roboticforce/sugar

Persistent memory for AI coding agents.
Your AI agent starts every session with amnesia. The architecture decisions, conventions,
and gotchas you explained last week are gone. Sugar is the local-first memory layer that
remembers them for you - per project, across projects, on your machine.
Your memory. Your machine. Your data.
What Sugar Does
Sugar is a memory layer your AI coding agent can read and write directly:
- **Project memory** - Decisions, preferences, error patterns, and research stored per-project
- **Global memory** - Standards and guidelines shared across every project you work on
- **Semantic search** - Retrieve relevant context by meaning, not just keywords
- **MCP integration** - Your AI agent reads and writes memory directly during sessions
- **Local-first** - SQLite on your disk, no API keys, fully offline-capable
- **Task queue** - Optional autonomous execution, powered by the same memory layer
Quick Start
Your AI agent can also read and write memory directly - no copy-pasting required.
MCP Integration
Connect Sugar's memory to your AI agent so it can access project context automatically.
**Claude Code - Memory server (primary):**
**Claude Code - Task server (optional):**
Once connected, Claude can call store_learning to save context mid-session and search_memories to pull relevant knowledge before starting work. The memory server works from any directory - global memory is always available even outside a Sugar project.
**Other MCP clients (Goose, Claude Desktop):**
Skills
Sugar ships Agent Skills - folders of instructions that teach coding agents to apply Sugar's methodology. Skills live under skills/ and follow the Agent Skills specification (a SKILL.md with name/description frontmatter plus instructions).
| Skill | What it does |
|-------|--------------|
| sugar-memory | Store and surface project context via Sugar's memory MCP server: recall context at task start, search before deciding, store learnings after completing work |
| sugar-task-planner | Turn a high-level task into a detailed execution plan: subtasks, dependencies, time estimates, risks, and measurable success criteria |
| sugar-quality-guardian | Review code across quality, testing, security, and performance, ending with a structured verdict |
| sugar-orchestrator | Coordinate multi-step workflows: analyze complexity, decompose tasks, assign roles, monitor execution |
Each skill includes an evaluation dataset (evals/evals.json) and is measured with NVIDIA SkillEvaluator against the OpenCode harness. See Skill Benchmarks for the Skill Lift results - sugar-memory and sugar-task-planner both show measured positive lift.
Global Memory
Some knowledge belongs to you, not just one project. Coding standards, preferred patterns, security practices - these should follow you everywhere.
Global memory lives at ~/.sugar/memory.db. Project memory lives at .sugar/memory.db. When you search, project context wins - but guideline type memories from global always appear in results so your standards stay visible.
**Via MCP**, pass scope: "global" to store_learning to save cross-project knowledge directly from your AI session.
**Memory types:** decision, preference, file_context, error_pattern, research, outcome, guideline
Full docs: Memory System Guide
How Memory Works
Sugar uses two SQLite databases and a tiered search strategy.
**Two stores:**
- **Project store** (.sugar/memory.db) - context specific to one project
- **Global store** (~/.sugar/memory.db) - knowledge that applies everywhere