Hybrid Context Optimizer β Shell Hook + MCP Server. Reduces LLM token consumption by 89-99%. Single Rust binary, zero dependencies.
Config is the same across clients β only the file and path differ.
{
"mcpServers": {
"lean-ctx": {
"command": "lean-ctx"
}
}
}Are you the author?
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LeanCTX β Lean Context Engineering for AI agents
LeanCTX β short for Lean Context β is the context engineering layer for AI agents. It runs as a single local binary between your agents and everything they touch β your code, shell, data, and the model itself: it decides what they read, compresses what they send (an optional local proxy shrinks every request β system prompt, history and tool results β prompt-cache-safe), remembers what they learn, guards what they touch β and proves what they save with a signed, verifiable savings ledger. The result: 60β90% fewer tokens. Zero config required. Local-first.
| Problem | With LeanCTX |
|---|---|
| Repeated file reads: ~2000 tokens each | Cached re-reads: ~13 tokens |
Raw git status: ~800 tokens | Compressed: ~120 tokens |
| Every turn re-sends the whole history | Proxy compresses each request, prompt-cache-safe |
| Context resets every chat | Session memory persists across chats |
| No visibility into context usage | Real-time dashboard + budget control |
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