichment costs from ~$180/1k leads to ~$2.

Problem

Domain decay wastes 15–30% of scraped domains, burning paid enrichment credits on dead or parked domains.

Outcome

The pipeline eliminates wasteful credit usage, reduces enrichment cost from ~$180/1k leads to ~$2, and provides contextual openers with minimal overhead.

Workflow

• Query Google DNS‑over‑HTTPS for MX records to validate domains.
• Drop domains with NXDOMAIN or no mail servers.
• For valid domains, fetch homepage title and meta description using Python’s urllib and regex.
• Feed the extracted metadata to gpt‑4o‑mini to generate contextual openers.
• Integrate steps into a self‑hosted n8n workflow for automation.

Evidence

Between 15% and 30% of scraped domains are dead, parked, or expired.

Source

Query Google’s public DNS-over-HTTPS API directly over standard port 443

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For verified live domains, extract the homepage <title> and meta description in ~200ms using the pure Python standard library

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Because the input payload is minimal, this drops enrichment costs from ~$180/1k leads down to just ~$2 in raw API tokens while generating contextual openers

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