What is mcn-components?

48/100
Trust Score (D)
⚠️ Use Caution

mcn-components is a npm that MCN Components is a collection of reusable React components designed to help developers build consistent and accessible user interfaces quickly. Each component is highly customizable and typed with Ty. It has a Nerq Trust Score of 48/100 (D). 0 GitHub stars. Published by laskailir. Last analyzed August 2026.

Why This Score

Trust & Safety Overview

48
TRUST SCORE
D
GRADE
0
STARS
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DOWNLOADS

What mcn-components Does

mcn-components is a npm in the npm category. MCN Components is a collection of reusable React components designed to help developers build consistent and accessible user interfaces quickly. Each component is highly customizable and typed with TypeScript for a better developer experience. The library. It is published by laskailir and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use mcn-components

mcn-components is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

Authorlaskailir
Categorynpm
LicenseNot specified
Typenpm
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=mcn-components

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

Frequently Asked Questions

What is mcn-components used for?
mcn-components is a npm tool. MCN Components is a collection of reusable React components designed to help developers build consistent and accessible user interfaces quickly. Each component is highly customizable and typed with Ty.
Is mcn-components free?
License: Check project page. mcn-components has 0 GitHub stars.
Is mcn-components safe?
mcn-components has a Nerq Trust Score of 48/100 (D). Evaluate carefully.
What are alternatives to mcn-components?
Top alternatives: . See full comparison.

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

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