Server (SvelteKit + SQLite Docker container) + per-machine agent that parses Claude Code JSONL transcripts. docker-compose one-command deploy; raw transcript view + search gated behind SHOW_TRANSCRIPTS (hidden by default). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| agent | ||
| ops | ||
| src | ||
| static | ||
| .dockerignore | ||
| .env.example | ||
| .gitignore | ||
| .npmrc | ||
| .prettierignore | ||
| .prettierrc | ||
| DEPLOY.md | ||
| docker-compose.yml | ||
| Dockerfile | ||
| eslint.config.js | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| tsconfig.json | ||
| vite.config.ts | ||
toknmtr
Self-hosted Claude Code usage & analytics dashboard. An agent on each of your machines parses Claude Code's JSONL transcripts into a full event log and pushes it to a server (one SvelteKit + SQLite container). The server stores everything — usage, tool calls, commands, raw prompts/responses — and serves a dashboard plus a full-text-searchable session archive.
It's two halves:
- Server (
src/, shipped as a Docker image) — the dashboard, the ingest API, the DB. - Agent (
agent/+ops/, runs on each machine) — parses~/.claude/projects/**/*.jsonland POSTs to the server. Not part of the image; you run it wherever you use Claude Code.
The server image contains no data — the SQLite DB is created empty in a mounted volume on first run. All conversation content only ever comes from your agent pushing your transcripts to your server.
New here? Follow DEPLOY.md — a full step-by-step walkthrough (prerequisites, server, agent, security, updating). The sections below are the quick reference.
1. Run the server (Docker)
Requires Docker with the Compose plugin. From the repo root:
cp .env.example .env
# edit .env: set API_TOKEN to a long random secret
# openssl rand -hex 32
docker compose up -d --build
The dashboard is now at http://localhost:3001. The DB lives in the toknmtr-data
Docker volume; the container restarts unless stopped.
Privacy note — the dashboard has no auth. By default the two surfaces that expose
verbatim prompt/response text (the per-session transcript view and full-text search)
are hidden; charts, KPIs, and session metadata stay visible. Only set
SHOW_TRANSCRIPTS=true in .env once you've put the dashboard behind auth (reverse proxy,
VPN, etc.). Don't expose it to the public internet as-is.
Config (.env)
| Var | Purpose |
|---|---|
API_TOKEN |
Required. Bearer token the agent must send to /api/ingest. |
SHOW_TRANSCRIPTS |
true reveals transcript view + search. Unset = hidden (safe). |
PORT |
Host port is set in docker-compose.yml (3001:3000). |
2. Feeding it data (the agent)
The server starts empty. To populate it, run the agent on each machine where you use Claude
Code (needs Node 24+ for --experimental-strip-types). One-time setup per machine:
mkdir -p ~/.toknmtr
cat > ~/.toknmtr/env <<'EOF'
TOKNMTR_URL=http://<server-host>:3001
TOKNMTR_TOKEN=<the same API_TOKEN you set on the server>
EOF
chmod 600 ~/.toknmtr/env
Then, from a clone of this repo on that machine:
# one-time: ingest all transcripts already on disk
node --experimental-strip-types agent/run.ts --backfill
# ongoing capture — register the Stop hook so every turn pushes incrementally
ops/install-hook.sh
ops/install-hook.sh adds a near-zero-cost Claude Code Stop hook (additive + reversible
with --remove). An optional ops/install-cron.sh adds a reconcile sweep as a safety net.
Full agent/capture docs — the ~/.toknmtr/env format, the hook-vs-cron tradeoff, backfill,
and troubleshooting — are in ops/README.md.
Ingest is an idempotent upsert (keyed on host + session_id + uuid), so re-running the
backfill or overlapping hook/cron sweeps never duplicates data.
3. Development
Node 24, SvelteKit 2 (Svelte 5), TypeScript, better-sqlite3.
npm install
npm run dev # dev server
npm run check # typecheck
npm run build # production build → build/ (run with `node build`)
npm run lint # prettier + eslint
Pricing lives server-side in src/lib/server/pricing.ts — adding a model is a one-line
update. Because the subscription is flat-rate, all $ figures are notional (API-equivalent).