TL;DR
Self-hosted OpenTelemetry backend for tracking token usage, costs, and performance across Claude Code, Gemini CLI, and OpenAI Codex—single binary, zero external dependencies.
Key Points
- Single ~54MB binary with embedded frontend; ~97MB Docker images for linux/amd64 and linux/arm64
- DuckDB-powered analytics with real-time WebSocket dashboard and historical JSONL/JSON import
- Cost tracking for 67+ models across Claude, Codex, and Gemini with pricing data embedded
- OTLP-native ingestion (HTTP/JSON and HTTP/Protobuf) with local-only data persistence
Why It Matters
Developers using AI coding assistants gain visibility into token consumption, API costs, and performance without shipping telemetry to third-party services. This addresses a critical gap in local development workflows where cost tracking and debugging of AI tool behavior has been opaque, enabling teams to optimize spending and understand tool performance characteristics.
Source: github.com