Convert PDF to JSON Online — Free
Extract text from PDF online — pull plain text or JSON-structured text from PDF pages for search, quoting, translation, or content reuse.
Direct converter coming soon
PDF text tools are coming. Today, our PDF tools handle merge/split/rotate.
Open Merge PDF Files →How to convert PDF to JSON
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Add your PDF file
Drop or select a .pdf file. Files up to 50MB process locally in your browser — nothing uploaded.
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Run the conversion
PDF.js parses your PDF's embedded text layer (the Tj, TJ, and related content stream operators) and emits plain text or structured JSON (page-by-page array of text spans with positions). For scanned PDFs without a text layer, use our OCR tool (on the roadmap) which uses Tesseract.js.
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Download your JSON
One click saves the result as a .json file. Your original file stays on your device.
Why convert PDF to JSON?
Text extraction lets you search, quote, translate, or repurpose PDF content without manual retyping. For legal review, paralegal work, academic research, content auditing, or feeding PDF content into an LLM for analysis, this is a daily-use capability. Extracting into JSON preserves structural info (page numbers, text positions) useful for more sophisticated processing.
Common PDF to JSON use cases
- Copying quotes or passages from a research PDF for citation in a paper or blog post
- Feeding PDF content into a custom RAG pipeline or LLM (ChatGPT, Claude) for summarization or Q&A
- Extracting contract clauses from a legal PDF for comparison, redlining, or template generation
- Translating a PDF's text in a translation tool (DeepL, Google Translate) that accepts plain text but not PDF upload
What file size to expect
A 20-page text PDF of a research paper yields a plain text file of roughly 50-150 KB. The JSON format with per-span positions is 2-3× larger (200-400 KB) but preserves page boundaries and layout info. A 300-page book PDF produces 400-800 KB of plain text.
Technical notes: PDF → JSON
PDF stores text as positioned glyph placements within content streams, not as flowing prose. PDF.js reconstructs logical text order by analyzing glyph positions — usually accurate, but multi-column layouts or complex page structures can produce jumbled word order. Scanned PDFs (where 'text' is actually pixels of characters) contain no text layer; extraction returns nothing. OCR is the right tool for scans. Unicode text is preserved including non-Latin scripts (Arabic, Chinese, Cyrillic). PDF form fields' values are extractable separately.
Compatibility and browser support
PDF.js runs in any modern browser and supports PDF 1.0 through 2.0 specifications. Password-protected PDFs need the password entered. Output text is standard UTF-8, parseable by any programming language or text editor.
PDF vs JSON
| JSON | ||
|---|---|---|
| File size | Varies | Compact |
| Quality | Preserves layout | Lossless data structure |
| Transparency | Yes (within pages) | N/A |
| Browser / app support | Universal | All programming languages |
| Best for | Documents, forms, archival | APIs, configs, structured data |
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Frequently Asked Questions
Will OCR work for scanned PDFs?
Not in the basic text extractor — OCR requires Tesseract.js (our OCR tool is on the roadmap). The text extractor only reads the PDF's embedded text layer; scans don't have one.
Output format?
Plain text (flowing prose per page, joined by form feeds) or JSON (structured as an array of pages with text spans and positions). Choose via the output dropdown.
Multi-column layouts?
Text order follows PDF's content stream, which approximates reading order. Two-column academic papers usually work; complex magazine-style layouts may produce scrambled word order.
Non-Latin scripts?
Unicode text is preserved — Arabic, Chinese, Japanese, Korean, Cyrillic, Greek, Hebrew, Devanagari, and others extract as UTF-8 correctly if the PDF embeds them as Unicode text (most modern PDFs do).
Password-protected PDFs?
Supported — enter the password when prompted. It's used in-browser only and not stored or transmitted.
Form fields?
Extractable as a separate object mapping field names to values, useful for parsing filled PDF forms in bulk.