Extract Phone Numbers

Paste any block of text and this pulls out the phone numbers, deduplicates them, and gives you a clean list you can copy — all of them at once or one at a time. It's built for the tedious job of harvesting numbers from an email thread, a scraped page, a call sheet, or a wall of contact info, without hunting through it by eye.

It recognizes the common ways people write phone numbers: with or without a country code, area codes in parentheses, and separators like spaces, dashes, or dots. Anything with at least seven digits in a phone-like shape gets matched, then duplicates are collapsed so you don't get the same number five times.

Everything runs in your browser — the text you paste never leaves your device, which matters when you're processing contact lists. The result updates live as you edit the input.

Extraction is pattern-based. A regular expression looks for phone-like sequences: an optional country code (an optional + and one to three digits), an optional parenthesized area code, and groups of digits separated by spaces, hyphens, or dots. To cut down on false matches, any candidate with fewer than seven digits (after stripping non-digits) is discarded, since real phone numbers have at least that many. Matches are then put through a set to remove duplicates.

Because it's regex-based rather than a true phone-number parser, it optimizes for recall over precision — it aims to catch numbers written many different ways, which means it can also grab number sequences that merely look like phones (long IDs, some dates, order numbers). It doesn't validate that a number is real, assigned, or correctly formatted for a given country, and it won't normalize numbers into a canonical form. All processing happens locally in your browser.

A library like Google's libphonenumber actually validates and formats numbers against per-country rules — it knows a UK mobile from a US landline and can reject impossible numbers. This tool doesn't do that; it's a fast extractor, not a validator. If you need to verify, normalize, or classify numbers, run the extracted list through libphonenumber or a similar library afterward.

Where this shines is the quick harvest: you have text with numbers scattered through it and you want them out, deduplicated, in seconds. For that everyday task — cleaning up a contact dump, grabbing numbers from a document — it's faster than any validating parser, and you can always validate the results downstream if precision matters.