What is StarRocks?

46/100
Trust Score (D)
⚠️ Use Caution

StarRocks is a AI tool that Integrates with StarRocks databases to enable efficient data querying and manipulation through customizable connection settings and support for both read and write operations.. It has a Nerq Trust Score of 46/100 (D). 150 GitHub stars. Published by https://github.com/hagsmand/mcp-server-starrocks. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

46
TRUST SCORE
D
GRADE
150
STARS
0
DOWNLOADS

What StarRocks Does

StarRocks is a mcp_server in the AI tool category. Integrates with StarRocks databases to enable efficient data querying and manipulation through customizable connection settings and support for both read and write operations.. It is published by https://github.com/hagsmand/mcp-server-starrocks and has no specified license. With 150 GitHub stars and 0 downloads, it has a growing community of users and contributors.

Who Should Use StarRocks

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

Details

Authorhttps://github.com/hagsmand/mcp-server-starrocks
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=starrocks

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

Safer Alternatives

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MarkItDown4292.8K
Filesystem5089.4K
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Frequently Asked Questions

What is StarRocks used for?
StarRocks is a AI tool tool. Integrates with StarRocks databases to enable efficient data querying and manipulation through customizable connection settings and support for both read and write operations..
Is StarRocks free?
License: Check project page. StarRocks has 150 GitHub stars.
Is StarRocks safe?
StarRocks has a Nerq Trust Score of 46/100 (D). Evaluate carefully.
What are alternatives to StarRocks?
Top alternatives: MarkItDown, Filesystem, Time. See full comparison.

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

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