Free Email Extractor

What this tool does in plain English

Paste in any text — a webpage's source, a long PDF copy-paste, a CSV column, a Slack thread — and we pull every email address out into a clean list. Deduplicates them, groups by domain, lets you filter, exports as CSV / JSON / XLSX / TXT. The whole thing runs in your browser, so nothing leaves your machine.

Think of it as a fast pre-cleanup before whatever you're doing next — building a contact list, auditing who's emailed your support inbox, or feeding the results into our email verifier to confirm which addresses are still live.

Where users actually paste content from

• Long PDFs and Word documents — contract addenda, RFPs, vendor lists. Copy the text, paste here, get a clean list. Way faster than ctrl-F'ing for `@` symbols.
• Webpage source — paste the HTML of a contact directory or team page. Our HTML strip option pulls emails out of `<a href="mailto:...">` links AND visible text without duplicating either.
• Support inbox export — paste a few weeks of conversation history, get the list of everyone who's emailed you. Useful for building re-engagement segments.
• Forum or Slack threads — extract every email mentioned in a discussion. Sometimes people drop addresses inline without using a proper `mailto:` link.
• CSV column with mixed data — when a CSV has emails buried in a freeform `notes` field. Paste the column, we extract the emails.
• Old email backups or .eml files — drop a `.eml` file directly into the upload box. We pull sender, recipient, and any addresses mentioned in the body.

How the smart parts work

HTML stripping (auto-detected)

Paste raw webpage HTML and our naive approach would pull the same email twice — once from the visible text `Email: kevin@x.com` and once from the `<a href="mailto:kevin@x.com">` link. The strip-HTML option removes tags before extraction so you get one clean address per real occurrence. We auto-detect HTML in your paste and turn the option on by default — you can switch it off if you want literal tag attributes treated as text.

Gmail dot-equivalence dedup

Gmail and Proton treat dots as cosmetic — `kevin.smith@gmail.com`, `kevinsmith@gmail.com`, and `kev.in.smith@gmail.com` all deliver to the same inbox. Our extractor groups these together by default so your final list has one entry per real mailbox, not three duplicates. Toggle off if you specifically want the original dot placement preserved.

Same logic applies to Gmail's `+tag` addressing. `kevin+sales@gmail.com` and `kevin+support@gmail.com` deliver to the same inbox as `kevin@gmail.com`, so we dedupe those too. This catches a common pattern where someone's used plus-addressing to track which form they signed up through — useful info, but the same person.

Domain include/exclude filter

Type a comma-separated list to filter results. `gmail.com, yahoo.com` keeps only emails at those domains. Prefix with `!` to exclude: `!gmail.com, !yahoo.com` removes those. Mix and match: `acme.com, !spam-domain.io`. Common use cases:

• B2B prospecting — exclude `gmail.com, yahoo.com, hotmail.com, outlook.com` to keep only business domains.
• Internal audit — include only `yourcompany.com` to see who from inside is in the list.
• Vendor cleanup — include only domains you've worked with: `vendor-a.com, vendor-b.com`.

After extraction — what to do with the list

Pulling emails out is the easy part. Making them actually useful takes one more step.

Verify before sending anywhere

Extracted emails are pre-verification — we don't know if any of them still work. Run the list through our email verifier before importing into a CRM or hitting send on a campaign. The verifier opens an SMTP conversation with each recipient mail server and tells you which mailboxes still exist.

A typical extracted list from a 6-month-old document has 15-30% dead addresses. Importing those to your email tool without verification means sending campaigns to bouncing mailboxes — which tanks your sender reputation in the eyes of Gmail and Outlook.

Check syntax for the rough cases

If your source had typos (`kevin@gmail.con`) or unusual characters that snuck through our regex, run the list through our email syntax checker. It catches the structural problems plus provider-specific rules (Gmail rejects dashes, Yahoo rejects dashes, etc.) that the verifier might mark as bouncing without explaining why.

Find missing addresses

Sometimes your extraction misses people you know should be in the list. If you have their name + company domain, our email permutator generates every common email format for that combination so you can verify the most likely ones.

Is it legal to extract emails like this?

Extraction itself is just text processing — nobody can object to copying text and running a regex on it. The legal question is what you DO with the extracted list:

• Cleaning your own data (your CRM, support inbox, contracts you've signed) — always legal. You already have the relationship.
• Sending personal one-to-one messages to addresses you found in public business contexts — generally allowed under CAN-SPAM (US) and GDPR's legitimate-interest provisions, provided your message respects opt-out and identifies you clearly.
• Bulk email campaigns to unverified extracted lists — risky. CAN-SPAM requires sender ID + physical address + unsubscribe; GDPR (EU/UK) wants explicit consent or strong legitimate-interest documentation; CASL (Canada) requires express consent before the first message.
• Scraping public-facing pages to build sales lists — operates in a gray zone. Legal in the US for true publicly-listed business contacts; restricted in the EU under GDPR even when the data is technically public.

What the tool doesn't catch (and what to do)

A few edge cases our regex misses:

• Obfuscated emails — `kevin (at) example (dot) com`. People write these on public pages to dodge harvesters. If you're extracting from a page with obfuscated emails, you'll need to manually fix those. Our email obfuscator explains the formats this typically takes.
• Internationalized addresses — `用户@example.com`. Our regex matches Latin characters only. International support is on the roadmap.
• Quoted local parts — `"Kevin Smith"@example.com`. RFC-valid but virtually never used in real mail.
• Images with email text — `<img>` tags showing email addresses as pictures. No way to extract without OCR.

For obfuscated or image-based emails, you'll need eyes-on review. The regex pulls the easy 95%. The remaining 5% are designed not to be extracted by automated tools — which is exactly why people obfuscate them in the first place.