---
title: Graphify
type: project
status: active
created: "2026-10-13"
updated: "2026-09-26"
tags:
  - project
  - ai-agents
  - architecture
  - obsidian
  - graphify
  - tool
  - knowledge-graph
  - pi-agent
  - showcase
skills:
  - python
  - knowledge-graphs
  - mcp
  - subagent-orchestration
  - graph-analytics
tools:
  - graphify (graphifyy)
  - pi-graphify
  - mcp
  - networkx
---

# Graphify — Overview

## 💡 What is this project?

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

```mermaid
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"]
```

## 🔗 Related Notes & Links

- **Graph data**: `/home/sam/graphify/obsidian-vault/graph.json`
- **Interactive HTML**: `/home/sam/graphify/obsidian-vault/graph.html`
- **Report**: `/home/sam/graphify/obsidian-vault/GRAPH_REPORT.md`
- **Interface**: MCP server `graphify-vault` (query from any folder), plus CLI and pi tools.
- **AI Context (Outline)**: collection `Graphify`