Local Memory Server Slashes AI Coding Context Costs by 86%

AI coding assistants lose session context on every restart, forcing developers to re-explain their work repeatedly. sessionmem solves this by auto-injecting compressed session summaries while reducing token consumption by 85.6%, cutting both costs and context-loading friction. Built as a local-first MCP server using SQLite, it works offline with zero cloud dependencies and integrates seamlessly with Claude Code, Cursor, Cline, and other AI coding tools.