CursorBurn — Real-Time Token Cost Monitor for Cursor Pro Power Users
Cursor Pro bills you the same flat fee while your token usage silently explodes, and you have zero visibility until the bill lands. CursorBurn hooks into your Cursor activity and gives you a live cost-per-session dashboard, weekly digest emails, and Slack alerts before you burn through your allocation. Think of it as your electricity meter for AI coding — finally.
Difficulty
intermediate
Category
Developer Tools
Market Demand
High
Revenue Score
7/10
Platform
Browser Extension
Vibe Code Friendly
No
Hackathon Score
6/10
Validated by Real Pain
— sourced from real community discussions
Cursor Pro users are experiencing sudden 3-10x token usage spikes with no in-product visibility, forcing manual post-hoc audits through raw API logs and spreadsheets to figure out what changed.
What is it?
Cursor Pro users on Reddit and HN are reporting 3-10x token spikes after model updates with no warning and no breakdowns. The current workaround is manually auditing API logs in spreadsheets after the damage is done. CursorBurn captures Cursor's local telemetry via a lightweight browser extension plus a local agent, buckets usage by session, file, and model, and surfaces a clean dashboard showing cost per action, model switch history, and a weekly email digest with anomaly alerts. This is 100% buildable right now: Cursor exposes enough local telemetry data via its log files, the extension layer is a standard Chrome MV3 extension, and the dashboard is a straightforward Next.js app. Stripe billing at $9/month is the simplest SaaS primitive. Similar cost-visibility tools like Helicone and OpenMeter validate the paying appetite.
Why now?
Cursor crossed 200k+ paid subscribers in early 2026 and simultaneously introduced more aggressive model switching, causing token spike complaints to peak on HN and Reddit in the June 2026 wave — no cost visibility tool exists yet.
- ▸Live token burn dashboard per session and per file (Implementation note: Node.js chokidar watches Cursor log directory, parses JSON telemetry events)
- ▸Weekly cost digest email with anomaly detection flagging sessions 2x above your baseline
- ▸Slack alert when hourly burn rate exceeds a user-set threshold
- ▸Model usage breakdown showing which model (GPT-4o vs Claude 3.5) is consuming the most tokens per week
Target Audience
Cursor Pro subscribers — estimated 200k+ active users as of June 2026, especially power users billing $20-40/month who noticed cost spikes.
Example Use Case
Maria, a senior engineer using Cursor 6 hours a day, gets a Slack alert that her token burn spiked 4x on Tuesday, traces it to a massive context file she forgot to exclude, fixes it, and cuts her monthly API overage by $60.
User Stories
- ▸As a Cursor Pro user, I want to see my token cost per coding session, so that I can identify which files or workflows are burning my budget.
- ▸As a power user, I want a Slack alert when my hourly token burn doubles my baseline, so that I can react before the week's allocation is gone.
- ▸As a team lead, I want a weekly email digest of my token usage trends, so that I can justify or adjust my AI tooling spend in monthly budget reviews.
Done When
- ✓Token dashboard: done when user sees a chart of today's token usage broken down by session within 10 minutes of installing the agent, with no manual data entry.
- ✓Slack alert: done when user sets a threshold, burns past it in a test session, and receives a Slack message within 2 minutes.
- ✓Stripe upgrade: done when user clicks Upgrade, completes Stripe checkout, and their dashboard immediately unlocks full 90-day history.
- ✓Weekly digest: done when user receives a formatted email every Monday showing their top 3 most expensive sessions from the prior week.
Is it worth building?
$9/month × 200 users = $1,800 MRR at month 3. $9/month × 600 users = $5,400 MRR at month 7. Math: 0.3% of 200k Cursor users converting via Reddit/HN posts.
Unit Economics
CAC: $8 via Reddit/HN organic posts. LTV: $108 (12 months at $9/month). Payback: 1 month. Gross margin: 88%.
Business Model
SaaS subscription
Monetization Path
Free tier: 7-day history. Pro at $9/month: full history, Slack alerts, weekly digest email. Upgrade triggered when free history limit hits.
Revenue Timeline
First dollar: week 2 via beta upgrade. $1k MRR: month 3. $5k MRR: month 8.
Estimated Monthly Cost
Vercel: $20, Supabase: $25, Resend: $10, Stripe fees: $15. Total: ~$70/month at launch.
Profit Potential
Profitable at $3k MRR. Full-time viable at $8k MRR with low infra costs.
Scalability
Can expand to VS Code Copilot, Windsurf, and other AI IDE cost tracking as one unified dashboard.
Success Metrics
Week 1: 500 extension installs. Week 3: 50 paid. Month 3: 85% month-1 retention.
Launch & Validation Plan
Post in r/cursor and HN Ask with a free beta link before writing any paid code. Recruit 10 power users via Cursor Discord for weekly feedback calls.
Customer Acquisition Strategy
First customer: DM 30 Cursor Pro users who complained about cost spikes in r/cursor or HN threads, offer 3 months free in exchange for a feedback call. Ongoing: ProductHunt launch, HN Show post, Twitter/X #cursor threads, Cursor Discord.
What's the competition?
Competition Level
Low
Similar Products
Helicone tracks LLM API costs but requires manual SDK wrapping. OpenMeter meters API usage but has no Cursor-specific integration. SpendWatch (internal idea) is broader automation cost tracking — none cover native Cursor session telemetry.
Competitive Advantage
Only tool purpose-built for Cursor telemetry visibility — Helicone and OpenMeter require manual API key setup and miss native IDE context entirely.
Regulatory Risks
GDPR: telemetry data includes file paths which may constitute personal data. Require explicit opt-in and provide a data deletion endpoint. Low overall regulatory risk.
What's the roadmap?
Feature Roadmap
V1 (launch): session cost chart, Slack alert, weekly digest email, Stripe Pro plan. V2 (month 2-3): file-level cost breakdown, model comparison view. V3 (month 4+): team dashboards, VS Code Copilot support.
Milestone Plan
Phase 1 (Week 1-2): log parser + ingestion API + basic dashboard ships, done when 5 beta users see real data. Phase 2 (Week 3-4): Stripe billing + alert system live, done when first paid upgrade completes. Phase 3 (Month 2): digest email + retention loop, done when 80% of paid users open week-2 digest.
How do you build it?
Tech Stack
Next.js, Supabase, Resend, Stripe, Chrome Extension MV3, local Node.js agent reading Cursor log files — build with Cursor for backend logic, v0 for dashboard UI components
Suggested Frameworks
-
Time to Ship
2 weeks
Required Skills
Chrome extension MV3, Node.js file watching, Next.js dashboard, Stripe billing.
Resources
Chrome extension docs, Cursor community Discord, Supabase quickstart, Stripe billing guide.
MVP Scope
extension/manifest.json (Chrome MV3 manifest), extension/background.js (log file polling via native messaging), agent/index.ts (Node.js log watcher with chokidar), app/page.tsx (dashboard landing), app/dashboard/page.tsx (cost chart UI), app/api/ingest/route.ts (telemetry ingestion endpoint), app/api/alert/route.ts (Slack + email alert trigger), lib/db/schema.ts (Drizzle schema: users, sessions, events), lib/parse.ts (Cursor log parser), .env.example (required env vars)
Core User Journey
Install extension + agent -> connect Supabase account -> see first session cost breakdown within 10 minutes -> set Slack alert threshold -> upgrade to Pro.
Architecture Pattern
Cursor log files -> Node.js agent (chokidar) -> POST to /api/ingest -> Supabase Postgres -> dashboard reads via Supabase client -> alert job checks thresholds -> Resend email + Slack webhook.
Data Model
User has many Sessions. Session has many TokenEvents. TokenEvent has model, token count, cost estimate, timestamp. User has one AlertConfig with threshold and channel.
Integration Points
Stripe for payments, Resend for weekly digest email, Slack Webhook API for alerts, Supabase for database and auth, Vercel for hosting, chokidar for local file watching.
V1 Scope Boundaries
V1 excludes: team accounts, VS Code or Windsurf support, custom model cost overrides, mobile app, white-label.
Success Definition
A paying Cursor Pro user finds CursorBurn on Reddit, installs it without any founder help, sees their real token burn within 5 minutes, and renews after month one.
Challenges
Cursor may change its local log format silently, breaking the parser overnight — distribution is harder: Cursor users are developers who expect free tools and need strong community proof before paying $9/month.
Avoid These Pitfalls
Do not depend on undocumented Cursor internals without a fallback parser — log format changes will break v1. Do not build team dashboards before validating solo user retention past 30 days. Finding first 10 paying users takes 3x longer than building the parser.
Security Requirements
Supabase Auth with Google OAuth, RLS on all user tables, 100 req/min rate limit per IP via Next.js middleware, file path data anonymized before storage, GDPR data deletion endpoint required.
Infrastructure Plan
Vercel for Next.js frontend and API routes, Supabase for Postgres and auth, GitHub Actions for CI, Sentry for error tracking, Vercel cron for alert jobs — total infra $70/month.
Performance Targets
100 DAU and 2,000 req/day at launch, API ingest under 200ms, dashboard load under 1.5s, no caching needed at launch scale.
Go-Live Checklist
- ☐Security audit complete.
- ☐Payment flow tested end-to-end.
- ☐Error tracking (Sentry) live.
- ☐Monitoring dashboard configured.
- ☐Custom domain set up with SSL.
- ☐Privacy policy and terms published.
- ☐5+ beta users signed off.
- ☐Rollback plan documented.
- ☐Launch post drafted for ProductHunt and r/cursor.
First Run Experience
On first run: a demo session with 7 days of pre-seeded fake token events is visible in the dashboard so it never looks empty. User can immediately explore the cost chart, set an alert threshold, and trigger a test alert — no real Cursor data required to see value. No manual config required: demo mode is on by default until the local agent sends its first real event.
How to build it, step by step
1. Define Drizzle schema for users, sessions, and token_events tables in lib/db/schema.ts. 2. Scaffold Next.js app with npx create-next-app and install chokidar, drizzle-orm, stripe, resend. 3. Build Node.js local agent that watches Cursor log directory and POSTs parsed events to /api/ingest. 4. Build Chrome MV3 extension with native messaging host to launch the agent on browser start. 5. Build /api/ingest route that validates and writes token events to Supabase. 6. Build /dashboard page with Recharts line chart showing daily token cost using v0 for component scaffolding. 7. Build /api/alert route that runs on a cron (Vercel cron job) and sends Slack webhook or Resend email when threshold exceeded. 8. Add Stripe checkout for Pro plan with webhook handler that sets user.plan in Supabase. 9. Add Supabase Auth with Google OAuth and RLS on all user tables. 10. Verify: install agent locally, open Cursor, write code for 5 minutes, open dashboard, confirm session appears with cost breakdown and alert fires correctly.
Generated
June 19, 2026
Model
claude-sonnet-4-6
Disclaimer: Ideas on this site are AI-generated and may contain inaccuracies. Revenue estimates, market demand figures, and financial projections are illustrative assumptions only — not financial advice. Do your own research before making any business or investment decisions. Technology availability, pricing, and market conditions change rapidly; always verify details independently.