willluck/claude-tools-dashboard repository overview

⁠Claude Tools Dashboard

Live wallboard for monitoring token savings across your Claude Code toolchain. Tracks RTK⁠, Headroom⁠, jCodeMunch⁠, and jDocMunch⁠ in a single-page dashboard with real-time SSE updates.

⁠What it shows

• RTK -- command-level token savings from the CLI proxy (SQLite)
• Headroom -- context compression stats from the MCP server (HTTP API)
• jCodeMunch -- indexed repos and session savings (filesystem + MCP)
• jDocMunch -- documentation indexing and section retrieval savings (filesystem)
• jDataMunch -- indexed datasets and session savings (filesystem + MCP)
• Combined total with sparkline trends and live activity feed
• Stats ticker -- weekly savings breakdown, daily burn rate, Claude usage percentages (5-hour, weekly, Sonnet), and reset countdown (reads Claude Code credentials directly, no extra tools needed)

⁠Quick start

# Clone and run locally
git clone https://github.com/Will-Luck/claude-tools-dashboard.git
cd claude-tools-dashboard
pip install -r requirements.txt
python app.py
# Open http://localhost:8095

⁠Docker (pre-built)

# Docker Hub
docker run -d --name claude-tools-dashboard \
  -p 8095:8095 \
  -v ~/.local/share/rtk:/root/.local/share/rtk:ro \
  -v ~/.code-index:/root/.code-index:ro \
  -v ~/.doc-index:/root/.doc-index:ro \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  --network host \
  willluck/claude-tools-dashboard

# Or from GHCR
docker run -d ... ghcr.io/will-luck/claude-tools-dashboard

⁠Docker (build from source)

docker build -t claude-tools-dashboard .
docker run -d --name claude-tools-dashboard \
  -p 8095:8095 \
  -v ~/.local/share/rtk:/root/.local/share/rtk:ro \
  -v ~/.code-index:/root/.code-index:ro \
  -v ~/.doc-index:/root/.doc-index:ro \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  --network host \
  claude-tools-dashboard

Use --network host so the container can reach the Headroom proxy on localhost. Alternatively, set HEADROOM_URL to point at the host IP. The credentials mount is optional -- without it, the usage ticker just shows dashes.

⁠Configuration

All settings via environment variables. Copy .env.example for reference:

⁠API

⁠Architecture

Single-file Flask app (app.py) that:

1. Polls RTK's SQLite database for command history and savings
2. Queries Headroom's HTTP stats API for compression data
3. Reads jCodeMunch, jDocMunch, and jDataMunch index files for repo, doc, and dataset metrics
4. Pushes aggregated state to browsers via SSE, and exposes the same snapshot as JSON (/api/stats) and Prometheus metrics (/metrics)
5. Serves a self-contained HTML/CSS/JS dashboard (no build step)

The frontend uses vanilla JS with CSS custom properties for theming. Sparkline charts are drawn with inline SVG. No external Python dependencies beyond Flask and python-dotenv.

⁠License

MIT