MarkPDF

An open-source, minimalistic, standalone PDF and Markdown reader that puts the features usually locked behind paywalls (editing PDFs, annotating, and signing) — into a free, local-first desktop app with advanced AI features.

Features

On top of typical pdf reader features (view, rotate, zoom etc.) the app contains the following capabilities:

Cleanup

• The app is minimalistic by design and thus majority of junk present in your standard PDF reader is gone

AI

• Autodetection of all your CLI agents
• Connect any LLM provider (remote or local)
• Semantic search in your file (type keyward and press enter to see the results)

Typically behind paywall features

• OCR conversion
• Group of images to PDF conversion
• Edit PDF (for now just page ordering)

Viewing

• Light and dark themes with a theme switcher; defaults to the OS theme on first launch and remembers your choice.

Editing & Annotation

• Add, move, resize, edit, and delete text overlays (with font-size control).
• Highlight selected text.
• Add pinned comments from selected text; edit and delete them.
• Comments and highlights are saved as standard PDF annotations, viewable in other Acrobat-compatible readers.

Forms

• Detect fillable PDF form fields.
• Fill text fields, checkboxes, radio groups, and dropdowns.
• Form values are preserved in saved and exported PDFs.

Signing

• Draw a signature with mouse/trackpad, type it as text, or upload a signature image.
• Place, move, and resize visual signatures on the page.

Note: signatures are visual only — MarkPDF does not provide certificate-backed digital signatures, identity verification, or legal/compliance guarantees yet.

Vision

I am at the very early stage of what this app should be, but so far I see it as:

1. Free, open-source alternative to paid alternatives
2. PDF/Markdown viewer with advanced AI features for humans and AI agents.
3. Minimalistic design
4. Extensible with community plugins (just like Obsidian is)
5. Not a "chat with pdf" app - you have your favorite chatbot for that (though possible via plugins in future - see below)

Roadmap & Ideas

Looking for people who want to contribute to codebase and bring it to next level. Thus far, these are my ideas:

1. Plugin interface - to enable community building easily on top of the core (just like in Obsidian)
2. Signature interface - Bring Your Own Key (BYOK) for any signature provider - to remove vendor lock-in like the one in traditial PDF reader
3. Expose as MCP/CLI (plus a Skill.md) for pdf-to-markdown and image-to-pdf conversions - to have a fixed realiable tool for this task
4. Discussion interface for AI agents - read your PDF and discuss with multiple AI agents
5. Obsidian plugin - read and discuss with agents in MarkPDF, save conclusions in Obsidian/MD file.
6. Make semantic search state-of-the-art - I just did the basic one, good but not great
7. Make OCR state of the art - handling images is missing

and anything else you think we should implement to make it awesome.

Tech Stack

• TypeScript + React 19 for the UI.
• Electron for the desktop shell.
• PDF.js (pdfjs-dist) for rendering.
• pdf-lib for editing, annotations, forms, and export.
• Vite for bundling, electron-builder for packaging.
• Embeddings: generated locally with Transformers.js running ONNX models in-process. Curated models include BGE Small EN v1.5 (384-dim), MiniLM L6 v2 (384-dim), and BGE Base EN v1.5 (768-dim). Embeddings use mean pooling with L2 normalization.
• Vector store: a local SQLite database (via sql.js / WebAssembly) persisted to the app's user-data directory. Document text is chunked, embedded, and stored as Float32 vector blobs alongside their source page, with deduplication by content hash so re-opening a document doesn't re-index it.
• Retrieval: queries are embedded with the same model and ranked by cosine similarity against the stored chunk vectors, with a configurable score threshold (loose / balanced / strict) to tune precision vs. recall.
• Tunable chunking: precise, balanced, and contextual presets control chunk size and overlap to trade granularity against context.
• Text extraction: native PDF text where available, falling back to Tesseract.js OCR for scanned pages so even image-only PDFs become searchable.

Development

npm install
npm run dev

Build

npm run build

Packaging

npm run package   # unpacked app directory
npm run dist      # distributable installer
npm run dist:mac  # macOS DMG and ZIP for the current architecture

Release

The public download channel is GitHub Releases:

• Latest release page: https://github.com/cwik-tech/MarkPDF/releases/latest
• Direct latest Apple Silicon download: https://github.com/cwik-tech/MarkPDF/releases/latest/download/MarkPDF-mac-arm64.dmg
• Direct latest Intel download: https://github.com/cwik-tech/MarkPDF/releases/latest/download/MarkPDF-mac-x64.dmg

Before publishing macOS releases, add these GitHub Actions secrets:

• MAC_CSC_LINK: base64-encoded Apple Developer ID Application .p12 certificate.
• MAC_CSC_KEY_PASSWORD: certificate password.
• MAC_CSC_NAME: Developer ID Application signing identity qualifier without the Developer ID Application: prefix.
• APPLE_ID: Apple ID used for notarization.
• APPLE_APP_SPECIFIC_PASSWORD: app-specific Apple ID password.
• APPLE_TEAM_ID: Apple Developer Team ID.

To publish a release, update package.json version, commit the change, tag the same version with a v prefix, and push the tag:

git tag v0.1.0
git push origin main --tags

The release workflow builds separate Apple Silicon and Intel macOS DMGs and ZIPs on native runners, signs and notarizes them, then uploads them to the GitHub Release for the pushed tag.

License and Rights

MarkPDF source code is licensed under the Apache License, Version 2.0. See LICENSE.

The MarkPDF name, logo, icons, product identity, and associated branding are not licensed under Apache-2.0. See NOTICE and TRADEMARKS.md.

Third-party package notices are listed in THIRD_PARTY_NOTICES.md.

Contributing

Contributions are accepted under Apache-2.0. See CONTRIBUTING.md.