How do I reduce my Claude API bill?

Install Entroly (pip install entroly), run 'entroly go' in your project, and restart your AI tool. Entroly compresses your context 79–99.5% before it reaches Claude, directly cutting your token costs. It also aligns prompts for KV-cache discounts (up to 90% off cached tokens).

What is the cheapest way to use Claude for coding?

Use a context compression proxy like Entroly between your coding tool and Claude. It selects only the relevant code fragments, compresses context 79–99.5%, and aligns prompts for cache discounts. Combined savings: 80–97% reduction in effective token cost.

Does prompt compression affect Claude's output quality?

Well-implemented compression improves quality. LLMs suffer from 'lost in the middle' attention degradation. Entroly selects only the most relevant code fragments using information theory, so Claude sees less noise and produces more accurate outputs. Entroly also includes WITNESS, a $0 hallucination guard that verifies outputs.

How to Cut Claude API Input Tokens by 79–99.5% ($0 tool)

If you're using Cursor, Claude Code, Windsurf, or Cline for AI-assisted coding, most of what you send the model on each request is context the model did not need. Here's how to cut that — in under 2 minutes, with zero code changes.

Evidence boundary: 79–99.5% is input-token reduction from committed benchmark artifacts (NeedleInAHaystack 99.5%, LongBench HotpotQA 85.3%, Berkeley Function Calling 79.3% — all at 100% answer retention; raw results). The worst case in that set is SQuAD 2.0 at 43.8% with 90% retention, on 233-token single-paragraph inputs where there is little redundancy to remove. Dollar figures below are illustrative arithmetic at published list pricing, not measured invoices — token cuts become cost cuts only on metered API routes, not on fixed-price subscriptions. Run entroly simulate for your own numbers, offline.

Before Entroly

$487/mo

~162K tokens × 50 requests/day × 20 days

After Entroly

$49/mo

90% reduction via compression + cache alignment

The Problem: AI Coding Tools Are Token Hogs

Every time you ask Cursor or Claude Code a question, it sends your entire visible context to the API — open files, recent edits, terminal output, and more. On a medium codebase (50K+ lines), that's 80,000–200,000 tokens per request.

At Claude Sonnet 4 pricing ($3/MTok input, $15/MTok output):

Usage Pattern	Tokens/Request	Requests/Day	Monthly Cost
Light (small project)	~40K	20	~$72
Medium (typical team)	~120K	40	~$432
Heavy (monorepo)	~200K	60+	~$1,080+

The Solution: 3 Steps, 2 Minutes

Install Entroly

pip install entroly

Works on macOS, Linux, and Windows. No GPU required.

Initialize in Your Repo

cd /path/to/your/project
entroly go

This auto-detects your AI tools (Cursor, Claude Code, etc.) and configures Entroly as an MCP server. It indexes your codebase in seconds.

Restart Your AI Tool

That's it. Entroly now runs as a background MCP server, automatically compressing context 79–99.5% before it reaches the API. Your AI tool works exactly the same — it just costs 79–99.5% less.

How It Works (3 Layers of Savings)

Layer 1: Context Compression (79–99.5% token reduction)

Entroly uses information-theoretic selection to pick only the code fragments that matter for your current query. Instead of sending your entire codebase, it sends the mathematically optimal subset using 0/1 Knapsack optimization, Shannon entropy scoring, and BM25 relevance ranking.

Layer 2: KV-Cache Alignment (50–90% off cached tokens)

Anthropic and OpenAI give automatic discounts when the prefix of your prompt matches a previous request. Entroly's Cache Aligner reorders prompt sections to maximize prefix stability between requests, triggering these discounts on every call.

Layer 3: Model Routing (80–95% off simple queries)

Not every question needs Claude Opus. Entroly's Epistemic Router analyzes query complexity and can route simple lookups to cheaper models (Haiku, GPT-4o-mini) while reserving expensive models for complex reasoning tasks.

FAQ

How much does Claude API cost per month for coding?

A typical Claude API user doing 50+ AI coding requests per day spends $250–$600/month. Each request can send 80,000–200,000 tokens at $3/MTok (Sonnet 4). Heavy monorepo users can exceed $1,000/month. Context compression with Entroly reduces this to $25–$60/month.

Does this work with Cursor Pro / Claude Code subscriptions?

Yes. Even with subscription plans, you hit rate limits faster when sending more tokens. Entroly reduces tokens per request, so you get more requests within your plan limits. For API-mode users (Cursor's "bring your own key"), the savings are direct and measurable.

Will compression make my AI coding worse?

No — it typically makes it better. LLMs suffer from "lost in the middle" attention degradation when context windows are stuffed with irrelevant code. Entroly selects only the relevant fragments, improving the signal-to-noise ratio. Plus, WITNESS checks responses against the supplied evidence on the routes where it is enabled, flagging unsupported claims before they enter your code.

Is this free?

Yes. Entroly is open-source under the Apache 2.0 license. No API keys, no accounts, no telemetry. Everything runs locally on your machine.

How does this compare to Cursor's built-in context management?

Cursor includes basic context selection (recently opened files, @-mentions), but it doesn't do knapsack-optimal selection, entropy scoring, cache alignment, or hallucination verification. Entroly adds all of these as an MCP server layer — it works alongside Cursor's built-in features, not instead of them.

Start Saving in 30 Seconds

No config. No API key. No signup. Just install and go.

pip install entroly && cd /your/repo && entroly go

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