Vektor Memory

VEKTOR - Vector Memory & Agentic AI Memory for Autonomous Agents | Local-First MCP Server

Your agents forget everything the moment a session ends. VEKTOR fixes that with a persistent vector memory graph that survives resets, restarts, and context limits — no cloud, no re-explaining, no lost work.

Built on the MAGMA graph architecture (semantic, causal, temporal, and entity layers) and benchmarked on LongMemEval, VEKTOR runs locally with 8ms average recall and zero embedding cost. It plugs into Claude, Cursor, Windsurf, and any MCP-compatible tool in minutes.

This channel covers how it works, what the research shows, and how to wire it into your own agent stack.

🔗 vektormemory.com · npm: vektor-slipstream · Open source tools: Vex, Vek-Sync, Via, Provenance

📄 Research: LongMemEval benchmark results and technical writeups at vektormemory.com/research

Your agents should remember everything. Now they can.