Enhanced Gemini MCP Server

# Enhanced Gemini MCP Server **Intelligent Codebase Analysis with Gemini's 1M Token Context Window** Transform your development workflow with this enhanced MCP server that leverages Google's Gemini AI for comprehensive codebase analysis. Load entire projects into Gemini's massive context window and get intelligent insights about your code. ## Key Features - **Intelligent Codebase Loading** - Smart file prioritization and relevance scoring - **1M Token Context** - Leverage Gemini's full context window for comprehensive analysis - **Semantic Search** - Natural language code search across your entire project - **Architecture Analysis** - Get detailed insights into your codebase structure - **Smart Improvements** - Targeted suggestions for performance, security, and maintainability - **Code Flow Tracing** - Understand how functionality works across files - **Project Summaries** - Comprehensive overviews of any codebase - **Session Caching** - 30-minute cache for faster repeated analyses - **Export Sessions** - Save important findings for future reference ## Quick Start ### Prerequisites - Python 3.8+ installed - Claude Code CLI installed - Google Gemini API key ([Get one free](https://aistudio.google.com/apikey)) ### Installation 1. **Clone the repository:** ```bash git clone https://github.com/ECamposSoria/gemini-mcp-enhanced.git cd gemini-mcp-enhanced ``` 2. **Run enhanced setup:** ```bash ./enhanced_setup.sh ``` 3. **Enter your Gemini API key when prompted** That's it! ## Available Tools ### Core Analysis Tools #### `load_codebase` Load an entire project into Gemini's context with intelligent prioritization: ```bash mcp__gemini-collab-enhanced__load_codebase project_path: "/path/to/your/project" max_tokens: 900000 # optional, default: 900000 ``` #### `analyze_architecture` Get comprehensive architecture analysis: ```bash mcp__gemini-collab-enhanced__analyze_architecture focus: "architecture" # or "patterns", "dependencies", "structure" ``` #### `semantic_search` Search your codebase using natural language: ```bash mcp__gemini-collab-enhanced__semantic_search query: "Find functions that handle user authentication" ``` #### `suggest_improvements` Get targeted improvement suggestions: ```bash mcp__gemini-collab-enhanced__suggest_improvements area: "security" # or "performance", "maintainability", "testing" ``` #### `explain_codeflow` Trace how functionality works across your codebase: ```bash mcp__gemini-collab-enhanced__explain_codeflow functionality: "How user registration works from API to database" ``` #### `codebase_summary` Get a comprehensive project overview: ```bash mcp__gemini-collab-enhanced__codebase_summary ``` #### `ask_with_context` Ask any question about your loaded codebase: ```bash mcp__gemini-collab-enhanced__ask_with_context question: "What security vulnerabilities exist in the authentication system?" ``` ### Session Management Tools #### `export_session` Export cached analysis results to a markdown file: ```bash mcp__gemini-collab-enhanced__export_session export_path: "/path/to/export" # optional, defaults to project path ``` #### `session_stats` Get current session cache statistics: ```bash mcp__gemini-collab-enhanced__session_stats ``` ## Session Caching The enhanced server includes intelligent session caching to improve performance: - **Automatic Caching**: Analysis results are cached for 30 minutes - **Smart Invalidation**: Cache clears when switching projects - **Performance Boost**: Repeated queries return instantly from cache - **Export Capability**: Save important findings before they expire ### Caching Benefits 1. **Faster Iterations**: Re-run analyses without waiting 2. **Token Savings**: Avoid redundant API calls to Gemini 3. **Persistent Insights**: Export sessions for long-term reference ## Usage Examples ### Complete Workflow Example ```bash # Start Claude Code claude # Load your project mcp__gemini-collab-enhanced__load_codebase project_path: "/home/user/my-app" # Get architecture overview mcp__gemini-collab-enhanced__analyze_architecture # Find specific functionality mcp__gemini-collab-enhanced__semantic_search query: "payment processing logic" # Get security improvements mcp__gemini-collab-enhanced__suggest_improvements area: "security" # Ask specific questions mcp__gemini-collab-enhanced__ask_with_context question: "How can I optimize the database queries in the user service?" ``` ## How It Works ### Intelligent File Prioritization The server uses a sophisticated scoring system to determine which files are most relevant: - **Language weights** - Core languages (Python, JavaScript, TypeScript) get higher priority - **Directory importance** - `src/`, `lib/`, `core/` directories are prioritized - **File size optimization** - Balances completeness with context limits - **Special files** - `main.py`, `index.js`, `app.py` get bonus priority ### Smart Token Management - Uses `tiktoken` for accurate token counting - Stays within Gemini's 1M token limit intelligently - Fallback estimation when tiktoken unavailable - Structured context formatting for optimal analysis ### Context Creation Creates comprehensive context including: - File tree structure with metadata - Complete file contents with syntax highlighting - Relevance scores and language detection - Project statistics and organization ## Technical Details ### Supported File Types - **Languages**: Python, JavaScript, TypeScript, Java, C++, Go, Rust, Swift, Kotlin, Scala - **Web**: HTML, CSS, SCSS, Vue, Svelte, React (JSX/TSX) - **Config**: JSON, YAML, XML, Dockerfile, Terraform - **Documentation**: Markdown, SQL scripts ### Performance Features - Intelligent file filtering (skips `node_modules`, `.git`, `__pycache__`, etc.) - Relevance-based file selection - Token-aware content loading - Efficient context creation ## Installation Details The enhanced server is installed at: `~/.claude-mcp-servers/gemini-collab-enhanced/` ### File Structure ``` ~/.claude-mcp-servers/gemini-collab-enhanced/ ├── enhanced_server.py # Main server with intelligent analysis ├── requirements.txt # Python dependencies └── test_enhanced.py # Test suite ``` ## Troubleshooting **Server not showing up?** ```bash # Check installation claude mcp list # Reinstall if needed claude mcp remove gemini-collab-enhanced ./enhanced_setup.sh ``` **Token counting issues?** ```bash # Install tiktoken for accurate counting pip install tiktoken>=0.5.1 ``` **Large codebase not loading completely?** - Increase `max_tokens` parameter - Check file relevance scores - Exclude unnecessary directories **Connection errors?** - Verify Gemini API key is valid - Check internet connection - Ensure dependencies are installed: `pip install -r requirements.txt` ## Best Practices ### For Large Codebases - Start with architectural analysis - Use semantic search to find specific areas - Focus improvement suggestions on specific areas - Break down complex questions into smaller parts ### For Security Analysis 1. Load codebase 2. Run security-focused improvements 3. Use semantic search for auth/validation code 4. Ask specific security questions with context ### For Performance Optimization 1. Analyze architecture first 2. Search for performance-critical code 3. Get performance-focused suggestions 4. Trace code flow for bottlenecks ## Contributing Contributions welcome! Please: 1. Fork the repository 2. Create a feature branch 3. Add tests for new functionality 4. Submit a pull request ## License MIT License - Use freely! ## Acknowledgments - Built for the Claude Code community - Powered by Google's Gemini AI - Enhanced by ECamposSoria --- **Ready to revolutionize your code analysis?** Start by loading your first codebase and experience the power of AI-driven development insights!