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mcp-graph-engine

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Python
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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.

Related MCP server: CodeRAG

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

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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