mcp-graph-engine
A graph database MCP server that lets AI assistants build, analyze, and visualize relationship graphs with algorithms like PageRank and cycle detection.
README
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.
<img alt="image" src="docs/assets/screenshot.png" />
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
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