NOW ON PYPI • 1.3.1 • USED BY FAST-GROWING TEAMS

Cut AI costs 30-60%.
Ship complex work faster.

TokenStretcher breaks down complex work into focused steps so your AI agents deliver better results using 30–60% fewer tokens.

pip install tokenstretcher
COPY
See 60-second start guide
✓ Prepaid only — zero surprise bills
Works with any LLM
Free plan previews
Want to just get started? Works inside AI agents
OpenCode
Cursor
Claude
Grok Build
CLI usage: tokenstretcher "task..." --key ...
Hover or tap preview • click copy • works on any screen size
30–60%
typical savings on complex tasks
9+
engineering teams already saving
0
risk of runaway API costs
WHY MID-SIZED TEAMS USE IT

Stop burning budget on vague,
expensive AI output.

WITHOUT TOKENSTRETCHER
  • → AI spend growing out of control
  • → Generic output that still needs heavy editing
  • → Hard to forecast monthly LLM bills
  • → One bad agent run can blow the budget
WITH TOKENSTRETCHER
  • → 30–60% lower cost on real engineering work
  • → Higher quality, production-ready output
  • → Detailed savings report after every job
  • → Prepaid only — full spend control, no surprises
Outcome: ship faster, spend less, keep finance happy
WHAT YOU EXPERIENCE

Smarter AI. Lower bills.
No extra work for your team.

01

Delegate & forget

Give it a complex task (new feature, big refactor, full system). It plans, breaks it down, runs specialist steps, and returns clean results.

02

Better results, lower cost

Specialized agents + short focused prompts = 30–60% fewer tokens and output that actually works the first time.

03

Full visibility + safety

See exact token use and savings after every run. Prepaid wallet — it stops before you overspend.

WHEN TO SKIP IT

Not every task needs TokenStretcher.
Save the big guns for big work.

JUST DO IT YOURSELF
  • • Quick questions or simple lookups
  • • Small bug fixes or one-line changes
  • • Trivial tasks that take seconds
  • • Straightforward "how do I..." requests
SAVINGS ARE MAXIMIZED HERE
  • • New features or large refactors
  • • Multi-step architecture + implementation
  • • Tests + documentation + deployment together
  • → Savings grow with complexity
START SAVING IN UNDER A MINUTE

Three steps. Zero risk.

01
Install
One command. Works on your laptop or in CI.
pip install tokenstretcher
02
Preview for free
Run with --plan-only first. See the full breakdown and estimated savings before spending a cent.
No API key required for plan previews.
03
Top up & run
Add prepaid credits (or use your own keys in local mode). Every job shows exact savings.
Buy credits →
For managers: share the plan preview with your team — they decide when to spend.
GET STARTED IN SECONDS

Simple CLI. Powerful Python API.

CLI
pip install tokenstretcher

# Basic usage
tokenstretcher "Build a production FastAPI service with JWT auth"

# Plan only (free preview)
tokenstretcher --plan-only "Refactor payment module"

# Interactive mode
tokenstretcher interactive
PYTHON
from tokenstretcher import Manager

manager = Manager()
result = await manager.run(
    "Create secure FastAPI auth with roles"
)

print(result.final_output)
print(result.savings.summary())
Full async support + custom config
Also works great inside Cursor, Claude, OpenCode, Grok Build and other agents used by engineering teams
ZERO RISK. PREPAID ONLY.

You preload funds.
You can never get a surprise bill.

Finance and engineering both love this. Every call is tracked live. When low, it stops and shows exactly how much to add. Full exportable logs.

tokenstretcher balance
tokenstretcher topup
tokenstretcher proxy start
QUESTIONS FROM ENGINEERING LEADERS

FAQ

What exactly are "tokens" and why do they cost so much?
Tokens are the units AI models use to read your prompt and write output (roughly ¾ of a word). Every call to GPT-4, Claude, etc. is billed per token. Complex agent work can easily use 50k–200k+ tokens per task.
How is this not just another wrapper that adds cost?
It delivers measurably better results at lower cost on complex work. The technical approach and data are in the whitepaper. Real customer runs show 30-60% net savings.
Is this safe for a team? Can it run away with my budget?
No. It is prepaid only. You load a wallet. It checks balance before every step and stops gracefully. You also get a full log + savings report after each job. Local mode lets you use your own keys with hard caps.
Who is this for?
Anyone doing complex, multi-step work (new features, refactors, full systems) — not simple questions or one-liners. Teams benefit most when someone with decision-making power can say "yes" to adopting a new tool. Great for engineering managers, CTOs, and program leads at growing companies.
Do I need to change how my team works?
Minimal change. Use the CLI or call from Python/Cursor/Claude. Your agents get a prompt that tells them when to delegate big work. Small tasks stay direct.
Where is the proof this actually saves tokens?
Every completed job prints a savings summary. We publish aggregate benchmarks on the docs site. Full technical whitepaper + methodology is available below.
FOR TEAMS & PRODUCTION

Prepay. Stay in control.
No surprise bills ever.

Perfect for managers who need predictable AI spend. Lemon Squeezy checkout launching soon. Use local mode today with your own keys at zero extra cost.

Team wallets • Real-time budget enforcement • Exportable reports for finance
Or start with free plan-only previews →
OUR MISSION

AI should accelerate teams,
not bankrupt them.

We built TokenStretcher after watching teams burn serious budget on AI agent work that still needed heavy cleanup. The goal: make complex AI tasks reliably cheaper and higher quality, without requiring you to become an LLM optimization expert.
Read the technical whitepaper →
Full methodology, benchmarks, and real before/after traces. (Also printable as PDF from browser.)
THE TEAM
Bradley — Founder
12 years in machine learning ranging from genetic sequencing and prediction to machine vision with the US olympics development committee.
Small team of engineers
Focused on making advanced AI tooling practical and safe for real product teams.
Fully bootstrapped. No VC pressure to "grow usage at all costs." Prepaid model is intentional.
✓ Open source core on PyPI
✓ Every run produces auditable savings report
✓ Prepaid + local mode = you control the keys and the spend
✓ No telemetry unless you opt in