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nikhilnt1234/TokenBurnRate

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[](https://glama.ai/mcp/servers/nikhilnt1234/TokenBurnRate) πŸ“‡ 🏠 - Track LLM token costs across Claude, GPT and Gemini. MCP server + CLI with optimization hints and $ savings esti

MCP

nikhilnt1234/TokenBurnRate

Added 7 June 2026

Overview

TokenBurnRate tracks LLM token costs across models from Claude, GPT, and Gemini. It delivers an MCP server and a CLI, with optimization hints and estimated cost savings.

Best for

Best for
Developers who need to monitor and optimize LLM API costs across multiple providers

Use cases

  • Monitor token spend across multiple LLM providers in real time
  • Identify cost-saving opportunities from usage patterns
  • Integrate cost tracking into development workflows via MCP or CLI

How to use

Install

npx token-tracker-mcp report

Tools exposed

  • log_usage
  • get_summary
  • get_hints
  • get_hint_detail
  • set_budget
  • list_sessions
  • list_models
  • export_csv
  • cache-utilization
  • model-swap-testing
  • model-swap-debug
  • verbose-outputs
  • session-spike
  • context-bloat
  • retry-loops
  • single-model-dependency

Tested with

Claude Desktop

Notes

TokenBurnRate tracks LLM token costs across models from Claude, GPT, and Gemini. It delivers an MCP server and a CLI, with optimization hints and estimated cost savings.

0 stars on GitHub. Last updated 2026-06-03. Licensed MIT.

Use cases

  • Monitor token spend across multiple LLM providers in real time
  • Identify cost-saving opportunities from usage patterns
  • Integrate cost tracking into development workflows via MCP or CLI

Pros

  • Supports three major LLM providers (Claude, GPT, Gemini)
  • Provides both an MCP server and a CLI for flexible integration
  • Offers actionable optimization hints and cost savings estimates

Cons

  • Low community adoption (0 GitHub stars) indicates limited validation
  • Focused solely on cost tracking, no usage management or budgeting features
  • Requires manual setup and configuration for each provider

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Supports three major LLM providers (Claude, GPT, Gemini)
  • Provides both an MCP server and a CLI for flexible integration
  • Offers actionable optimization hints and cost savings estimates

Cons

  • Low community adoption (0 GitHub stars) indicates limited validation
  • Focused solely on cost tracking, no usage management or budgeting features
  • Requires manual setup and configuration for each provider
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