AgentIndex icon
AgentIndex
mykg logo
mykg
★ 78
vs
deep-research logo
deep-research
★ 4.7k

mykg vs deep-research

mykg: myKG automatically generates confidence-scored knowledge graphs from diverse document types, grounded in an induced RDFS/OWL ontology. It builds trustworthy knowledge graphs through a self-evolving ontology that adapts, maintains consistency, and assigns confidence scores to extracted knowledge.; 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

mykg logo
mykgRAG / Knowledge Base · ★ 78

Converting websites, GitHub repositories, and personal notes into queryable knowledge graphs.

Read mykg 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
mykg logomykg
deep-research logodeep-research
Category
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 78
★ 4.7k
License
MIT
MIT
Install Command
pip install mykg && mykg init
docker run -d --name deep-research -p 3333:3000 xiangfa/deep-research
Updated
2w ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Knowledge Graph, LLM, Ontology
AI Research, LLM, Privacy-focused
03

Features

mykg logomykg
01Schema-guided knowledge graph generation grounded in a formal RDFS/OWL schema.
02Supports mixed-format corpora including PDF, Word, HTML, and images, automatically converted to Markdown.
03Provides five output formats: JSONL, Turtle RDF, NetworkX, Obsidian vault, and Neo4j LOAD CSV.
04Enables incremental updates and schema growth by appending new or modified files to existing sessions.
05Integrates with AI coding assistants (e.g., Claude Code) by exporting an Obsidian vault as a 'second brain' for context.
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

mykg logomykg
↳Converting websites, GitHub repositories, and personal notes into queryable knowledge graphs.
↳Building a 'second brain' for AI coding assistants to ground answers and trace relationships in documents.
↳Creating an LLM-powered wiki from diverse documents for AI agents to reason over.
↳Facilitating human-in-the-loop ontology design and refinement through schema review gates.
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 mykg and deep-research?
Both mykg and deep-research are in the RAG / Knowledge Base category. mykg has 78 stars, while deep-research has 4.7k stars.
Which is better, mykg or deep-research?
The best choice depends on your use case. Choose mykg if Converting websites, GitHub repositories, and personal notes into queryable knowledge graphs., and deep-research if Rapidly generate in-depth research reports for personal and professional use..
Is mykg free or open source?
Yes, mykg 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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