MCP Graph Engine

A graph database for AI assistants via the Model Context Protocol. Build relationship graphs, run analysis algorithms, and visualize in real-time.

Installation

Requirements: Python 3.10+, MCP-compatible client (Claude Code, Claude Desktop, Cursor)

pipx install mcp-graph-engine

Add to your MCP config:

{
  "mcpServers": {
    "graph-engine": {
      "command": "mcp-graph-engine"
    }
  }
}

Client	Config Location
Claude Code	~/.mcp.json or .mcp.json
Claude Desktop	~/Library/Application Support/Claude/claude_desktop_config.json
Cursor	.cursor/mcp.json

Restart your client after adding the config.

What You Can Do

Just ask your AI assistant:

• "Map out the dependencies in this codebase"
• "Build a graph of the characters in this document"
• "What's the most critical component?"
• "Are there any circular dependencies?"
• "Show me the path from X to Y"
• "Visualize the graph"

The AI handles the tool calls. You get a live visualization at http://localhost:8765.

Features

• Analysis - PageRank, cycle detection, shortest paths, connected components
• Visualization - Live D3 force-directed graph in your browser
• Import/Export - DOT, CSV, GraphML, JSON, Mermaid

Configuration

Variable	Default	Description
VIS_PORT	8765	Visualization server port
VIS_HOST	localhost	Visualization server host
VIS_ENABLED	true	Enable/disable visualization

Notes

• Transient - Graphs live in memory. Export to JSON for persistence.
• Fuzzy matching - pipx install mcp-graph-engine[embeddings] for semantic node matching.

License

MIT