Extract Email Addresses - Online Email Harvester Tool

An Email Extractor (also called an Email Harvester) is a tool that scans text content and automatically identifies and extracts email addresses. It uses pattern matching (regular expressions) to find strings matching the standard email format (user@domain.tld). This tool runs entirely in your browser — no data is ever sent to any server.

Simply paste any text containing email addresses into the input box, configure your preferences (deduplication, sorting, domain filtering), and click "Extract Emails". The tool instantly finds all email addresses, removes duplicates if selected, applies any domain filters, and displays them as both a raw list and clickable badges. You can then copy or download the results.

Absolutely safe. All processing happens locally in your browser using JavaScript. No text, email addresses, or any data is ever transmitted to a server, stored, or logged. You can even disconnect your internet after the page loads and the tool will work perfectly offline. Your data remains 100% private on your device.

The tool supports all standard RFC 5322 email formats, including:
• Standard addresses: name@domain.com
• Plus aliases: user+tag@domain.com
• Subdomains: user@mail.sub.domain.co.uk
• Numeric domains: user@domain123.net
• Common special characters: dots, underscores, hyphens, percent signs in the local part.
It also handles internationalized domains (IDN) in their ASCII representation.

This browser-based tool cannot fetch content from URLs directly (due to CORS and browser security policies). However, you can easily extract emails from any website by: (1) opening the webpage, (2) selecting all text (Ctrl+A / ⌘+A), (3) copying it (Ctrl+C / ⌘+C), and (4) pasting it into this tool. For bulk URL scraping, consider using a dedicated server-side scraping tool.

When "Auto-dedup" is enabled (default), the tool performs a case-insensitive comparison of all extracted email addresses and removes exact duplicates, keeping only the first occurrence. The stats panel shows how many duplicates were removed. This is especially useful when extracting emails from long documents or email threads where the same address appears multiple times.

Yes! Expand the "Advanced" options and enter one or more domains (comma-separated) in the domain filter field. For example, entering gmail.com, outlook.com will only show email addresses from those two domains. Leave the filter empty to extract all domains. This is great for targeted lead generation or competitor analysis.

You have multiple export options:
• Copy All – Copies all extracted emails to your clipboard in plain text (one per line).
• Download TXT – Saves a .txt file with one email per line.
• Download CSV – Saves a .csv file with an "Email" header, compatible with Excel, Google Sheets, and most CRM tools.
You can also click any individual email badge to copy just that address.

Yes, 100% free. There are no hidden fees, no premium tiers, and no registration required. You can extract unlimited emails from unlimited text, as many times as you want. We built this tool to be a genuinely useful free resource. No paywalls, no usage limits, no catch.

The tool uses a robust regular expression pattern designed to match the vast majority of real-world email addresses while avoiding false positives. The pattern matches the standard structure local-part@domain.tld where the local part can contain letters, digits, and common special characters (. _ % + -), and the domain part supports subdomains and multi-level TLDs (like .co.uk). The regex is case-insensitive and handles edge cases like plus aliases and long TLDs.

There is no hard limit imposed by the tool. However, since processing happens in your browser, performance depends on your device's capabilities. The tool can comfortably handle texts containing thousands of email addresses. For extremely large datasets (e.g., 50,000+ emails), you may notice a slight delay during extraction and rendering.

While our regex is comprehensive, certain edge cases may not match, including:
• Emails with quoted local parts (e.g., "john doe"@domain.com)
• Emails with comments or folding whitespace per RFC 5322
• Emails using IP address literals (e.g., user@[192.168.1.1])
• Emails with non-Latin scripts (internationalized email addresses)
If you encounter consistently missed formats, try manually reviewing the text for unusual email patterns.