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Local-first proxy for LLM spend visibility and control.

Project description

TokenBurn

htop for your LLM spend — proxy-only.

TokenBurn is a local-first HTTP proxy for LLM spend visibility and control.

Route OpenAI-, Anthropic-, and Gemini-compatible traffic through a local proxy. TokenBurn logs usage locally, attributes cost by model/provider/program/tag, and turns raw traffic into actionable waste reports.

No hosted backend. No account. No prompt egress by default.


Install

pip install "tokenburn[proxy]"
tokenburn proxy setup
tokenburn proxy start --background

After setup, clients that support base URL overrides can route through TokenBurn with no app-specific SDK integration.


What it does

  • Proxy-based capture — intercepts LLM traffic at the HTTP layer
  • Cross-language — works with Python, TypeScript, Go, curl, and anything else that can point at a base URL
  • Cross-provider — OpenAI, Anthropic, Gemini
  • Local logs — normalized JSONL logs under ~/.tokenburn/logs/
  • Spend reports — model, provider, endpoint, program, and tag breakdowns
  • Waste detection — highlights expensive patterns worth fixing first
  • Shareable output — terminal and exported reports

Core commands

tokenburn proxy setup
tokenburn proxy start --background
tokenburn proxy status
tokenburn proxy stop

tokenburn report
tokenburn gain
tokenburn share --open
tokenburn doctor

Product direction

TokenBurn is proxy-only.

That means the product lives at the proxy boundary rather than inside application runtimes.

The product lives at the network boundary, not inside app SDKs.


Repo docs

  • PROXY_TFF.md — proxy technical design
  • SPEC.md — product and positioning
  • keche.md — project operating brief
  • CLAUDE.md — maintainer workflow notes

License

MIT

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