Use the free Extract Emails from Text below: your data never leaves your browser — all work happens on your device, and nothing is uploaded to any server.
The problem with email addresses buried in text
Email addresses rarely arrive in a tidy list. They arrive inside forwarded threads, copied web pages, chat logs, meeting notes, resumes and support tickets. Pulling them out by hand means reading every line, copying each address one at a time, and hoping you did not miss one or mistype another. In a long document that job is slow, boring and error-prone.
It also matters that the result is clean. A list with a missing address means someone does not get the message. A list with a mistyped address means a bounce or, worse, a message sent to a stranger. An automated extractor does the boring part exactly and leaves you the easy job of checking the result.
How this tool works
Paste any text and press Extract emails. The tool scans for the standard email pattern: a local part of letters, digits and common symbols, followed by @, followed by a domain with at least one dot and a top-level domain of two or more letters. Every match is collected into a list, one address per line.
Two options shape the output. Remove duplicates, on by default, keeps only the first occurrence of each address, which is what you usually want for a mailing list. Sort A to Z orders the list alphabetically, which makes it easier to compare with an existing list or to spot near-duplicates. Copy the result with one button and paste it wherever it needs to go.
Common uses
Organizers build invitation lists from forwarded messages and sign-up notes. Recruiters pull contact addresses out of resumes and cover letters. Support teams collect addresses from ticket exports. Sales teams turn a messy pile of notes from an event into a clean follow-up list.
Anyone migrating between tools uses it too: moving contacts out of an old system often produces a text dump rather than a proper export, and an extractor turns that dump back into a usable list in seconds.
What it catches and what it misses
The tool catches ordinary addresses like name@example.com, plus addresses with dots, plus signs and hyphens, and addresses on subdomains like mail.sales.company.co.uk. The plus sign matters: many people use tagged addresses like name+newsletter@example.com, and those are matched in full.
It deliberately skips things that look almost like addresses but are not valid: a name followed by @ with no domain, or a domain with a one-letter ending. It also cannot recover an address that was broken across lines or hidden behind a “name at domain dot com” obfuscation, because the characters are not actually there. For those, fix the text first and then extract.
Privacy and safety
Email addresses are personal data, and this tool is designed so that yours never leave your device. Everything runs in your browser: no upload, no server, no log. That makes it safe to use on private correspondence, customer data and internal documents.
That privacy cuts both ways. Just because you can extract addresses from a text does not mean you should email all of them. Only contact people who expect to hear from you, or who gave you their address for that purpose. Bulk email to harvested addresses is spam in most places and illegal in some, and it damages the sender’s reputation fast.
Tips
Before extracting, check the source text for addresses split across lines, which happens often in narrow chat windows and PDFs. Join those lines first, or the tool will miss the split address.
After extracting, sort the list and scan it once. Sorting puts near-duplicates next to each other, so a typo like jon@ and john@ stands out. Then deduplicate, copy, and paste into your mail program or spreadsheet. For a spreadsheet, one address per line pastes neatly into one column.
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