Developer Tools
7 toolsSeven tools for the times a PDF has to become text, or text has to become a PDF. Every one of them runs entirely in your browser, which is the point: these are the jobs where the file is most likely to be a customer record, a signed contract or a production payload, and where pasting it into an upload form is the worst available option.
Developer Tools tools
PDF to Markdown
Extract PDF text into a simple Markdown file
PDF to Text
Extract plain text from PDF files
Markdown to PDF
Convert Markdown text into a plain, readable PDF
PDF to JSON
Extract PDF page text as structured JSON data
JSON to PDF
Convert JSON data to a readable PDF document
Base64 to PDF
Decode a Base64 PDF string back into a downloadable PDF file
PDF to Base64
Encode a PDF file as a Base64 string for APIs, JSON, and embedding
Why does encoding a PDF locally matter more than for other tools?
Because of what tends to be in the file. People reach for a Base64 encoder or a text extractor while debugging — mid-incident, with a real document from a real customer, at exactly the moment nobody is thinking carefully about where they are pasting things. Every other site ranking for these searches accepts an upload, which means the document lands on infrastructure you have never audited, under a retention policy you have never read. These pages read the bytes with the File API and never open a network connection, so the question does not arise.
What can a browser actually extract from a PDF?
The embedded text layer, and nothing more. A PDF records glyphs and their positions, not headings, paragraphs or tables, so extraction recovers words and where they sat on the page but cannot recover structure that was never written down. Two consequences follow. A scanned document has no text layer at all, so extraction returns an empty file — which is a useful diagnosis, not a failure. And converting to Markdown cannot invent heading levels; the honest output is clean prose, and any tool promising perfect Markdown from an arbitrary PDF is guessing from font sizes.
Should a PDF travel through your API as Base64 at all?
For small documents, often yes. It is the right answer when the transport is JSON-only, when the document is part of a signed payload that has to stay one object, or when you need a self-contained test fixture with no file storage attached. For large documents it is the wrong answer twice over: Base64 inflates the payload by a third, so a 6 MB PDF becomes roughly 8 MB of text, and the whole document has to be held in memory as a string at both ends. Above a few megabytes, multipart upload or a pre-signed URL costs less and fails less.
Where are the code samples and command-line equivalents?
On the individual tool pages. The Base64, JSON, text and Markdown pages each carry working snippets in the languages people actually automate these jobs in — browser JavaScript, Node, Python, cURL, PHP and C# — plus the equivalent command using qpdf, poppler, Ghostscript, MuPDF or the Base64 encoder your operating system already ships. Publishing the offline path is straightforward here because nothing on this site is metered: if the command line is a better fit for your job, use it.
Every tool in this category runs on your device
There is no upload step and no processing server. Open your browser’s network panel and run any of them — the only requests are for the page itself.