Graphify turns a folder of files into a knowledge graph. It reads the files, finds
concepts, and links them. The graph answers questions that cross many files.
I run it on my Obsidian vault. The graph holds 2,171 nodes and 2,770 edges across
128 communities. An AI agent reads the graph instead of all 134 notes.
🌟 Key Highlights (Portfolio & Employment)
Concept: A persistent knowledge graph with an honest audit trail. Every link is tagged EXTRACTED, INFERRED, or AMBIGUOUS.
Tools & Skills Showcase: Python, NetworkX community detection, an MCP server, pi extension tools, and subagent orchestration for semantic extraction.
Practical Value: One query reads the graph instead of 134 files. The measured cost is 31 times fewer tokens per query.
📐 Architecture & Flow
flowchart LR
A["Obsidian vault<br/>134 notes"] --> B["detect + chunk"]
B --> C["semantic extraction<br/>pi subagents"]
C --> D["graph.json<br/>2171 nodes / 2770 edges"]
D --> E["cluster + analyze"]
E --> F["GRAPH_REPORT.md"]
E --> G["graph.html"]
D --> H["MCP server<br/>graphify-vault"]
H --> I["AI agents<br/>query_graph"]
