Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.

Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.

Control what your AI can see. LeanCTX (Lean Context) is the context intelligence layer for AI agents — one local Rust binary that decides what they read, remembers what they learn, guards what they touch, and proves what they save. 60–90% fewer tokens as the receipt. 76 MCP tools, 30+ agents, local-first.

MCP server that lets Claude Code delegate heavy-token tasks to DeepSeek, Kimi, GLM, Qwen, Grok, or any OpenAI-compatible model. Claude orchestrates; the delegate does the heavy lifting. Zero dependencies.