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tokenmeter

Track AI token usage and costs locally in an SQLite database.

11|2|Updated Feb 6, 2026
Search Tags:#ai#llm#token usage#cost tracking#privacy#local storage
One-click install
npx skills add https://github.com/mupengi-bot/mupengism --skill tokenmeter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tokenmeter
Source: https://github.com/mupengi-bot/mupengism/tree/main/skills/tokenmeter
Command: npx skills add https://github.com/mupengi-bot/mupengism --skill tokenmeter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires typer, rich, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a private, local solution to track AI token usage and associated costs across various providers, helping users understand and manage their AI spending.

Core Features & Use Cases

  • Local Tracking: All usage data is stored locally in an SQLite database, ensuring privacy.
  • Multi-Provider Support: Tracks usage for Anthropic, OpenAI, Azure OpenAI, and Google Gemini.
  • Cost Calculation: Estimates real-time costs based on current pricing and breaks down usage by model and provider.
  • Use Case: A developer can use this Skill to monitor the token consumption of their AI-powered application, identify which models are most expensive, and ensure they are staying within budget.

Quick Start

Run tokenmeter dashboard to see a summary of today's AI token usage and costs.

Frequently Asked Questions about tokenmeter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track AI token usage and costs locally across multiple LLM providers?▼

You can track AI token usage and costs locally by storing data in a SQLite database, calculating real-time cost estimates, and breaking down usage by model and provider for Anthropic, OpenAI, Azure OpenAI, and Google Gemini.

Can I import session files to automatically log LLM token consumption?▼

Yes, you can automatically import LLM token consumption from session files. This local tracking method supplements manual logging and API-based fetching to populate your local SQLite database.

Does this local AI cost tracking approach support Google Gemini and Azure OpenAI?▼

Yes, local AI cost tracking supports Google Gemini and Azure OpenAI, alongside Anthropic and OpenAI. It calculates real-time cost estimates and provides breakdowns by model and provider for all supported platforms.

What is the best way to monitor AI spending without sending usage data to external servers?▼

The best way to monitor AI spending privately is using a local SQLite database to store token usage data. This ensures privacy by keeping all cost tracking and usage breakdowns on your local machine.

How do I view a summary of today's AI token usage and costs?▼

You can view a summary of today's AI token usage and costs by running the dashboard command. It displays real-time cost estimates and breakdowns calculated from your locally stored SQLite database records.

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