v0.0.1 · MIT
Context-Engine MCP - Agentic Context Compression Suite
v5.7.0 · MIT
Measure token savings per AI coding agent, optimize context, and share a live local knowledge graph across 16 CLI clients.
— · Apache-2.0
vMLX - JANGTQ Uber Compressed MLX Models - L2 Disk Cache (survives restart) + L1 Paged (super fast ttft) + Hybrid SSM Scheduler + Cont Batching + etc!
— · no license
A long-term memory system built for AI Agents. Agent wakes up already knowing who he is, not querying "who am I?" every session. Every turn calling back accurate memory context. Achieving accurate memory hits while also preventing memory from expanding at scale. No compression, no forgetting.