What is Apple Reminders?

42/100
Trust Score (E)
⚠️ Use Caution

Apple Reminders is a AI tool that Integrates with Apple's Reminders app to create, read, and manage tasks with specified parameters like titles, notes, due dates, and priority levels. It has a Nerq Trust Score of 42/100 (E). 15 GitHub stars. Published by https://github.com/chenningling/mcp-applereminders. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

42
TRUST SCORE
E
GRADE
15
STARS
0
DOWNLOADS

What Apple Reminders Does

Apple Reminders is a mcp_server in the AI tool category. Integrates with Apple's Reminders app to create, read, and manage tasks with specified parameters like titles, notes, due dates, and priority levels. It is published by https://github.com/chenningling/mcp-applereminders and has no specified license. With 15 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use Apple Reminders

Apple Reminders is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

Authorhttps://github.com/chenningling/mcp-applereminders
CategoryAI tool
LicenseNot specified
Typemcp_server
SourceView on GitHub
Security Score0/100
Activity Score0/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=apple-reminders

Setup guide · Full safety report · Production review · Is it safe?

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Frequently Asked Questions

What is Apple Reminders used for?
Apple Reminders is a AI tool tool. Integrates with Apple's Reminders app to create, read, and manage tasks with specified parameters like titles, notes, due dates, and priority levels.
Is Apple Reminders free?
License: Check project page. Apple Reminders has 15 GitHub stars.
Is Apple Reminders safe?
Apple Reminders has a Nerq Trust Score of 42/100 (E). Evaluate carefully.
What are alternatives to Apple Reminders?
Top alternatives: MarkItDown, Sequential Thinking, Filesystem. See full comparison.

Last updated September 2026. Trust scores based on automated analysis of public data.

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