AgentIndex icon
AgentIndex
knowledge-rag logo
knowledge-rag
★ 300
vs
deep-research logo
deep-research
★ 4.7k

knowledge-rag vs deep-research

knowledge-rag: Knowledge RAG is a fully local, zero-cloud document retrieval system that lets Claude Code search your PDFs, markdown, code, and notebooks natively. It indexes up to 1800+ files in under 3 minutes, using hybrid search (BM25 + semantic vectors + cross-encoder reranking) via 12 MCP tools. Everything runs locally via ONNX, no Docker, Ollama, or API keys required.; deep-research: Deep Research is an AI-powered tool designed to generate comprehensive research reports rapidly, leveraging advanced AI models and internet connectivity. It prioritizes user privacy by processing and storing all data locally.

01

TL;DR

knowledge-rag logo
knowledge-ragRAG / Knowledge Base · ★ 300

Personal document retrieval and knowledge base for developers

Read knowledge-rag full review →
deep-research logo
deep-researchRAG / Knowledge Base · ★ 4.7k

Rapidly generate in-depth research reports for personal and professional use.

Read deep-research full review →
02

Side-by-Side Comparison

Field
knowledge-rag logoknowledge-rag
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 300
★ 4.7k
License
MIT
MIT
Install Command
pip install knowledge-rag
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
1w ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
bm25, chromadb, claude
AI Research, LLM, Privacy-focused
03

Features

knowledge-rag logoknowledge-rag
01Hybrid Search with BM25 + semantic vectors + cross-encoder reranking
02Optional GPU acceleration for 5-10x faster indexing
0320 format parsers (MD, PDF, DOCX, code, etc.)
04YAML configuration with domain-specific presets
0512 MCP tools for full CRUD, search, and evaluation
deep-research logodeep-research
01Rapidly generates comprehensive research reports in minutes.
02Ensures privacy by processing and storing all data locally in the browser.
03Supports a wide range of mainstream large language models (LLMs).
04Integrates with various web search engines for enhanced information gathering.
05Allows uploading and processing local files to build a knowledge base.
04

Use Cases

knowledge-rag logoknowledge-rag
↳Personal document retrieval and knowledge base for developers
↳Security research document indexing and querying
↳Offline documentation assistant for sensitive environments
deep-research logodeep-research
↳Rapidly generate in-depth research reports for personal and professional use.
↳Serve as a deep research as a service (SaaS) platform via SSE API.
↳Integrate deep research functionality into other AI applications using MCP.
FAQ

FAQ

What is the difference between knowledge-rag and deep-research?
Both knowledge-rag and deep-research are in the RAG / Knowledge Base category. knowledge-rag has 300 stars, while deep-research has 4.7k stars.
Which is better, knowledge-rag or deep-research?
The best choice depends on your use case. Choose knowledge-rag if Personal document retrieval and knowledge base for developers, and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is knowledge-rag free or open source?
Yes, knowledge-rag is open source on GitHub (MIT).
Is deep-research free or open source?
Yes, deep-research is open source on GitHub (MIT).
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