What is SAGE Universal AI Assistant?

45/100
Trust Score (E)
⚠️ Use Caution

SAGE Universal AI Assistant is a AI assistant that Universal development assistant that automatically selects optimal AI models based on task complexity.. It has a Nerq Trust Score of 45/100 (E). 12 GitHub stars. Published by https://github.com/david-strejc/sage-mcp. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

45
TRUST SCORE
E
GRADE
12
STARS
0
DOWNLOADS

What SAGE Universal AI Assistant Does

SAGE Universal AI Assistant is a mcp_server in the AI assistant category. Universal development assistant that automatically selects optimal AI models based on task complexity.. It is published by https://github.com/david-strejc/sage-mcp and has no specified license. With 12 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use SAGE Universal AI Assistant

SAGE Universal AI Assistant is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

Authorhttps://github.com/david-strejc/sage-mcp
CategoryAI assistant
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=sage-universal-ai-assistant

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

Safer Alternatives

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Frequently Asked Questions

What is SAGE Universal AI Assistant used for?
SAGE Universal AI Assistant is a AI assistant tool. Universal development assistant that automatically selects optimal AI models based on task complexity..
Is SAGE Universal AI Assistant free?
License: Check project page. SAGE Universal AI Assistant has 12 GitHub stars.
Is SAGE Universal AI Assistant safe?
SAGE Universal AI Assistant has a Nerq Trust Score of 45/100 (E). Evaluate carefully.
What are alternatives to SAGE Universal AI Assistant?
Top alternatives: Captain Dackie, HuggingGPT, aya-101. See full comparison.

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

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