gephi-ai

AI-powered network analysis through Gephi and the Model Context Protocol (MCP). Build, analyze, style, and export publication-ready network visualizations by talking to your AI assistant.

Built for researchers working across network science and AI.

What you get

73 MCP tools for controlling Gephi Desktop — graph construction, community detection, centrality analysis, layout algorithms, filtering, styling, and publication-ready export.

Claude Code plugin with slash commands (/analyze-network, /community-detection, /centrality, /visualize, /import-and-explore), a specialized network analyst agent, and workflow skills that teach Claude network science best practices.

Works with any MCP client — Claude Code, Claude Desktop, or any MCP-compatible assistant.

Architecture

Three components connect your AI assistant to Gephi Desktop:

Claude / AI Assistant
        │
   MCP Protocol (stdio)
        │
   MCP Server (Python)          ← Translates MCP tool calls to HTTP
        │
   HTTP API (localhost:8080)
        │
   Gephi Plugin (Java)          ← Runs inside Gephi Desktop
        │
   Gephi Desktop                ← Must be running first

All three must be installed. Gephi Desktop must be running before using any tools.

Setup

Prerequisites

• Gephi Desktop 0.10.1+
• Java JDK 11+ and Maven (to build the Gephi plugin)
• Python 3.10+ (for the MCP server)
• Claude Code or Claude Desktop (for AI interaction)

Step 1: Install the Gephi plugin

This adds the HTTP API server inside Gephi Desktop.

cd gephi-mcp-plugin
mvn clean package

Then in Gephi: Tools → Plugins → Downloaded → Add Plugins — select target/nbm/gephi-mcp-1.0.0.nbm.

Restart Gephi. The plugin starts automatically and listens on http://127.0.0.1:8080.

Verify: Open a browser to http://127.0.0.1:8080/health — you should see {"success": true}.

Step 2: Install the MCP server

This bridges MCP clients to the Gephi HTTP API.

cd mcp-server
pip install -e .

This installs the gephi-mcp command on your PATH.

Verify: Run gephi-mcp --help to confirm it installed.

Step 3: Connect your AI assistant

Claude Code (full plugin — recommended)

claude plugin install gephi-ai/gephi-network-analysis

This adds the MCP server, slash commands, network analyst agent, skills, and a health-check hook.

Claude Code (MCP tools only)

If you just want the 73 tools without skills and commands:

claude mcp add gephi-mcp -- gephi-mcp

Claude Desktop

Add to your MCP configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "gephi-mcp": {
      "command": "gephi-mcp"
    }
  }
}

Other MCP clients

Point your client at the gephi-mcp command using stdio transport.

Step 4: Verify

With Gephi running, ask your assistant:

"Check if Gephi is running"

It should call gephi_health_check and confirm the connection. In Claude Code, try:

/gephi-network-analysis:import-and-explore path/to/your/graph.gexf

What the Claude Code plugin adds

The plugin (claude-plugin/) goes beyond raw MCP tools:

Tools (73)

Example workflows

Community detection

1. gephi_create_project
2. gephi_import_file                  (your GEXF, GraphML, or CSV)
3. gephi_compute_degree
4. gephi_compute_modularity           (resolution: 1.0)
5. gephi_color_by_partition           (column: modularity_class)
6. gephi_size_by_ranking              (column: degree)
7. gephi_run_layout                   (ForceAtlas 2, 1000 iterations)
8. gephi_export_png                   (3840x2160 for publication)

Centrality analysis

1. Import or build graph
2. gephi_compute_betweenness
3. gephi_compute_pagerank
4. gephi_run_layout                   (ForceAtlas 2)
5. gephi_color_by_ranking             (column: betweenesscentrality)
6. gephi_size_by_ranking              (column: pageranks)
7. gephi_query_nodes                  (find top-ranked nodes)

Documentation

Reference guides are in claude-plugin/skills/gephi/:

• SKILL.md — Workflow patterns, best practices, and critical gotchas
• references/tool-reference.md — Complete API reference for all 73 tools
• references/layout-guide.md — Layout algorithm selection and parameter tuning
• references/statistics-guide.md — Statistics interpretation guide

Tech stack

• Gephi Plugin: Java 11, NetBeans Platform, NanoHTTPD, Gson
• MCP Server: Python 3.10+, MCP SDK (FastMCP), httpx, Pydantic
• Target: Gephi 0.10.1, NetBeans RELEASE126

Attribution

If you use or adapt this project in your work, please credit:

Built with gephi-ai (Matt Artz, 2025–2026) — https://github.com/MattArtzAnthro/gephi-ai

License

Apache License 2.0 — see LICENSE.

Author

Matt Artz — mattartz.me | ORCID