tokenmap

Your AI coding stats, visualized.

A GitHub-style contribution heatmap that shows how much you actually use AI coding tools. One command. Auto-detected. Shareable.

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pip install tokenmap
tokenmap

That's it. It reads your local data, renders a heatmap in your terminal, and exports a shareable PNG.

Supported Tools

Tool	Data Source	What's Tracked
Claude Code	~/.claude/stats-cache.json	Tokens, models, sessions, costs
Codex CLI	~/.codex/sessions/*.jsonl	Tokens, models, session durations
OpenCode	~/.local/share/opencode/	Tokens, models, messages
Cursor	Cursor API + local state.vscdb	Tokens, models, usage events

tokenmap auto-detects which tools you have installed. No configuration needed.

Install

pip install tokenmap

Requires Python 3.10+.

System Dependencies

For PNG export, you need Cairo installed:

# macOS
brew install cairo

# Ubuntu/Debian
sudo apt install libcairo2-dev

# Fedora
sudo dnf install cairo-devel

Usage

# Basic — auto-detect all tools, export PNG
tokenmap

# Add your name to the heatmap
tokenmap --user yourname

# Filter to a specific tool
tokenmap --claude
tokenmap --codex
tokenmap --cursor
tokenmap --opencode

# Filter to a specific year
tokenmap --year 2025

# Change the color theme
tokenmap --theme dark-green

# Export as SVG instead of PNG
tokenmap --export svg

# Custom output path
tokenmap --out ~/Desktop/my-ai-usage.png

# Terminal only, no file export
tokenmap --no-export

# Copy PNG to clipboard (macOS/Linux/Windows)
tokenmap --copy

# Dump raw stats as JSON (for scripting)
tokenmap --json

# Show estimated cost breakdown by model
tokenmap --cost
tokenmap --claude --cost

# See all themes
tokenmap --list-themes

Themes

10 built-in themes — 5 light, 5 dark:

Dark	Light
dark-ember	green (default)
dark-green	purple
dark-purple	blue
dark-blue	amber
dark-mono	mono

Options

Flag	Description	Default
--user <name>	Username shown on the heatmap	—
--claude	Include only Claude Code data	—
--codex	Include only Codex data	—
--opencode	Include only OpenCode data	—
--cursor	Include only Cursor data	—
--theme <name>	Color theme	green
--export <fmt>	Export format: png or svg	png
--no-export	Skip file export, terminal only	—
--out <path>	Custom output file path	tokenmap.png
--copy	Copy PNG to clipboard after export	—
--year <year>	Filter to a specific year	last 365 days
--json	Output raw stats as JSON	—
--cost	Show estimated cost breakdown by model	—
--list-themes	Show all available themes	—

Programmatic Usage

from tokenmap import aggregate_multi, render_terminal, render_svg, compute_stats
from tokenmap.types import RenderOptions

# Load data from all detected tools
panels = aggregate_multi()

# Render to terminal
render_terminal(panels, RenderOptions(theme="dark-green", user="myname"))

# Generate SVG
svg_string = render_svg(panels, RenderOptions(theme="dark-green", user="myname"))

# Access raw stats
for panel in panels:
    print(f"{panel.tool}: {panel.stats.total_tokens} tokens")

How It Works

tokenmap reads locally stored data from your AI coding tools. It never sends data anywhere — everything stays on your machine.

1. Detect — scans for installed tool data directories
2. Aggregate — merges token usage, sessions, and model stats across tools
3. Render — generates a terminal heatmap + exportable image
4. Export — saves a high-res PNG/SVG with stats panel

Privacy

• All data is read locally from your filesystem
• Nothing is uploaded or transmitted
• The only network request is Cursor's API (to fetch your own usage CSV, using your local auth token) — and even that's optional with a loca

Attribution

This project is a Python port of tokenviz by Harsh Kedia. Original source: https://github.com/harshkedia177/tokenviz

Licensed under MIT. Original copyright retained.

License

MIT