Sugar gives AI coding agents a persistent, cross-project memory via MCP. Most agents start every session knowing nothing about your codebase, your preferences, or decisions you made last week. Sugar gives them a memory that survives sessions, survives switching tools, and survives switching projects. It stores typed memories: decisions, preferences, file context, error patterns, research notes, outcomes, and guidelines. When your agent starts a session, it can pull relevant context from ~/.sugar/memory.db - shared across all your projects. Switch from Claude Code to Goose mid-week? Same memory. Tech: Python, SQLite + FTS5, sentence-transformers for vector search with FTS5/LIKE fallback. No server. No Docker. No cloud account. AGPL-3.0. GitHub: https://github.com/roboticforce/sugar Happy to answer questions about what works, what doesn't, and where it's rough around the edges. |