Email addresses end up buried in all sorts of text: a long email thread, a signup export, a spreadsheet cell, the page source of a directory, a PDF of conference attendees. Copying them one by one is dull and prone to missing a few. Paste the text here and the addresses come out as a tidy list.
What gets found
The tool looks for the usual shape: a name part, an at sign, a domain, and a top-level ending of at least two letters. That includes addresses with dots, underscores, hyphens and plus signs, such as [email protected], and addresses in other alphabets. Punctuation around an address is left out, so a full stop at the end of a sentence is not treated as part of it.
Beside the list you get two figures: how many addresses were found, and how many are listed after filtering. If you leave “Remove repeats” on, an address that appears ten times is listed once.
Options worth using
“Remove repeats” is on by default and is almost always what you want. Ticking “Lowercase” before removing repeats makes [email protected] and [email protected] count as the same address. That is the right call in practice: domains are case-insensitive and almost every mail service treats the name part the same way. “Sort A to Z” orders the list, which helps you spot patterns such as one domain dominating.
You can also choose to receive the list one per line, or on one line separated by commas, which is the form a mail client’s To field accepts and what most import tools expect.
A note on using the addresses
Finding an address in text does not give you permission to email its owner. Rules such as GDPR in Europe and the CAN-SPAM Act in the US, along with similar laws elsewhere, govern unsolicited commercial email, and the details depend on where you and the recipients are. Use extracted addresses for legitimate purposes: tidying your own contact list, recovering addresses from your own correspondence, or building a list of people who have asked to hear from you.
What it will miss
Addresses written to defeat scrapers, such as “jane at example dot com”, are not recognised, and neither are addresses split across lines. A rare address with a quoted local part will not match. It will occasionally pick up something that is shaped like an address but is not, like an [email protected] filename. Scan the list before using it.
Once you have the list, tidy it with remove duplicate lines or sort lines if you need further processing, and the URL extractor and phone number extractor pull other contact details out of the same text. To limit a messy export to rows that mention a particular domain, use filter lines first.