mnemo-secondbrain 0.2.1

Personal knowledge graph system for Obsidian vaults with hybrid search

Mnemo — Personal Knowledge Graph for Obsidian

Turn your Obsidian vault into a queryable knowledge graph with hybrid search (vector + graph traversal).

Features

• Automatic Graph Building — Parses [[wikilinks]], YAML frontmatter, and tags from your Obsidian vault into a NetworkX knowledge graph
• Hybrid Search — Combines vector similarity search with graph-based multi-hop traversal
• Ontology Classification — Auto-classifies entities (Person, Concept, Project, Tool, Insight, etc.)
• Knowledge Collectors — Web clipping, trust evaluation, and automated knowledge pipeline
• REST API — FastAPI server for programmatic access
• Obsidian Plugin — Companion plugin for in-vault queries (see obsidian-plugin/)
• CLI Interface — Full-featured command-line tool for graph operations

Quick Start

Option 1 — uvx (recommended, no install needed)

uvx --from mnemo-secondbrain mnemo start /path/to/your/vault

That's it. One command builds your knowledge graph and starts the API server.

Option 2 — pip

pip install mnemo-secondbrain
mnemo start /path/to/your/vault

Option 3 — Docker

docker run -p 7890:7890 -v /path/to/your/vault:/vault jini92/mnemo /vault

Connect Obsidian Plugin

1. Open Obsidian → Settings → Community plugins → search Mnemo SecondBrain → Install & Enable
2. In the Mnemo plugin settings, set Server URL to http://localhost:7890
3. Press Ctrl+Shift+M to search your knowledge graph

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Advanced Usage

# Build graph only (no server)
mnemo build /path/to/your/vault

# Start server only (after building)
mnemo serve --port 7890

# Query from CLI
mnemo query "machine learning fundamentals"

# Show graph statistics
mnemo stats

API Endpoints

Method	Path	Description
GET	/api/search	Hybrid search
GET	/api/graph/stats	Graph statistics
GET	/api/graph/node/{id}	Get node details
GET	/api/graph/neighbors/{id}	Get node neighbors

Architecture

Obsidian Vault (Markdown + YAML + [[links]])
        ↓  parse
   NetworkX Graph (in-memory)
        ↓  embed
   Vector Index + Graph Index
        ↓  query
   Hybrid Search (vector + graph traversal)
        ↓  rerank
   Results with context

Development

git clone https://github.com/jini92/MAISECONDBRAIN.git
cd MAISECONDBRAIN
pip install -e ".[dev,all]"
pytest

License

MIT — see LICENSE.