Local-first proxy for LLM spend visibility and control.
Project description
TokenBurn
htopfor 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 designSPEC.md— product and positioningkeche.md— project operating briefCLAUDE.md— maintainer workflow notes
License
MIT
Project details
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