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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.

Related MCP server: contextpulse-mcp

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

Available Tools

6 tools
cost_reportB

Get a spending report.

Args: period: 'today', 'week', 'month', or 'all'

Inputs: period. Returns: result

cost_trendB

Show daily spending trend as a text chart.

Args: days: Number of days to show (default: 7)

Inputs: days. Returns: result

estimate_costA

Estimate cost without logging it. Use for planning.

Args: model: Model name tokens_in: Expected input tokens tokens_out: Expected output tokens

Inputs: model (required), tokens_in (required), tokens_out (required). Returns: result

log_costA

Log token usage and cost for a task. Call this after each AI interaction.

Args: model: Model name (e.g., 'claude-sonnet-4-6', 'gpt-5.4') tokens_in: Number of input tokens tokens_out: Number of output tokens task: Description of what the task was

Inputs: model (required), tokens_in (required), tokens_out (required), task. Returns: result

set_budgetA

Set daily and/or monthly budget limits.

Args: daily_limit: Maximum daily spend in USD (0 = don't change) monthly_limit: Maximum monthly spend in USD (0 = don't change)

Inputs: daily_limit, monthly_limit. Returns: result

supported_modelsA

List all supported models and their pricing.

Inputs: no named parameters. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clear and distinct purpose: cost_report for spending summaries, cost_trend for daily trends, estimate_cost for planning, log_cost for recording usage, set_budget for limits, and supported_models for pricing info. No overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., cost_report, set_budget). Even 'supported_models' fits as a verb+noun. The naming is predictable and clear.

    Tool Count5/5

    With 6 tools, the server is well-scoped for cost management—covering logging, estimating, reporting, budgeting, and model listing. This is a natural and complete set without being excessive.

    Completeness4/5

    The surface covers main cost operations: logging, estimating, reporting, trending, and budget setting. Minor gaps like viewing current budget limits or resetting budgets exist, but these are not critical for the core workflow.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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