If you use Claude Code, Cursor, or any AI coding tool, you're probably burning tokens on the same files over and over. Every session, the AI re-reads your codebase from scratch.

I built Code Context Engine (CCE) to fix this. It indexes your code locally and lets the AI search instead of reading entire files. The result: 94% fewer input tokens , benchmarked on FastAPI with 20 real coding queries.

The Problem

Input tokens are 85-95% of your Claude Code bill. Every time you ask Claude about your payment flow, it reads payments.py , shipping.py , and whatever else it thinks might be relevant. That's 45,000 tokens for a question that needs 800 tokens of context.

Without CCE: Claude reads payments.py + shipping.py = 45,000 tokens With CCE: context_search "payment flow" = 800 tokens

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How It Works

CCE runs as a local MCP server.…