What is Decent Sampler Drums?

39/100
Trust Score (E)
🔴 Avoid

Decent Sampler Drums is a AI tool that Integrates with DecentSampler to generate drum kit configurations by analyzing WAV samples and creating XML-based presets with velocity layers and muting groups.. It has a Nerq Trust Score of 39/100 (E). 0 GitHub stars. Published by https://github.com/dandeliongold/mcp-decent-sampler-drums. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

39
TRUST SCORE
E
GRADE
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STARS
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DOWNLOADS

What Decent Sampler Drums Does

Decent Sampler Drums is a mcp_server in the AI tool category. Integrates with DecentSampler to generate drum kit configurations by analyzing WAV samples and creating XML-based presets with velocity layers and muting groups.. It is published by https://github.com/dandeliongold/mcp-decent-sampler-drums and has no specified license. With 0 GitHub stars and 0 downloads, it has a small community of users and contributors.

Who Should Use Decent Sampler Drums

Decent Sampler Drums is recommended only for experimental use. Consider alternatives with higher trust scores for production systems.

Details

Authorhttps://github.com/dandeliongold/mcp-decent-sampler-drums
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=decent-sampler-drums

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

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Frequently Asked Questions

What is Decent Sampler Drums used for?
Decent Sampler Drums is a AI tool tool. Integrates with DecentSampler to generate drum kit configurations by analyzing WAV samples and creating XML-based presets with velocity layers and muting groups..
Is Decent Sampler Drums free?
License: Check project page. Decent Sampler Drums has 0 GitHub stars.
Is Decent Sampler Drums safe?
Decent Sampler Drums has a Nerq Trust Score of 39/100 (E). Evaluate carefully.
What are alternatives to Decent Sampler Drums?
Top alternatives: MarkItDown, Fetch, Time. See full comparison.

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

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