Wick MCP
A local MCP server that tracks token usage and costs for Claude Desktop and Claude Code, providing a live dashboard at localhost:6789.
README
Wick MCP — Claude token tracker for Desktop & Code
A local MCP server that meters Claude Desktop, Claude Code, and the CLI the same way the Wick Chrome extension meters claude.ai. It accumulates tokens, computes cost (USD + INR) and burn rate, estimates messages left, and streams it all to a live dashboard at http://localhost:6789.
Everything runs locally. No API keys, no accounts, no data leaves your machine.
How Wick MCP works
Wick tracks usage in two ways, so you pick effort vs. coverage:
| Client | How it tracks | Effort | Accuracy |
|---|---|---|---|
| Claude Code / CLI | Automatic. Wick reads the usage logs Claude Code already writes (~/.claude/projects/**/*.jsonl) and ingests the real per-turn token counts. |
Zero — install once, nothing else | Exact (real API numbers, incl. cache) |
| Claude Desktop | Claude calls the wick_track tool after each response (Desktop doesn't expose parseable logs). |
Paste a one-time custom-instruction | Approximate (model self-reports tokens) |
Either way the numbers land in the same session, the same dashboard, and the
same wick_status / wick_summary tools. The server auto-starts the Claude
Code watcher on boot — so for coding sessions, it just works.
Install in 30 seconds
One command — installs from npm and patches your Claude Desktop config automatically:
npx usewick-mcp install
Then restart Claude Desktop.
<details> <summary>Or install from source</summary>
git clone https://github.com/pranshuguptaa/wick-mcp
cd wick-mcp
npm install
npm run install-desktop
</details>
Verify it's working
Open Claude Desktop and type:
"Call wick_status"
You should see your session stats in a boxed panel.
Add to Claude Code (one command)
claude mcp add wick node /absolute/path/to/wick-mcp/server.js
That's the whole setup. Because Wick auto-reads Claude Code's logs, you do
not need any custom instructions — start (or continue) any coding session and
the dashboard fills in with real usage. Prefer a config file? Add the same block
to .claude/settings.json:
{
"mcpServers": {
"wick": { "command": "node", "args": ["/absolute/path/to/wick-mcp/server.js"] }
}
}
Make Claude Desktop track automatically
Claude Desktop has no readable usage log, so it reports via the wick_track
tool. Paste this once into Settings → Custom Instructions:
After every response, silently call wick_track with:
- model: the model you used
- input_tokens: your input token count
- output_tokens: your output token count
- cache_read_tokens: cache read tokens if any
Do this without mentioning it.
(Claude Code users can skip this entirely — the log watcher covers it.)
Feed data manually (demos / other clients)
Any tool can push a turn over HTTP — handy for screenshots or wiring up a client Wick doesn't natively watch:
curl -X POST http://localhost:6789/api/track -H 'content-type: application/json' \
-d '{"model":"claude-sonnet-4-6","input_tokens":1200,"output_tokens":400,"cache_read_tokens":0}'
Dashboard
Visit http://localhost:6789 while Wick is running (Claude Desktop launches the server automatically once installed). It shows:
- Messages left, session cost (₹ + $), and tokens as live stat cards
- Two arc gauges — session usage (amber) and daily-budget spend (purple)
- A live turn-history table (last 20 turns), updated over WebSocket
A ● LIVE amber dot shows when the dashboard is connected; it auto-reconnects
every 3 seconds if the server restarts.
Tools available
| Tool | What it does |
|---|---|
wick_track |
Track tokens for this response |
wick_status |
See current session stats |
wick_reset |
Start a fresh session |
wick_export |
Export data as CSV / JSON / Markdown |
wick_summary |
All-time usage totals |
Ports & storage
- 6789 — HTTP dashboard +
GET /api/status,GET /api/summary,POST /api/track - 6790 — WebSocket live updates
~/.wick/history.json— persisted session history (driveswick_summary)- CSV exports are written to
~/wick-export-<timestamp>.csv - Reads (never writes)
~/.claude/projects/**/*.jsonlfor the Code watcher
Environment overrides: WICK_HTTP_PORT, WICK_WS_PORT, WICK_NO_WATCH=1
(disable the Code watcher), WICK_CLAUDE_PROJECTS (custom log path).
How cost is computed
Prices are per million tokens (see models.js). Cache reads are billed at
10% of the input price, and Wick reports the savings versus paying full price.
INR is USD × 84.
| Model | Input $/M | Output $/M | Burn |
|---|---|---|---|
| Opus 4.8 / 4.7 / 4.6 | 15 | 75 | 5.0 |
| Sonnet 4.6 | 3 | 15 | 2.0 |
| Haiku 4.5 | 0.8 | 4 | 1.0 |
Messages-left estimate: Haiku ≈ 50 messages per 5-hour window, scaled down by the burn multiplier (Sonnet ≈ 25, Opus ≈ 10), minus messages already used.
Troubleshooting
wick_statussays the tool isn't found — fully quit and reopen Claude Desktop (MCP servers only load at startup).- Dashboard won't load — the server only runs while a Claude client (or
node server.js) is running. Check that ports 6789/6790 are free. - Claude Code usage isn't showing — the watcher tracks turns that happen
after Wick starts (it never back-fills history). Send one message and it
appears. Confirm
~/.claude/projects/exists and isn't overridden. - Claude Desktop isn't tracking — add the custom-instructions snippet above;
Desktop only calls
wick_trackwhen told to (Code needs nothing).
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。