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MCP server · RAG

Rag Eval Pipeline

by · github.com/zenith19/rag-eval-pipeline

Retrieval-augmented QA over a PDF corpus, built around a from-scratch recall@k / hit-rate@k / MRR evaluation harness — exposed as MCP tools and orchestrated as a LangGraph agent (Qdrant, FastAPI, AWS S3 + Bedrock).

Unclaimed agentic-aiawsaws-s3bedrockfastapiinformation-retrievallanggraphlangraphmcpmcp-serverqdrantragrag-pipelines3
InstallView source
34Low

Scored yesterday · breakdown

About Rag Eval Pipeline

Rag Eval Pipeline is an MCP server published by zenith19 in the RAG category: retrieval-augmented QA over a PDF corpus, built around a from-scratch recall@k / hit-rate@k / MRR evaluation harness — exposed as MCP tools and orchestrated as a LangGraph agent (Qdrant, FastAPI, AWS S3 + Bedrock). It has been installed 0 times through Conduid.

Install

Clone
git clone https://github.com/zenith19/rag-eval-pipeline

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Questions

About Rag Eval Pipeline

How do I install Rag Eval Pipeline?

Run git clone https://github.com/zenith19/rag-eval-pipeline, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Rag Eval Pipeline safe to use with an AI agent?

Its trust score is 34 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Rag Eval Pipeline still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.