How To Make Your Clients More Context-Aware With OpenMemory MCP

OpenMemory MCP is presented as a self-hosted, local-first persistent memory layer for MCP-compatible AI clients such as Cursor, Claude Desktop, Windsurf, and Cline, designed to preserve context across sessions while keeping data under user control. Built on Mem0, it stores semantically indexed memories in Qdrant and relational metadata, categories, audit logs, and access controls in Postgres or SQLite, exposing memory operations such as adding, searching, listing, and deleting through an MCP server over Server-Sent Events. The system includes a FastAPI backend, Docker-based deployment, a Next.js dashboard for viewing and managing memories and connected applications, and per-memory or per-app controls that allow memories to be paused, archived, deleted, or restricted. Setup requires Docker, Python, Node.js, GNU Make, and an OpenAI API key, after which users can connect supported clients through a generated SSE endpoint. While data is intended to remain local and interactions are logged for traceability, authentication must be supplied through an external gateway and default open CORS settings should be tightened for production. Suggested applications include multi-agent research systems, meeting assistants that track action items, and coding assistants that recall prior errors, fixes, preferences, and project-specific context.

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