Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
제작자가 쓴 설명(영어 원문)
Autonomous AI development system with persistent task queue and background execution
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
ANTHROPIC_API_KEY, GITHUB_TOKEN, SUGAR_DEFAULT_REPO필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"sugar": {
"command": "uvx",
"args": [
"sugarai",
"mcp",
"serve"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"GITHUB_TOKEN": "your-value",
"SUGAR_DEFAULT_REPO": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add sugar --env ANTHROPIC_API_KEY=your-value --env GITHUB_TOKEN=your-value --env SUGAR_DEFAULT_REPO=your-value -- uvx sugarai mcp serve실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"sugar": {
"command": "uvx",
"args": [
"sugarai",
"mcp",
"serve"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"GITHUB_TOKEN": "your-value",
"SUGAR_DEFAULT_REPO": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"sugar": {
"type": "stdio",
"command": "uvx",
"args": [
"sugarai",
"mcp",
"serve"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"GITHUB_TOKEN": "your-value",
"SUGAR_DEFAULT_REPO": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
ANTHROPIC_API_KEY envGITHUB_TOKEN envSUGAR_DEFAULT_REPO env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
게시자(cdnsteve)가 저장소 소유자(roboticforce)가 아니에요. 다른 사람이 등록했을 수 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 0개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(3.4.2)은 10개월 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Agent-Native Google Calendar - manage events, sync, and public booking
Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
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.
Sugar is a memory layer your AI coding agent can read and write directly:
# Install once, use in any project
pipx install sugarai
cd ~/dev/my-app sugar init
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
sugar recall "authentication" sugar recall "how do we handle async"
Your AI agent can also read and write memory directly - no copy-pasting required.
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
sugar opencode setup
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.
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
sugar recall "security" --global sugar memories --global
sugar recall "database queries"
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
Sugar uses two SQLite databases and a tiered search strategy.
Two stores:
.sugar/memory.db) - context specific to one project~/.sugar/memory.db) - knowledge that applies everywhereSeven memory types, each with different retrieval behavior:
| Type | Purpose | TTL |
|---|---|---|
decision | Architecture and implementation choices | Never |
preference | How you like things done | Never |
file_context | What files and modules do | Never |
error_pattern | Bugs and their fixes | 90 days |
research | API docs, library findings | 60 days |
outcome | What worked, what didn't | 30 days |
guideline | Cross-project standards and best practices | Never |
Search strategy - project-first with reserved guideline slots:
This means a mature project's local context dominates results. A new project with no local memory gets global knowledge automatically. And your guidelines are always visible regardless.
Search engine: Semantic search via sentence-transformers (all-MiniLM-L6-v2, 384-dim vectors) with sqlite-vec. Falls back to SQLite FTS5 keyword search, then LIKE queries. No external API calls - everything runs locally.
# Install with semantic search (recommended)
pipx install 'sugarai[memory]'
pipx install sugarai
MCP tools available to your AI agent:
| Tool | What it does |
|---|---|
search_memory | Search both stores, returns results with scope labels |
store_learning | Save a memory (pass scope: "global" for cross-project) |
recall | Get formatted markdown context for a topic |
get_project_context | Full project summary including global guidelines |
list_recent_memories | Browse recent memories by type |
MCP resources:
sugar://project/context - project summarysugar://preferences - coding preferencessugar://global/guidelines - cross-project standardsThe task queue lets you hand off work and let it run autonomously. It reads from the same memory store, so Sugar already knows your preferences and patterns before it starts.
# Add tasks
sugar add "Fix authentication timeout" --type bug_fix --urgent sugar add "Add user profile settings" --type feature
sugar run
Sugar picks up tasks, executes them with your configured AI agent, runs tests, commits working code, and moves to the next task. It runs until the queue is empty or you stop it.
Delegate from Claude Code mid-session:
/sugar-task "Fix login timeout" --type bug_fix --urgent
Advanced task options: New in 3.10: Task Orchestration decomposes large features into a 4-stage workflow (research, plan, implement, review) with specialist agent routing and dependency-ordered sub-tasks.
# Orchestrated execution - 4-stage workflow (New in 3.10)
sugar add "Add OAuth authentication" --type feature --orchestrate
sugar add "Implement rate limiting" --ralph --max-iterations 10
sugar list sugar status
Full docs: Task Orchestration
Because Sugar remembers your codebase and conventions, it can also resolve routine issues autonomously. Point it at a GitHub repo, configure which labels to act on (security, bug, dependabot), and Sugar will read each issue, implement the fix, run your tests, and open a PR.
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
This is one application of the memory layer, not the headline. Use Sugar purely as memory, or enable resolution - your choice. See workflow examples for security auto-fix, bug triage, test coverage, and more.
Works with any CLI-based AI coding agent:
| Agent | Memory MCP | Task MCP | Notes |
|---|---|---|---|
| Claude Code | Yes | Yes | Full support |
| OpenCode | Yes | Yes | sugar opencode setup |
| Goose | Yes | Yes | Via MCP |
| Aider | Via CLI | Via CLI | Manual recall |
Recommended: pipx - installs once, available everywhere, no venv conflicts:
pipx install sugarai
Upgrade / Uninstall:
pipx upgrade sugarai
pipx uninstall sugarai
Other installation methods
pip (requires venv activation each session)
pip install sugarai
uv
uv pip install sugarai
With semantic search (recommended for memory):
pipx install 'sugarai[memory]'
With GitHub integration:
pipx install 'sugarai[github]'
All features:
pipx install 'sugarai[all]'
Sugar is project-local by default. Each project gets its own .sugar/ folder with its own database and config. Global memory lives at ~/.sugar/. Like git - one installation, per-project state.
~/.sugar/
└── memory.db # Global memory (guidelines, cross-project knowledge)
~/dev/my-app/ ├── .sugar/ │ ├── sugar.db # Project memory + task queue │ ├── config.yaml # Project settings │ └── prompts/ # Custom agent prompts └── src/
Recommended .gitignore:
.sugar/sugar.db
.sugar/sugar.log .sugar/*.db-*
Commit .sugar/config.yaml and .sugar/prompts/ to share settings with your team.
.sugar/config.yaml is created on sugar init:
sugar:
dry_run: false loop_interval: 300 max_concurrent_work: 3
claude: enable_agents: true
discovery: github: enabled: true repo: "user/repository"
Contributions welcome. See CONTRIBUTING.md.
git clone ht앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요