Summary

Adds Entroly to the Development & Code Tools section of the README.

What it solves

AI coding agents spend a large share of context on repeated file reads and redundant codebase searches. Entroly is a context optimization engine that addresses this with semantic caching, SimHash deduplication, and submodular knapsack optimization so agents stay within context limits without losing task-relevant detail.

Who it is for

Developers using Claude Code, Cursor, GitHub Copilot, and other agent setups that speak MCP.

Links

• Repository: https://github.com/juyterman1000/entroly
• License: Apache-2.0