sugar
Persistent memory for AI coding agents. Local-first, cross-session context, global knowledge, and optional autonomous task execution.
No outside reports on file
sugar is distributed via PyPI (sugarai); review its source code, dependencies, and requested permissions before use.
Based on public adoption and transparency signals as of Oct 19, 2026. Our opinion, not a code audit or security guarantee.
What it can access
- Local filesNo local folder access notedLOW
- Command executionRuns shell or system commandsREVIEW
- Network reachConnects to outside service APINOTED
- CredentialsNo API token requiredLOW
- Package sourcePyPI (sugarai)PUBLIC
Inferred from this listing’s public package details and description. Check the project’s source before installing.
Install
uvx sugaraiAbout Sugar
Sugar is an MCP server focused on Memory & knowledge: Persistent memory for AI coding agents. Local-first, cross-session context, global knowledge, and optional autonomous task execution.
It is published on PyPI as sugarai and hosted on GitHub at roboticforce/sugar (98 GitHub stars). Based on its public metadata, it operates with standard local or API scope without broad shell execution flags noted.
Setup
Check these steps against the project’s own instructions before running anything.
Run the PyPI package sugarai in an isolated environment:
uvx sugarai
See https://github.com/roboticforce/sugar (opens external site) for required environment variables.
Why this grade
Signal-based grade (2/7 points): public source code. This reflects adoption and transparency, not a code review.
Popularity and upkeep
- GitHub stars
- 99
- Listing last refreshed
- 2026-10-29
These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.
Security reports
No reports found for this package in our research (last checked 2026-10-29).
Risks to watch for
- Dependency & version pinning: Distributed via PyPI (sugarai). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.
How to lower the risk
Least-privilege permissions
- Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
- Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.
Network isolation
- Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
- If your IT team can, limit which websites and services it is allowed to contact.
Monitoring
- Check its activity history or logs weekly at first, and look at what it changed or sent.
- Turn on alerts for new logins or unusual usage on any account it connects to.
Red flags to watch for
- It asks for more access than its job requires, or prompts you to paste passwords.
- It suddenly updates with new owners, or starts contacting unfamiliar websites.
Questions
How do I install Sugar?
Run uvx sugarai (or pip install sugarai) in your terminal, or add the server entry to your claude_desktop_config.json or .cursor/mcp.json as shown in the Setup section on this page. Full setup docs and environment variables are in github.com/roboticforce/sugar.
Are there security reports about Sugar?
No reports found for this package in our research (last checked 2026-10-29). Sugar currently holds Grade C (Moderate risk signals) based on public adoption and transparency signals. Key risk areas to watch include dependency & version pinning:.
Is Sugar actively maintained?
Sugar has 99 GitHub stars. Our directory data was last refreshed on 2026-10-29. Check recent commit activity, release tags, and open issues at github.com/roboticforce/sugar before pinning it in production.
What are alternatives to Sugar?
You can compare Sugar side by side with other Memory MCP servers in the Related tools section on this page, or use the Compare tool on AgentArmorHQ.
Key facts
- Type
- App connector
- Publisher
- roboticforce
- Source code
- github.com/roboticforce/sugar
- Install command
- pip install sugarai
- Est. context load
- ~550 tokens / turn (~3 tool schemas, 0.27% of 200k context)
- Popularity
- 99 GitHub stars
- Last updated
- 2026-10-29
- Last graded
- 2026-10-19
Community
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