Architecting Privacy-Preserving Long-Term Memory for Autonomous AI Agents via MCP

This guide addresses the statelessness problem in autonomous AI agents by architecting a privacy-preserving long-term memory layer using the Model Context Protocol (MCP). It details a full stack including an MCP memory server, encrypted vector store (Qdrant/Milvus), and a PII-scrubbing privacy proxy. Production considerations such as context fragmentation, mTLS security, and race conditions are also discussed.