Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Autonomous AI development system with persistent task queue and background execution
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
ANTHROPIC_API_KEY, GITHUB_TOKEN, SUGAR_DEFAULT_REPOYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"sugar": {
"command": "uvx",
"args": [
"sugarai",
"mcp",
"serve"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"GITHUB_TOKEN": "your-value",
"SUGAR_DEFAULT_REPO": "your-value"
}
}
}
}Run this in your terminal
claude mcp add sugar --env ANTHROPIC_API_KEY=your-value --env GITHUB_TOKEN=your-value --env SUGAR_DEFAULT_REPO=your-value -- uvx sugarai mcp serveFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"sugar": {
"command": "uvx",
"args": [
"sugarai",
"mcp",
"serve"
],
"env": {
"ANTHROPIC_API_KEY": "your-value",
"GITHUB_TOKEN": "your-value",
"SUGAR_DEFAULT_REPO": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"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"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
ANTHROPIC_API_KEY envGITHUB_TOKEN envSUGAR_DEFAULT_REPO envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The publisher (cdnsteve) is not the repo owner (roboticforce); someone else may have listed it
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 0 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (3.4.2) reached the registry 10 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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 htOnly the beginning is shown; read the rest in the repo