io.github.whdrnr2583-cmd/token-meter

Official

by whdrnr2583-cmd · TypeScript

Local-first dashboard + MCP for Claude Code and Codex token usage. Per-MCP/tool breakdown.

Local dashboard tracking token usage for Claude Code with per-tool and per-MCP breakdowns.

Token Meter

Track Claude Code, Codex & Cursor token usage and cost locally — no account, no cloud.

One local dashboard for your Claude Code and Codex token usage. Free, MCP-aware, MIT-licensed core.

npm: @whdrnr2583/token-meter · GitHub: whdrnr2583-cmd/token-meter · Site: token-meter.dev

Token Meter parses the JSONL files that Claude Code and Codex already write to disk and turns them into a real dashboard: cost per project, per model, per MCP tool, per hour. Your data never leaves your machine.

When to use this

Use Token Meter if you:

want to know how many tokens and dollars your Claude Code or Codex sessions are costing — broken down by project, model, and MCP tool
are on a flat-fee plan (Claude Max, etc.) and want to see what the equivalent API cost would be
want to find which MCP server or tool is eating the most tokens, or which hour of the day is most expensive
want to resume a recent session and need the claude --resume / codex resume command handy
want all of the above offline, with no account and nothing uploaded

Not a fit if you need billing-grade numbers validated against your Anthropic or OpenAI invoice — Token Meter computes estimates from local JSONL files only.

MCP tools

When Token Meter is wired as an MCP server (install-mcp all), four tools become available to your AI assistant:

Tool	What it returns
`usage_summary`	Daily table of token counts, USD-equivalent cost, and call counts — broken down by day and model
`recent_sessions`	Latest sessions with paste-ready `claude --resume` / `codex resume` commands
`session_tools`	Per-tool breakdown inside a session: call count, total tokens, average latency, response size
`refresh_data`	Re-scans your local JSONL logs for new activity, then returns a fresh summary

All four are read-only. No data leaves your machine.

Example prompts

Copy-paste any of these into Claude Code or Cursor after installing the MCP server:

code

Show me my token usage and cost for the last 7 days.

code

List my recent sessions so I can pick one to resume.

code

Show the tool breakdown for my most recent session — which tool used the most tokens?

code

Refresh token-meter data, then tell me which model cost the most this week.

code

Which hour of the day am I spending the most tokens on?

Quick start

npx @whdrnr2583/token-meter ingest        # scan ~/.claude/projects + ~/.codex/sessions
npx @whdrnr2583/token-meter stats 30      # CLI summary for last 30 days
npx @whdrnr2583/token-meter serve         # http://localhost:8765 dashboard
npx @whdrnr2583/token-meter mcp           # run as an MCP server for Claude Code / Cursor

The package is published under an npm scope (@whdrnr2583/) because the bare token-meter name collides with an existing similar name on npm. The CLI binary is still called token-meter after install.

Connect Token Meter to your AI tool (MCP)

One command registers Token Meter with every supported client on your machine:

npx -y @whdrnr2583/token-meter install-mcp all

Handles Claude Code, Cursor, and Claude Desktop — idempotent, backs up existing config, preserves other MCP servers. Single-client variants: install-mcp claude-code | cursor | claude-desktop. Add --dry-run to preview.

Or have your LLM do it. Open Claude Code / Cursor / Claude Desktop and ask: "Read https://raw.githubusercontent.com/whdrnr2583-cmd/token-meter/main/docs/mcp-server.md and set up token-meter as my MCP server."

Manual one-liners (if you'd rather not run our installer):

Client	Command / config
Claude Code	`claude mcp add token-meter -- npx -y @whdrnr2583/token-meter mcp` then `claude mcp list` to verify
Cursor	Edit `~/.cursor/mcp.json` (Windows: `%USERPROFILE%\.cursor\mcp.json`) — see docs/mcp-server.md
Claude Desktop	Edit `claude_desktop_config.json` — see docs/mcp-server.md
ChatGPT	Stdio-only for now; HTTP wrapper recipe in docs/mcp-server.md
Other (Continue, Zed, custom)	`npx -y @whdrnr2583/token-meter mcp` over stdio

Then ask: "Use token-meter to show my recent sessions" or "Use token-meter usage_summary for this week".

Claude Code shortcut: run npx -y @whdrnr2583/token-meter install-command claude-code once to register the /token-meter slash command. After reopening your session, type /token-meter for a one-shot summary without natural language.

Full setup + verification + troubleshooting: docs/mcp-server.md.

Storage: ~/.tokenpulse/usage.db (SQLite). Remove the folder to start over. The folder name will become ~/.tokenmeter/ in a future release with an automatic migration; until then the v0.1 directory keeps its original name.

What you see

USD-equivalent cost per day, model, project. Useful if you're on a Max plan and want to know what the API would have cost.
MCP and tool breakdown: which MCP server is eating tokens, how slow each tool is on average, response sizes per call.
Hourly distribution of output tokens.
Claude Code + Codex side-by-side, in one view.

A note on the dollar figures

Costs are estimates computed locally from the token counts that Claude Code and Codex already write to their JSONL files, multiplied by the model's published per-million-token rate. They are not validated against your actual Anthropic / OpenAI invoice and may diverge for several reasons:

Vendors change pricing; the table in src/pricing.ts is a snapshot
Subscription plans (Pro / Max) bill a flat fee — the on-screen $ is what the API would have cost, not what you pay
Some token categories (server-side tool use, cache write variants) are approximated

Treat the numbers as relative signal for spotting waste, not as billing-grade accounting. Token Meter ships a regression test that the calculation is reproducible, and an audit script that checks invariants; neither verifies the rates against vendor invoices.

Why local-first

Your JSONL contains source code, prompts, and tool results. Token Meter never uploads any of it. Heuristics, regex, and SQL aggregation only.
No SDK to integrate, no proxy to configure for the free tier.
The CLI and dashboard core are MIT licensed.

Pricing

Tier	Price	What you get
Free	$0	Claude Code + Codex parsing, MCP/tool breakdown, hourly/model/project breakdown, 7-day history, 1 desktop alert
Pro	$5/mo	Everything in Free + 30-day history, unlimited smart alerts (desktop + webhook), session drill-down, cache efficiency, waste signals
Pro+	later	Local LLM proxy (Ollama / LM Studio / llama.cpp / vLLM), GPU/VRAM tracking, auto actions

Pro is live — Subscribe at token-meter.dev.

Pro+ ships once Pro sign-ups + community demand confirm the segment.

Roadmap

M1 ✅ Claude Code parsing, MCP/tool breakdown, hourly stats
M2 ✅ Codex integration
M3 Pro tier ($5), Polar.sh billing, license activation
M4+ Pro+ (local LLM proxy, GPU tracking), conditional on demand

Privacy & security

Tokens are counted from the JSONL files Claude Code and Codex already write. Token Meter does not touch network APIs of either vendor.
No prompt or response bodies are stored by default — only metadata (timestamps, token counts, tool names, response lengths).
The database lives under ~/.tokenpulse/; delete it to wipe. (Renamed to ~/.tokenmeter/ in a future release with an automatic migration.)

Changelog

See CHANGELOG.md for release notes and breaking changes.

License

MIT for the CLI, dashboard, and parsers. Pro-tier features ship in a separate package under a closed source license.

Install

claude_desktop_config.json

{
  "mcpServers": {
    "token-meter": {
      "command": "npx",
      "args": [
        "-y",
        "@whdrnr2583/token-meter@0.1.17"
      ]
    }
  }
}