CodeGraph CLI MCP Server

# CodeGraph MCP Tools Usage Guidelines ## 🌍 **Universal Programming Language Support (11 Languages)** CodeGraph provides **revolutionary AI intelligence** across the most popular programming languages: ### 🚀 **Tier 1: Advanced Semantic Analysis (8 Languages)** - **Rust** - Complete ownership/borrowing analysis, trait relationships, async patterns - **Python** - Type hints, docstrings, dynamic analysis patterns - **JavaScript** - Modern ES6+, async/await, functional patterns - **TypeScript** - Type system analysis, generics, interface relationships - **Swift** - iOS/macOS development, SwiftUI patterns, protocol-oriented programming - **C#** - .NET patterns, LINQ analysis, async/await, dependency injection - **Ruby** - Rails patterns, metaprogramming, dynamic typing intelligence - **PHP** - Laravel/Symfony patterns, namespace analysis, modern PHP features ### 🚀 **Tier 2: Basic Semantic Analysis (3 Languages)** - **Go** - Goroutines, interfaces, package management - **Java** - OOP patterns, annotations, Spring framework detection - **C++** - Modern C++, templates, memory management patterns **Revolutionary Total: 11 languages with AI-powered semantic analysis** ## 📋 **MCP Tools - Streamlined Essential Suite (8 Tools)** ### 🧠 AI Intelligence & Analysis Tools #### 1. `enhanced_search` - AI-Powered Semantic Search ``` Description: Search your codebase with AI analysis. Finds code patterns, architectural insights, and team conventions. Use when you need intelligent analysis of search results. Required: query (what to search for) Optional: limit (max results, default 10) Example: "Find all authentication-related code and explain the patterns" ``` #### 2. `semantic_intelligence` - Deep Architectural Analysis ``` Description: Perform deep architectural analysis of your entire codebase using AI. Explains system design, component relationships, and overall architecture. Use for understanding large codebases or documenting architecture. Required: query (analysis focus) Optional: task_type (analysis type, default 'semantic_search'), max_context_tokens (AI context limit, default 80000) Example: "Explain the overall system architecture and component relationships" ``` #### 3. `impact_analysis` - Breaking Change Prediction ``` Description: Predict the impact of modifying a specific function or class. Shows what code depends on it and might break. Use before refactoring to avoid breaking changes. Required: target_function (function/class name), file_path (path to file containing it) Optional: change_type (type of change, default 'modify') Example: "What would happen if I modify the authentication middleware?" ``` #### 4. `pattern_detection` - Team Convention Analysis ``` Description: Analyze your team's coding patterns and conventions. Detects naming conventions, code organization patterns, error handling styles, and quality metrics. Use to understand team standards or onboard new developers. Required: No parameters required Example: "Analyze the coding patterns and conventions in this codebase" ``` ### 🔍 Advanced Search & Graph Navigation Tools #### 5. `vector_search` - Fast Similarity Search ``` Description: Fast vector similarity search to find code similar to your query. Returns raw search results without AI analysis (faster than enhanced_search). Use for quick code discovery. Required: query (what to find) Optional: paths (filter by directories), langs (filter by languages), limit (max results, default 10) Example: "Search for error handling patterns in the service layer" ``` #### 6. `graph_neighbors` - Code Dependency Analysis ``` Description: Find all code that depends on or is used by a specific code element. Shows dependencies, imports, and relationships. Use to understand code impact before refactoring. Required: node (UUID from search results) Optional: limit (max results, default 20) Note: Get node UUIDs from vector_search or enhanced_search results Example: "Find all code that depends on the UserService class" ``` #### 7. `graph_traverse` - Architectural Flow Exploration ``` Description: Follow dependency chains through your codebase to understand architectural flow and code relationships. Use to trace execution paths or understand system architecture. Required: start (UUID from search results) Optional: depth (how far to traverse, default 2), limit (max results, default 100) Note: Get start UUIDs from vector_search or enhanced_search results Example: "Trace the complete flow from API endpoint to database" ``` ### 📊 Performance & System Analytics Tools #### 8. `performance_metrics` - System Health Monitoring ``` Description: Get CodeGraph system performance metrics including cache hit rates, search performance, and AI model usage stats. Use to monitor system health or troubleshoot performance issues. Required: No parameters required Example: "Show me the performance metrics and optimization suggestions" ``` ## 🚀 Usage Best Practices ### **Setup & Indexing** - **Always index your codebase** before starting AI-assisted development with `codegraph init .` and `codegraph index . --recursive` - **Automatic language detection** - Just run `codegraph index .` to process all 11 supported languages - **Reindex periodically** after adding features, version upgrades, API changes etc. ### **Workflow Recommendations** - **Use `pattern_detection`** first to understand team conventions and coding standards - **Use `impact_analysis`** before making significant changes to predict breaking changes - **Use `enhanced_search`** for AI-powered architectural understanding and code discovery - **Use `semantic_intelligence`** for comprehensive codebase analysis and documentation - **Use `vector_search`** for fast similarity-based code search across large codebases - **Use `graph_neighbors` and `graph_traverse`** for dependency analysis and architectural exploration (requires UUIDs from search results) - **Monitor system health** with `performance_metrics` for optimization insights ### 💡 **Tool Selection Guide** **For Code Discovery**: `vector_search` (fast) → `enhanced_search` (AI analysis) **For Architecture Understanding**: `semantic_intelligence` → `graph_traverse` **For Refactoring Safety**: `impact_analysis` → `graph_neighbors` **For Team Onboarding**: `pattern_detection` → `semantic_intelligence` ## 🛠️ **Quick Setup for New Projects** ```bash # 1. Navigate to your project directory cd /path/to/your/project # 2. Initialize CodeGraph (one-time setup) codegraph init . # 3. Index your codebase (supports all 11 languages automatically) codegraph index . --recursive # 4. Start using CodeGraph tools in Claude Code! # No configuration needed - works globally with any project ``` ## 🎯 **Integration Notes** - **Global Operation**: Works from any project directory without manual configuration - **Zero Tool Overlap**: Designed to complement Claude Code's built-in tools - **Universal Compatibility**: Supports 90%+ of popular programming languages - **Framework Intelligence**: Automatically detects and analyzes framework-specific patterns --- *This guide can be copied to any project's CLAUDE.md file for universal CodeGraph MCP tool access.*