Extract Phone Numbers from Text
Paste any text — emails, documents, web pages — and NumSwift instantly finds and extracts all phone numbers. No signup, no install, completely free.
Last updated: 2026-02-21
Extract Phone Numbers Instantly
How to Use the Phone Number Extractor
Start by pasting text with phone numbers to see them appear here!
1. Copy Text
Copy text with phone numbers
2. Extract Numbers
Paste & extract
3. Use the Numbers
Call, SMS, or WhatsApp
🔒 Privacy-First Tool
All processing happens in your browser. Your data never leaves your device and is not stored on our servers.
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💡 Pro Tips
- • Paste text from emails, documents, or websites
- • Works with international phone numbers from all countries
- • Click WhatsApp to message without saving contacts
- • Your extracted numbers are saved locally for quick access
How to Extract Phone Numbers
- Copy the text that contains phone numbers
- Paste it into the text box above
- Phone numbers are highlighted in real-time as they are detected
- Click Extract to get a clean list of all unique numbers
- Use the extracted numbers to call, SMS, or WhatsApp directly
Supported Formats
- International format: +1 (555) 123-4567
- Local format: (555) 123-4567 or 555-123-4567
- Compact format: 5551234567
- European format: +44 20 7946 0958
- Numbers from 200+ countries with automatic country detection
Where People Extract Phone Numbers From
Phone numbers appear in all kinds of documents and digital content. NumSwift handles them all — just copy the text and paste it in. Here are the most common sources:
- Emails and email signatures — Business emails often contain phone numbers in signatures, footers, or inline text. Copy the entire email body and let NumSwift find them.
- Web pages and directories — Contact pages, business listings, and online directories often list multiple numbers. Select all text on the page and paste it in.
- PDF documents and invoices — Contracts, invoices, and official documents frequently include phone numbers. Copy the text from your PDF viewer.
- Spreadsheets and CSV files — Exported contact lists or CRM data often have phone numbers mixed with other data. Paste the raw content and NumSwift filters out just the numbers.
- Chat messages and social media — WhatsApp groups, Telegram channels, or social media posts where people share their numbers in free-form text.
Common Mistakes When Extracting Phone Numbers
Manually copying phone numbers from text is error-prone. Here are the most frequent issues that NumSwift solves automatically:
- Missing country codes — A local number like 555-123-4567 won't work for WhatsApp or international calls without the country code. NumSwift adds it based on your selected country.
- Extra characters — Numbers like "Call us: (555) 123-4567 ext. 200" need the extension and label stripped. NumSwift extracts just the dialable number.
- Duplicate numbers — The same number may appear multiple times in different formats. NumSwift deduplicates results so you get a clean list.
- Misidentified sequences — Not every string of digits is a phone number. NumSwift validates format and digit count against the selected country's rules to avoid false positives.
Frequently Asked Questions
▶How does NumSwift extract phone numbers from text?
NumSwift uses pattern recognition and the libphonenumber library to detect phone numbers in any format — international, local, with or without country codes, dashes, spaces, or parentheses.
▶What text sources can I extract phone numbers from?
You can extract phone numbers from emails, documents, websites, spreadsheets, PDFs, chat messages, or any text that contains phone numbers. Just copy and paste the text.
▶Does it handle different phone number formats?
Yes. NumSwift recognizes phone numbers in many formats including +1 (555) 123-4567, 555-123-4567, 5551234567, +44 20 7946 0958, and more. It supports numbers from over 200 countries.
▶Can I extract phone numbers from an email?
Absolutely. Copy the email body (or the entire email including signature) and paste it into NumSwift. It will find and extract all phone numbers, filtering out any duplicates.