RagScore

by HZYAI · MCP Server · ★ 31

About RagScore

⚡️ The "1-Minute RAG Audit" — Generate QA datasets & evaluate RAG systems in Colab, Jupyter, or CLI. Privacy-first, async, visual reports.

ai-evaluationcolabdataset-generationevaluationfine-tuningjupyterllmllm-as-a-judgellmopslocal-llm

Quick Facts

Stars31
Forks5
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score32.9/100
Last Updated2026-05-19
Created2025-12-26
Platformscli, mcp, python
Est. Tokens~72k

Compatible Skills

These tools work well together with RagScore for enhanced workflows:

  • synkro — semantic(0.39)+complementary+rare_topics+same_lang+similar_pop+shared_platform (72%)
  • Dataset_Generator_for_Fine-tuning — semantic(0.23)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • just-eval — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • arag — semantic(0.26)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)

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Frequently Asked Questions

What is RagScore?

RagScore is ⚡️ The "1-Minute RAG Audit" — Generate QA datasets & evaluate RAG systems in Colab, Jupyter, or CLI. Privacy-first, async, visual reports.. It is categorized as a MCP Server with 31 GitHub stars.

What programming language is RagScore written in?

RagScore is primarily written in Python. It covers topics such as ai-evaluation, colab, dataset-generation.

How do I install or use RagScore?

You can find installation instructions and usage details in the RagScore GitHub repository at github.com/HZYAI/RagScore. The project has 31 stars and 5 forks, indicating an active community.

What license does RagScore use?

RagScore is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

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