md-viewer: A Live-Reloading Markdown Viewer for Claude Code Workflows

md-viewer is a lightweight markdown viewer built specifically for developers using Claude Code to generate documentation. It provides live-reloading functionality that automatically updates when Claude modifies markdown files, eliminating the need to switch between terminal and editor windows.
Key Features
The tool addresses specific pain points when working with AI-generated documentation:
- Live reload by default: When Claude updates a file, the viewer re-renders automatically without manual refresh
- Independent file watching: Unlike VS Code preview, md-viewer watches files independently without requiring them to be open in an editor
- File explorer sidebar: Browse between documentation files without leaving the viewer
- Mermaid diagram support: Renders architecture diagrams natively when Claude generates them in markdown
- Tabbed interface: Open multiple documents across different projects simultaneously
- Lightweight footprint: Approximately 35 MB, only links libc, and opens instantly
Installation Options
The tool is available through multiple package managers:
# AUR (Arch-based)
yay -S md-viewer-git
Snap
sudo snap install md-viewer
Cargo (Rust)
cargo install md-viewer
Usage
Basic usage is straightforward:
- Open md-viewer on a second monitor or tiled next to your terminal
- Point it at your project's CLAUDE.md file or docs/ folder
- Use
md-viewer path/to/file.mdor drag and drop files - No "Open Folder" required - works with individual files
The tool is built with Rust and egui, and currently supports Linux only (both X11 and Wayland). It functions as a read-only companion for AI-assisted development, designed to stay open alongside terminal sessions throughout the workday.
📖 Read the full source: r/ClaudeAI
👀 See Also

Natural Language Autoencoders: Turning Claude's Internal Representations into Text
Transformer Circuits Thread publishes Natural Language Autoencoders that decode Claude's internal activations into readable text. GitHub repo and interactive demo available.

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Sentrial: Production Monitoring for AI Agents
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Testing δ-Mem on Apple Silicon: MLX Implementation and Benchmarks
δ-mem paper implemented via mlx on a MacMini 64GB shows mixed but promising local benchmarks, with gains in realistic replay scenarios.