ragflow vs modular-context-obsidian-plugin
ragflow: RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that integrates RAG with Agent capabilities. It provides a superior context layer for LLMs and offers a streamlined RAG workflow adaptable to enterprises of any scale.; modular-context-obsidian-plugin: Modular Context is an Obsidian plugin that provides an LLM-native knowledge base structured as Sources, Wiki, and Schema, inspired by Karpathy's framing. It also includes a G-Suite MCP server that exposes multi-account Gmail and Calendar as 10 tools for Claude Code. The plugin is local-first, encrypted, and has no telemetry.
TL;DR
- Your documents have complex layouts (PDFs, scanned files, tables, slides) and you need layout analysis, OCR, and traceable citations.
- You want an Apache-2.0 all-in-one RAG platform where you can inspect and hand-tune template-based chunks in a web UI.
- Your server has less than 4 CPU cores and 16 GB RAM; RAGFlow's multi-service stack is heavy.
- You want an autonomous web research agent that writes 2,000-word reports from live search rather than indexing a local document corpus; GPT Researcher fits better.
Synthesise raw files (transcripts, notes, backlog) into vault modules
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