MCP Servers

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MCP server for tracking AI agent costs in real time. Per-message spending, budget alerts, visual dashboard. Works with Claude Code, Cursor, Windsurf, Codex, Gemini CLI, OpenClaw. Stop overspending on AI APIs.MCP server that tracks AI agent spending in real time. Visual dashboard, budget alerts, 15+ models. Works with Claude Code, Cursor, Windsurf.

创建于 3/27/2026
更新于 about 4 hours ago
Repository documentation and setup instructions

agent-cost-mcp

MCP server that tracks AI agent token usage and spending in real time. Budget alerts, per-task cost breakdown, visual dashboard, daily/weekly/monthly reports.

Works with any MCP client: Claude Code, Cursor, Windsurf, Codex, Gemini CLI, and more.

License: MIT Python MCP

Dashboard

Activity Log

Why?

Every developer using AI agents worries about spending. Most tools don't tell you what each message costs until the bill arrives.

This MCP server tracks it in real time — per message, per model, per day. Set a budget, get alerts, see exactly where your money goes.

Features

  • Visual dashboard — dark-themed web UI with spending charts, budget gauges, and activity log
  • Per-message cost logging — see what each AI interaction costs instantly
  • Budget alerts — warns when approaching daily/monthly limits
  • Cost reports — today, this week, this month, all time
  • Model breakdown — donut chart showing which model eats your budget
  • Spending trends — 14-day bar chart with color-coded spending
  • 15+ models supported — Claude, GPT, DeepSeek, Gemini, Llama
  • Estimate before running — check cost before expensive tasks
  • Local storage — all data stays on your machine (~/.agent-cost-mcp/)
  • Auto-refresh — dashboard updates every 30 seconds

Quick Start

1. Install

pip install agent-cost-mcp

Or with uv:

uv pip install agent-cost-mcp

2. Add to your AI tool

Claude Code — add to ~/.claude/settings.json:

{
  "mcpServers": {
    "agent-cost": {
      "command": "agent-cost-mcp"
    }
  }
}

Cursor — add to .cursor/mcp.json:

{
  "mcpServers": {
    "agent-cost": {
      "command": "agent-cost-mcp"
    }
  }
}

Windsurf — add to MCP config:

{
  "mcpServers": {
    "agent-cost": {
      "command": "agent-cost-mcp"
    }
  }
}

3. Open the dashboard

open dashboard.html

Or serve it locally:

cd ~/.agent-cost-mcp && python3 -m http.server 3456
# Open http://localhost:3456/dashboard.html

The dashboard reads from ~/.agent-cost-mcp/cost-log.json and auto-refreshes every 30 seconds. Leave it open in a browser tab while you work.

MCP Tools

These tools are available to any connected MCP client:

| Tool | What it does | Example | |------|-------------|---------| | log_cost | Log token usage and cost for a task | log_cost(model="claude-sonnet-4-6", tokens_in=1500, tokens_out=800, task="code review") | | cost_report | Get spending report | cost_report(period="today") — also: week, month, all | | set_budget | Set daily/monthly budget limits | set_budget(daily_limit=5.00, monthly_limit=50.00) | | cost_trend | Show daily spending chart | cost_trend(days=7) | | estimate_cost | Estimate cost without logging | estimate_cost(model="claude-opus-4-6", tokens_in=5000, tokens_out=3000) | | supported_models | List all models + pricing | supported_models() |

How It Works

You use Claude Code / Cursor / Windsurf normally
        ↓
MCP server logs each interaction (model, tokens, cost)
        ↓
Data saved to ~/.agent-cost-mcp/cost-log.json
        ↓
Dashboard reads the JSON and shows charts
        ↓
Budget alerts warn you before you overspend

The MCP server runs as a background process alongside your AI tool. You don't need to do anything extra — it tracks automatically when tools call log_cost.

Example Session

> How much did that last message cost?
Logged: $0.0165 (1,500 in / 800 out, claude-sonnet-4-6)

> Show my spending for today
# Cost Report — Today (2026-03-27)
- Messages: 26
- Tokens: 187,000 (118,000 in / 69,000 out)
- Total cost: $2.14
- Avg cost/message: $0.082

## By Model
  claude-opus-4-6: $0.99 (46%)
  claude-sonnet-4-6: $0.93 (43%)
  gpt-5.4: $0.19 (9%)
  deepseek-v3: $0.01 (1%)
  gemini-2.5-flash: $0.00 (<1%)

## Budget
  Daily: $2.14 / $5.00 (43%)
  Monthly: $12.43 / $50.00 (25%)

> Set my daily budget to $3
Budget set: $3.00/day, $50.00/month

Supported Models

| Model | Input ($/1M) | Output ($/1M) | |-------|-------------|--------------| | claude-opus-4-6 | $15.00 | $75.00 | | claude-sonnet-4-6 | $3.00 | $15.00 | | claude-haiku-4-5 | $0.80 | $4.00 | | gpt-5.4 | $2.50 | $10.00 | | gpt-5.2 | $1.50 | $6.00 | | gpt-5.1 | $0.60 | $2.40 | | gpt-4o | $2.50 | $10.00 | | gpt-4o-mini | $0.15 | $0.60 | | deepseek-v3 | $0.27 | $1.10 | | deepseek-r1 | $0.55 | $2.19 | | gemini-2.5-pro | $1.25 | $10.00 | | gemini-2.5-flash | $0.15 | $0.60 | | llama-4-maverick | $0.20 | $0.60 |

Missing a model? Open an issue or PR.

Data Storage

All data stored locally at ~/.agent-cost-mcp/cost-log.json. Nothing is sent to external services. Your spending data never leaves your machine.

Contributing

PRs welcome. Areas to improve:

  • Add more model pricing
  • Auto-detect token counts from MCP protocol metadata
  • Export reports to CSV/PDF
  • Slack/Discord alert integrations

License

MIT

Author

Built by Ha Le — University of Central Florida

快速设置
此服务器的安装指南

安装命令 (包未发布)

git clone https://github.com/vanthienha199/agent-cost-mcp
手动安装: 请查看 README 获取详细的设置说明和所需的其他依赖项。

Cursor 配置 (mcp.json)

{ "mcpServers": { "vanthienha199-agent-cost-mcp": { "command": "git", "args": [ "clone", "https://github.com/vanthienha199/agent-cost-mcp" ] } } }