Live limits, before you're blocked
Your Claude 5-hour and weekly limits with a forecast — “at this pace, ~5 hr to the limit” — a heads-up while there's still room to react, not at 95%.
Open source · macOS menu-bar app
A local-first command center for AI-assisted development. StackPulse reads the logs Claude Code and Codex already write to disk — no account, no API key, nothing leaves your Mac.
Scanning your Mac…
3 of 11 providers detected
One monitor, every provider
StackPulse reads the logs each tool already writes and turns them into cost, tokens, and live limits — locally, in real time. No API keys, no dashboards to wire up.
Claude
165M tok · full cost scan
ChatGPT · Codex
685M tok · full cost scan
Gemini
sessions · activity
A look inside

Home
Today's spend, live limits, active AI sessions, and anything that needs you — the moment you open it.

Diagnostics
Is StackPulse healthy, and if not, exactly what to fix — each issue listed with a repair step and a secret-free support bundle.

Missions
What your agents are doing across Claude, Codex, and Antigravity — observed locally, in real time.
What it shows you
Your Claude 5-hour and weekly limits with a forecast — “at this pace, ~5 hr to the limit” — a heads-up while there's still room to react, not at 95%.
Per-model, per-window token and cost for Claude Code and Codex, read from local logs. Every figure is a labeled estimate — never presented as your bill.
Live Claude, Codex, and Antigravity sessions observed on this Mac — what each one is working on, right now.
Launch a dev server in one tap, run remembered commands, and see whether each project's stack is current and secure.
Answers “is StackPulse working, and if not exactly why” — credentials, refresh, permissions, data integrity, each with a fix.
A full-screen monitor for a second display — AI usage and mission control at a glance while you work.
Honest by design
Every dollar figure is computed on your machine against an embedded table of public list prices, always tagged as a local estimate. On a subscription it's an equivalent metered figure — usually far more than you paid.
If it doesn't recognize a model, it counts the tokens but drops the cost rather than borrowing a sibling's rate — and a “canary” names the gap, so it can say “I might be under-reporting” instead of showing a confidently wrong total.
It labels every number with where it came from and states its known inaccuracies in the open. The whole design is built around honest reporting.
Eleven providers, honestly scoped
Per-model cost, cache metrics, and limit windows — read from local logs, zero network.
Sessions, recency, and model — its tokens live server-side at Google, so cost is not shown.
Installed / authenticated presence — no usage, no cost, no limits.
Open source · MIT
No black box. The portable Rust core makes no network calls at all, and the app is offline by default with a short, named list of opt-in exceptions that go only to the provider — never to us. Read every line, open an issue, or build it yourself.
Read the privacy policy →Clone StackPulse, run make run, and watch your AI spend in real time.