What is RAGLight?

58/100
Trust Score (D)
⚠️ Use Caution

RAGLight is a infrastructure that RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connec. It has a Nerq Trust Score of 58/100 (D). 638 GitHub stars. Published by Unknown. Last analyzed September 2026.

Why This Score

Trust & Safety Overview

58
TRUST SCORE
D
GRADE
638
STARS
0
DOWNLOADS

What RAGLight Does

RAGLight is a agent in the infrastructure category. RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.. It is published by an independent developer and has no specified license. With 638 GitHub stars and 0 downloads, it has a growing community of users and contributors.

Who Should Use RAGLight

RAGLight is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.

Details

AuthorUnknown
Categoryinfrastructure
LicenseNot specified
Typeagent
SourceView on GitHub
Security Score0/100
Activity Score1/100

How to Get Started

Check the trust score before installing:

curl nerq.ai/v1/preflight?target=bessouat40-raglight

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

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Frequently Asked Questions

What is RAGLight used for?
RAGLight is a infrastructure tool. RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connec.
Is RAGLight free?
License: Check project page. RAGLight has 638 GitHub stars.
Is RAGLight safe?
RAGLight has a Nerq Trust Score of 58/100 (D). Use with caution.
What are alternatives to RAGLight?
Top alternatives: n8n, langflow, dify. See full comparison.

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

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