Go Code Graph

A powerful Go codebase analyzer that transforms code into explorable graphs, enabling AI assistants to understand complex codebases through the Model Context Protocol (MCP).

What is Go Code Graph?

Go Code Graph analyzes Go source code to create a comprehensive graph representation of your codebase structure, including packages, types, functions, and their relationships. This graph can be:

• Visualized in an interactive web interface
• Stored in Neo4j for complex queries
• Queried by AI assistants through MCP for intelligent code understanding

Key Features

• 🔍 Deep Code Analysis: Extracts 9 node types and 12 relationship types from Go AST
• 🎨 Interactive Visualization: Web interface handling 4,000+ nodes with real-time filtering
• 🧠 AI-Powered Understanding: MCP server enables natural language queries about your code
• 📊 Graph Database: Neo4j integration for complex architectural analysis
• 🚀 Enterprise Scale: Successfully tested on codebases with 97 packages and 4,000+ nodes
• ⚡ Semantic Search: Optional embeddings for enhanced code understanding

Quick Start with MCP

1. Setup with Docker (Recommended)

# Clone and setup
git clone https://github.com/brutski/go-code-graph.git
cd go-code-graph
make dev-setup  # Starts Neo4j and builds MCP server image

2. Configure Claude Desktop

make generate-mcp-config  # Generates exact configuration needed

Copy the output to your Claude Desktop config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

3. Start Using with AI

The MCP server is now ready! Your AI assistant can analyze any Go codebase.

MCP Tools and Prompts

The MCP server provides two ways to analyze your codebase:

MCP Prompts (Guided Workflows)

The MCP server includes 15 comprehensive prompts that guide you through common analysis tasks. These prompts show the AI assistant exactly which tools to use and in what order, ensuring best practices and comprehensive coverage. See MCP Prompts Guide for detailed documentation.

Example prompts:

• analyze_new_codebase - Complete initial analysis with architecture overview
• assess_code_quality - Comprehensive quality assessment with actionable insights
• analyze_change_impact - Understand effects before making changes
• debug_execution_flow - Trace execution paths for debugging
• plan_refactoring - Get step-by-step refactoring guidance

When to use prompts: Starting new analysis tasks, following best practices, ensuring comprehensive coverage.

MCP Tools (Building Blocks)

The MCP server provides 8 powerful tools for direct codebase analysis. These are the building blocks that prompts use, but you can also use them directly for specific queries and custom exploration:

🔍 analyze_workspace