nikhilnt1234/TokenBurnRate
by Various
[](https://glama.ai/mcp/servers/nikhilnt1234/TokenBurnRate) π π - 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_usageget_summaryget_hintsget_hint_detailset_budgetlist_sessionslist_modelsexport_csvcache-utilizationmodel-swap-testingmodel-swap-debugverbose-outputssession-spikecontext-bloatretry-loopssingle-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
Open-source & AI alternatives
Swap-in tools that solve the same job. Weigh the trade-offs before you commit.
Get the free Developerβs Field Guide
A 27-page field guide to the AI coding workflow with Claude. Claude Code, MCP servers, the prompt patterns that work, and what to delegate. Free.
Enter your work email. We send it straight over, plus a few short notes worth knowing. Unsubscribe any time.
