Extract Domains

Extract Domains from Text, URLs, and Documents

Extract Domains is a browser-based domain extractor for turning messy text into a useful list of website domains. Paste a paragraph, a collection of URLs, exported data, email addresses when the optional email setting is enabled, or text copied from a report, and the tool identifies domain names while removing URL paths, queries, fragments, ports, and surrounding punctuation.

The tool is designed for practical data-cleaning work rather than only simple URL lists. It can recognize full HTTP and HTTPS URLs, protocol-relative links, common URLs without a protocol, subdomains, internationalized domain names, and domains embedded in ordinary sentences. You can preserve the original order or sort results alphabetically, keep or remove subdomains, remove www., and convert domains to lowercase. Unique extraction uses the normalized value, so the normalization choices can directly affect which entries are considered duplicates.

Because extraction happens in the browser, the normal text workflow does not require a server-side text-processing service. This makes the tool convenient for quick research and data preparation while keeping pasted content on the device during processing. Large inputs are handled with efficient scanning and Set-based deduplication, while document parsers are loaded only when a compatible document is actually selected.

How to Extract Domains

1. Paste or upload your source. Put URLs, text, lists, or supported document content into the input area. You can also use the Sample button to see how extraction behaves.
2. Choose extraction options. Select all domains or unique domains. Decide whether www. should be removed, whether subdomains should be preserved, whether output should be lowercase, and whether email addresses should be included.
3. Choose the order. Original Order keeps the first appearance sequence. Alphabetical A–Z sorts the final domain values with a Unicode-aware comparison.
4. Extract Domains. Click the main button to scan the content. The statistics show how many domains were detected, how many are unique, how many are duplicates, and how many URL-like references were found.
5. Review and export. Search within the result list, select all visible results when needed, copy the complete result set, or download TXT, CSV, or JSON.

For advanced data cleaning, remember that normalization happens before duplicate comparison. For example, www.example.com and example.com become the same value when Remove www. is enabled. Likewise, a subdomain such as blog.example.com becomes example.com when subdomain removal is selected.

Features of Our Domain Extractor

• Text and URL extraction: find domains inside paragraphs, URL lists, copied web content, and exported datasets.
• Unique-domain extraction: use efficient deduplication to create a clean domain list.
• Normalization: remove www., preserve or remove subdomains, and lowercase output.
• URL component removal: paths, query strings, fragments, and ports are not included in the domain result.
• Internationalized domains: Unicode domain labels can be retained instead of being treated as ASCII-only text.
• RTL-friendly interface: mixed Arabic, Persian, Urdu, Hebrew, or other right-to-left text can be entered without forcing the content into an incorrect direction.
• Document input: common text and office formats can be parsed locally with browser-compatible libraries where practical.
• Multiple export formats: download one domain per line as TXT, structured CSV, or a JSON array.
• Result search: filter large result sets without changing the underlying extracted dataset.
• Responsive design: the workspace adapts from phones to large desktop screens without a narrow fixed card.
• Accessibility: semantic controls, labels, keyboard access, visible focus, live status updates, and reduced-motion support are included.

Why Use an Online Domain Extractor?

Manually copying domains from hundreds of links is slow and easy to get wrong. A domain extractor can separate the host portion from URLs and produce a consistent list that is easier to inspect, compare, clean, or import into another workflow. This is particularly useful when the source contains a mixture of complete URLs, bare domains, subdomains, punctuation, and unrelated prose.

SEO professionals can use domain extraction when cleaning backlink exports, competitor research notes, referral data, or lists of websites. The tool does not decide whether a website is valuable or authoritative; instead, it performs the mechanical extraction step so the resulting list can be reviewed in a spreadsheet or another analysis system.

Developers can use domain extraction to inspect URL datasets, prepare test fixtures, clean application exports, or identify hosts in documentation and logs. The ability to preserve subdomains is useful when the distinction between api.example.com, blog.example.com, and www.example.com matters.

Researchers and analysts can extract domains from articles, reports, datasets, transcripts, and other text. Unique extraction can turn repeated references into a compact set of websites for later categorization. Alphabetical ordering can make manual review easier, while original order is useful when sequence matters.

Marketing and data teams can clean lists gathered from multiple sources. Removing URL paths and tracking parameters reduces unnecessary variation, and removing duplicate domains can make a source list substantially easier to work with.

Domain Extraction, Normalization, and Subdomains

A domain is the host name used to identify a website or other network service. In a URL such as https://blog.example.com/articles?id=25, the host is blog.example.com. The path, query string, and fragment describe resources or navigation inside that host and are therefore removed by the extractor.

Normalization is important because the same website can appear in many forms. Protocols such as HTTP and HTTPS are not part of the extracted domain. A URL can also contain a port such as :8080, a path, query parameters, or a fragment. These components are stripped so that the result represents the host rather than the entire URL.

Subdomain handling requires more care. A naive algorithm that always removes the last two labels can break domains using public suffixes such as co.uk or com.au. This implementation uses a maintained-in-code fallback set for common multi-part public suffix patterns and treats unknown suffix structures conservatively. It does not claim to be a complete, continuously updated Public Suffix List implementation. If a rare or newly delegated public suffix is important to your workflow, verify the registrable domain with a full PSL-based system.

Internationalized Domain Names and Unicode

The web is not limited to English or ASCII. Internationalized domain names can contain labels written in scripts used by Arabic, Persian, Hebrew, Chinese, Japanese, Korean, Cyrillic, Greek, Hindi and many other languages. Surrounding text can also be multilingual, for example: هذا الموقع https://example.com مفيد جداً. Domain extraction should not damage that surrounding text or assume that every character belongs to the Latin alphabet.

This tool uses Unicode-aware JavaScript patterns where available, safe string operations, and browser URL validation as a second layer. Unicode domain labels are retained in the result when they are supplied that way. Modern browsers can also represent domain names in their ASCII-compatible encoding internally. The extractor avoids unnecessary conversion of a user's Unicode result, because preserving the visible representation is generally more useful for text-processing tasks.

Unicode does not mean every dotted word is automatically a valid domain. The extraction engine applies hostname-oriented checks, rejects obvious numeric and malformed candidates, trims surrounding punctuation, and uses URL parsing where possible. These checks reduce false positives without imposing an ASCII-only restriction on legitimate internationalized domains.

Extract Domains from Documents

For simple text formats such as TXT, CSV, TSV, and LOG, the browser can read the file directly with the File API. HTML, XML, and JSON can also be read as text; the extractor scans their textual content rather than executing or rendering uploaded markup. This is important for safety because user-provided HTML is never inserted into the page as executable markup.

For office and document formats that use ZIP/XML containers, compatible browser libraries are loaded on demand. DOCX uses Mammoth for text extraction, XLS/XLSX uses SheetJS, and PDF uses PDF.js. OpenDocument and PowerPoint files use ZIP/XML inspection where the required library is available. Heavy libraries are intentionally not loaded during the initial page render, which helps keep the first interaction fast.

Document parsing is inherently more complex than reading plain text. A document may contain headers, footers, hidden content, images, charts, or unusual XML structures. The goal here is to extract readable text locally and then run the same domain engine over that text. If a file cannot be parsed safely or is too large, the interface reports a clear error rather than pretending that the file was processed successfully.

Privacy and Browser-Based Processing

The ordinary text workflow runs entirely in the browser. Uploaded supported files are read from the local file object and parsed locally whenever possible. The application does not intentionally store your pasted text in localStorage, cookies, IndexedDB, or the URL. Downloads are generated with browser Blobs, so the extracted list can be saved without sending it to a remote processing endpoint.

Privacy can still depend on the surrounding website and browser environment. If you add third-party libraries, those library files are requested from their CDN when needed. The uploaded document content itself is passed to the parser in the browser; it is not sent to those libraries' servers as part of the parsing operation. Avoid uploading confidential material to any website unless your organization's policies permit it.

Practical Use Cases

SEO Research

Extract domains from backlink lists, competitor research, exported reports, or notes containing many URLs. Unique extraction can provide a compact source list for further review.

Data Cleaning

Turn mixed URL lists into normalized domains, remove repeated entries, and export a clean TXT, CSV, or JSON dataset.

Web Research

Identify websites mentioned across long articles, reports, transcripts, or research notes without manually copying each address.

Marketing

Clean domain lists gathered during campaign research or partner discovery while retaining the ordering needed for review.

Development

Inspect hosts in logs, URL fixtures, documentation, or application exports. Preserving subdomains helps distinguish service-specific hosts.

Research and Analysis

Extract website domains from articles, datasets, reports, and documents before categorizing or comparing the resulting sites in another tool.

Frequently Asked Questions