What email formats are detected?

The tool detects standard email formats (user@domain.com). It uses a regex pattern that matches most common email formats. Non-standard formats, obfuscated emails (e.g., 'user at domain dot com'), or emails in images won't be detected. For best results, ensure emails are in standard format.

What URL formats are detected?

The tool detects URLs starting with http:// or https://. Other URL schemes (ftp://, mailto:, file://) may not be detected. URLs without protocol prefix (e.g., 'example.com' without 'http://') may not be detected. For best results, URLs should include the http:// or https:// prefix.

Will the tool validate extracted emails or URLs?

No, the tool only extracts emails and URLs—it doesn't validate whether they're valid or active. Extracted emails/URLs may include invalid or non-existent addresses. Use email validation tools or URL checkers separately if you need to verify validity.

Can I extract from HTML or encoded text?

The tool works with plain text. If emails/URLs are in HTML (e.g., HTML entities, encoded), they may not be extracted correctly. Extract text from HTML first (remove HTML tags), then use this tool. For HTML source code, the tool can extract visible URLs but may miss encoded content.

Are duplicates automatically removed?

Yes, the tool automatically removes duplicate emails and URLs. Each unique email or URL appears only once in the results. However, slight variations (e.g., trailing spaces, different cases) are treated as different entries, so exact duplicates are removed but variations remain.

Extract Emails/URLs - Find Contacts Free

When to Use This Tool

Use this when:

You need to extract email addresses from contact pages, directory listings, or documents for mailing lists
You want to extract URLs from web pages, documents, or HTML source code for link analysis
You're collecting contact information from text sources for database import or CRM systems
You need to find all email addresses in text documents, email threads, or chat logs
You want to extract links from HTML source code or markdown documents
You're analyzing text data and need to identify all email addresses or URLs present
You're cleaning text data and want to extract structured information (emails, URLs) from unstructured text

Don't use this if:

You need to extract emails or URLs from very large texts (over 500,000 characters may process slowly)
You want to extract emails or URLs from images or PDFs (use OCR first, then extract from text)
You require extraction from binary files or non-text content (this tool only works with text)
You need to validate email addresses or URLs (this tool extracts but doesn't validate)
You want to extract from multiple files simultaneously (process files individually or use batch tools)

What is an Email & URL Extractor?

An email and URL extractor scans text content and automatically identifies and extracts all email addresses and URLs found within it. Our tool processes everything in your browser — your text is never sent to any server.

Extracting emails and URLs from text is essential for building contact lists from document content, harvesting links from research materials, extracting references from academic papers, pulling contact information from copied web pages, and creating structured data from unstructured text.

This tool is valuable for marketers extracting contact emails from business documents, researchers collecting reference URLs from papers, sales teams building prospect lists from company directories, journalists extracting source links from articles, and anyone who needs to quickly pull structured data (emails and URLs) from large blocks of unstructured text.

Compared to manually scanning text for emails and URLs (slow and error-prone for large documents), writing custom regex scripts (requires programming knowledge), or using browser extensions (which require installation and permissions), PureXio's extractor automatically identifies all valid email addresses and URLs using comprehensive pattern matching.

The tool handles various email formats (standard, with subdomains, with tags), URL protocols (http, https, ftp), URLs with and without protocols, and nested URLs. Results are presented as clean, deduplicated lists that can be copied individually, all at once, or downloaded as a file. The extractor also shows the count of unique emails and URLs found.

Best for: extracting all email addresses and URLs from text. Handles complex formats, deduplicates results. Copy or download lists. 100% private.

How to Extract Emails and URLs

Paste text containing emails or URLs into the input field. Text is scanned for email addresses and URLs

Click 'Extract Emails & URLs' to process. Tool extracts all emails and URLs found in text. Results are displayed in separate lists with counts

Copy extracted emails or URLs to clipboard. Use for contact lists, link extraction, or data analysis. Each list can be copied separately

Common Use Cases

Extract email addresses from contact pages or directory listings for mailing lists

Extract URLs from web pages or documents for link analysis or verification

Find all email addresses in text documents or email threads

Extract links from HTML source code or markdown documents

Collect contact information from text sources for database import

Extract all URLs from a webpage's HTML source for link checking

Find email addresses in chat logs, forum posts, or social media content

Features

Extract email addresses from any text using standard email format detection

Extract URLs (http:// and https://) from text automatically

Separate lists for emails and URLs with individual counts

One-click copy for emails or URLs separately

Removes duplicates automatically—each email or URL appears only once

Works with any text length (small snippets to large documents)

100% private—all processing happens in your browser

Limitations & Constraints

Email extraction uses standard email format—may miss non-standard formats or obfuscated emails

URL extraction finds http/https links—may miss other URL schemes (ftp, mailto, etc.)

Very long texts (>500,000 characters) may process slowly

Emails in images or encoded text (Base64, HTML entities) are not extracted

Some URL formats (without http:// prefix) may not be detected correctly

Troubleshooting

No emails or URLs found when text clearly contains them

Solution: Check if emails/URLs are in standard format. Emails must follow standard format (user@domain.com). URLs must start with http:// or https://. Non-standard formats or obfuscated emails (e.g., 'user at domain dot com') won't be detected. Ensure text is plain text, not encoded or in special formats. Prevention: Use standard email and URL formats for reliable extraction.

Extracted emails or URLs are incorrect or incomplete

Solution: The tool uses regex patterns to detect emails and URLs. Very long or complex emails/URLs may not match perfectly. Check extracted results and manually verify. Some edge cases (emails with unusual domains, URLs with special characters) may not be detected. Prevention: Review extracted results, especially for non-standard formats.

Processing is slow for large texts

Solution: Very long texts (>500,000 characters) may process slowly. Split text into smaller sections and extract separately, or wait for processing to complete. Close other browser tabs to free up resources. For extremely long texts, use desktop tools. Prevention: Process text in smaller sections if it's very long.

Some emails or URLs are missing from results

Solution: Emails or URLs in non-standard formats may not be detected. Obfuscated emails (e.g., 'user [at] domain [dot] com') won't be extracted. URLs without http:// or https:// prefix may not be detected. Check if emails/URLs follow standard formats. Prevention: Ensure emails and URLs use standard formats for reliable extraction.

Duplicate emails or URLs in results

Solution: The tool automatically removes duplicates, so each email or URL should appear only once. If you see duplicates, they may be slightly different (e.g., 'user@domain.com' and 'user@domain.com ' with trailing space). The tool treats these as different. Normalize text first if needed. Prevention: The tool removes exact duplicates—slight variations are treated as different entries.