Sugar

Autonomous issue resolution for AI-assisted development.

Security scanners find vulnerabilities. Dependabot opens issues. Copilot flags problems. Sugar reads the issue, writes the fix, runs the tests, and opens the PR.

• Discovers - watches your GitHub repo for labeled issues (security, bug, dependabot)
• Resolves - reads each issue and implements a fix using Claude
• Verifies - runs your test suite and quality gates before committing
• Ships - opens a PR referencing the original issue, ready for your review

No issue left sitting in a backlog waiting for someone to have time.

How Sugar Compares

Most AI dev tools stop at the discovery layer:

GitHub Copilot CLI  ->  scan  ->  open issues
Snyk                ->  scan  ->  open issues
Dependabot          ->  scan  ->  open issues

Sugar is the resolution layer:

Labeled issue appears on GitHub
  -> Sugar picks it up (label filter: "security", "dependabot", "bug")
  -> AI agent reads the issue, analyzes the affected code
  -> Fix implemented, tests run locally
  -> PR opened - you review and merge

Configure which labels Sugar watches, point it at your repo, and run sugar run.

See workflow examples for security auto-fix, bug triage, test coverage, and more.

What Sugar Does

Sugar combines persistent memory with autonomous task execution:

• Project memory - Decisions, preferences, error patterns, and research stored per-project
• Global memory - Standards and guidelines shared across every project you work on
• GitHub integration - Watches for labeled issues and resolves them autonomously
• Semantic search - Retrieve relevant context by meaning, not just keywords
• MCP integration - Your AI agent reads and writes memory directly during sessions
• Task queue - Hand off work to run autonomously, powered by the same memory layer

Quick Start

# Install once, use in any project
pipx install sugarai

# Initialize in your project
cd ~/dev/my-app
sugar init

# Store what you know
sugar remember "We use async/await everywhere, never callbacks" --type preference
sugar remember "JWT tokens use RS256, expire in 15 min - see auth/tokens.py" --type decision
sugar remember "When tests fail with import errors, check __init__.py exports first" --type error_pattern

# Retrieve it later
sugar recall "authentication"
sugar recall "how do we handle async"

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 mcp add sugar -- sugar mcp memory

Claude Code - Task server (optional):

claude mcp add sugar-tasks -- sugar mcp tasks

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):

# Goose
goose configure
# Select "Add Extension" -> "Command-line Extension"
# Name: sugar
# Command: sugar mcp memory

# OpenCode - one command setup
sugar opencode setup

Global Memory (New in 3.9)

Some knowledge belongs to you, not just one project. Coding standards, preferred patterns, security practices - these should follow you everywhere.

# Store a guideline that applies to all your projects
sugar remember "Always validate and sanitize user input before any DB query" \
  --type guideline --global

sugar remember "Use conventional commits: feat/fix/chore/docs/test" \
  --type guideline --global

# View your global guidelines
sugar recall "security" --global
sugar memories --global

# Search works project-first, but guidelines always surface
sugar recall "database queries"
# Return

... [View full README on GitHub](https://github.com/roboticforce/sugar#readme)