AI assistants like Cursor, GitHub Copilot, and ChatGPT generate beautiful Markdown plans, specs, and documentation — often with Mermaid diagrams for architecture, flows, and sequences. But when you export them to PDF, diagrams appear as plain text.

This extension fixes that. It renders every Mermaid diagram as a real vector graphic before printing, so your AI-generated documents look professional in PDF form.

• 🤖 Made for AI workflows — Perfect for Cursor plans, Copilot specs, ChatGPT docs
• 📊 Real SVG rendering — Mermaid diagrams are actual graphics, not text
• 🎨 GitHub-flavored styling — Tables, code blocks, blockquotes, task lists
• 📄 Page numbers — Configurable footer with current / total pages
• ⚙️ Fully configurable — Page size, orientation, margins, font size
• 🔒 Privacy-first — Everything runs locally, no data leaves your machine
• 🖥️ No bundled browser — Uses your installed Chrome/Chromium

Open VS Code / Cursor, launch Quick Open (Ctrl+P / Cmd+P), and run:

ext install jcendal.ai-markdown-to-pdf

Or search for AI Markdown to PDF in the Extensions sidebar.

Export any Markdown content to PDF in one click. The command AI Markdown: Export to PDF is accessible from two locations depending on the type of document you are working with.

When working with a plan generated by Cursor (.plan.md), click the ⋯ menu in the top-right corner of the editor and select AI Markdown: Export to PDF.

For any standard .md file, right-click on it in the Explorer sidebar or within the editor to open the context menu, then select AI Markdown: Export to PDF.

• Command Palette — Cmd+Shift+P / Ctrl+Shift+P → AI Markdown: Export to PDF
• Editor title bar — top-right area when a .md file is active

The PDF is saved alongside the source file and opens automatically in your default viewer.

Write any Mermaid diagram in your Markdown and it will render as a vector graphic in the PDF:

```mermaid
graph TD
    A[Start] --> B{Decision}
    B -->|Yes| C[Action 1]
    B -->|No| D[Action 2]
    C --> E[End]
    D --> E
```

All Mermaid diagram types are supported: flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, Gantt charts, pie charts, mindmaps, and more.

Landscape A3 for large diagrams:

{
  "aiMarkdownToPdf.pageSize": "A3",
  "aiMarkdownToPdf.orientation": "landscape"
}

Extra time for complex diagrams:

{
  "aiMarkdownToPdf.mermaidWaitMs": 10000
}

Custom margins for binding:

{
  "aiMarkdownToPdf.margins": {
    "top": "20mm",
    "bottom": "20mm",
    "left": "30mm",
    "right": "15mm"
  }
}

Minimal PDF without page numbers:

{
  "aiMarkdownToPdf.showPageNumbers": false,
  "aiMarkdownToPdf.openAfterExport": false
}

Configure via File → Preferences → Settings and search for aiMarkdownToPdf.

A Chromium-based browser must be installed:

The browser is auto-detected. If detection fails:

{
  "aiMarkdownToPdf.chromePath": "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome"
}

┌─────────────┐     ┌──────────────┐     ┌───────────────────┐     ┌──────────┐
│  .md file   │ ──▶ │  marked.js   │ ──▶ │  Headless Chrome  │ ──▶ │   .pdf   │
│             │     │  (HTML)      │     │  + Mermaid.js     │     │          │
└─────────────┘     └──────────────┘     └───────────────────┘     └──────────┘

1. Markdown is parsed to HTML with marked
2. Fenced ```mermaid blocks become <pre class="mermaid"> elements
3. HTML is loaded in headless Chrome via puppeteer-core
4. Mermaid.js v11 is loaded from CDN and renders all diagrams as inline SVG
5. The extension waits for rendering to complete (configurable timeout)
6. Chrome prints the page to PDF with the configured settings
7. Temporary HTML file is cleaned up automatically

This extension runs entirely on your local machine:

• ✅ No telemetry or analytics
• ✅ No data collection or transmission
• ✅ Markdown content never leaves your computer
• ✅ The only network request is loading Mermaid.js from cdn.jsdelivr.net

Contributions, issues, and feature requests are welcome!

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'feat: add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

MIT © Jorge Cendal