ASAPUtils
What is the Markdown Link Extractor?
Auditing a large Markdown file — a long README, a comprehensive documentation page, or an archived blog post — often means tracking down every outbound URL and image path. Finding them manually means scanning line by line, which is slow and easy to mess up.
The Markdown Link Extractor parses your Markdown source and builds a clean list of every link it finds. For each one, it shows the anchor text or alt text, the URL, and the title if one was provided. You can review the full list right in the browser, or export everything as a CSV for a spreadsheet-based audit.
Everything runs in your browser. No content is uploaded or stored anywhere.
How to Use the Markdown Link Extractor
- Paste your Markdown — drop your document into the editor on the left.
- Review the links — the tool populates a structured list of every URL found, with anchor text and title included.
- Export if needed — click “Export as CSV” to get a comma-separated file you can open in Excel or Google Sheets.
Use Cases
- SEO link audits — Get a full inventory of outbound links in documentation or blog posts. Check for missing anchor text, broken patterns, or links that need updating after a site migration.
- README hygiene — Before publishing a new version of a project, quickly confirm all links in the README are pointing to the right places.
- Content migration — When moving docs between platforms, extract every link and verify each one still resolves correctly in the new environment.
- Documentation reviews — Technical writers can pull a list of all external references in a document and hand it off for review without asking a developer to grep through files.
Why Use This Tool?
Grepping through Markdown files for URLs works, but it requires knowing the right regex, piping the output somewhere useful, and then formatting it for review. This tool skips all of that. Paste your content and get a clean, structured list within a second.
Because it runs client-side, it works with content that shouldn’t leave your machine — internal docs, pre-release notes, or anything with sensitive URLs.