Estimates the environmental footprint of your AI use — energy (kWh), miles driven, water used for cooling, and CO₂ — plus a prompt-efficiency score, working with any AI client by measuring token usage.
Counts LLM prompt tokens and estimates API costs across OpenAI and Anthropic models directly inside MCP-compatible chat clients. Supports exact tokenization for OpenAI models and fallback approximation for Claude when no API key is present.
Analyzes Claude Code session token usage and cost locally — where spend actually lands across cache-read, cache-write and output, and what is consuming the context window. Read-only and offline: it parses your own session files and exposes analyze_claude_cost, get_cost_benchmark and tokenscope_share_summary.
Provides intelligent analysis of token usage patterns and optimization recommendations to improve efficiency and reduce costs in Claude Code sessions. Offers real-time analysis, cost metrics, and actionable insights for better context window and tool usage optimization.