Wikimedia MCP Server

# MCP Neurolora    An intelligent MCP server that provides tools for code analysis using OpenAI API, code collection, and documentation generation. ## 🚀 Installation Guide Don't worry if you don't have anything installed yet! Just follow these steps or ask your assistant to help you with the installation. ### Step 1: Install Node.js #### macOS 1. Install Homebrew if not installed: ```bash /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" ``` 2. Install Node.js 18: ```bash brew install node@18 echo 'export PATH="/opt/homebrew/opt/node@18/bin:$PATH"' >> ~/.zshrc source ~/.zshrc ``` #### Windows 1. Download Node.js 18 LTS from [nodejs.org](https://nodejs.org/) 2. Run the installer 3. Open a new terminal to apply changes #### Linux (Ubuntu/Debian) ```bash curl -fsSL https://deb.nodesource.com/setup_18.x | sudo -E bash - sudo apt-get install -y nodejs ``` ### Step 2: Install uv and uvx #### All Operating Systems 1. Install uv: ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` 2. Install uvx: ```bash uv pip install uvx ``` ### Step 3: Verify Installation Run these commands to verify everything is installed: ```bash node --version # Should show v18.x.x npm --version # Should show 9.x.x or higher uv --version # Should show uv installed uvx --version # Should show uvx installed ``` ### Step 4: Configure MCP Server Your assistant will help you: 1. Find your Cline settings file: - VSCode: `~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json` - Claude Desktop: `~/Library/Application Support/Claude/claude_desktop_config.json` - Windows VSCode: `%APPDATA%/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json` - Windows Claude: `%APPDATA%/Claude/claude_desktop_config.json` 2. Add this configuration: ```json { "mcpServers": { "aindreyway-mcp-neurolora": { "command": "npx", "args": ["-y", "@aindreyway/mcp-neurolora@latest"], "env": { "NODE_OPTIONS": "--max-old-space-size=256", "OPENAI_API_KEY": "your_api_key_here" } } } } ``` ### Step 5: Install Base Servers Simply ask your assistant: "Please install the base MCP servers for my environment" Your assistant will: 1. Find your settings file 2. Run the install_base_servers tool 3. Configure all necessary servers automatically After the installation is complete: 1. Close VSCode completely (Cmd+Q on macOS, Alt+F4 on Windows) 2. Reopen VSCode 3. The new servers will be ready to use > **Important:** A complete restart of VSCode is required after installing the base servers for them to be properly initialized. > **Note:** This server uses `npx` for direct npm package execution, which is optimal for Node.js/TypeScript MCP servers, providing seamless integration with the npm ecosystem and TypeScript tooling. ## Base MCP Servers The following base servers will be automatically installed and configured: - fetch: Basic HTTP request functionality for accessing web resources - puppeteer: Browser automation capabilities for web interaction and testing - sequential-thinking: Advanced problem-solving tools for complex tasks - github: GitHub integration features for repository management - git: Git operations support for version control - shell: Basic shell command execution with common commands: - ls: List directory contents - cat: Display file contents - pwd: Print working directory - grep: Search text patterns - wc: Count words, lines, characters - touch: Create empty files - find: Search for files ## 🎯 What Your Assistant Can Do Ask your assistant to: - "Analyze my code and suggest improvements" - "Install base MCP servers for my environment" - "Collect code from my project directory" - "Create documentation for my codebase" - "Generate a markdown file with all my code" ## 🛠 Available Tools ### analyze_code Analyzes code using OpenAI API and generates detailed feedback with improvement suggestions. Parameters: - `codePath` (required): Path to the code file or directory to analyze Example usage: ```json { "codePath": "/path/to/your/code.ts" } ``` The tool will: 1. Analyze your code using OpenAI API 2. Generate detailed feedback with: - Issues and recommendations - Best practices violations - Impact analysis - Steps to fix 3. Create two output files in your project: - LAST_RESPONSE_OPENAI.txt - Human-readable analysis - LAST_RESPONSE_OPENAI_GITHUB_FORMAT.json - Structured data for GitHub issues > Note: Requires OpenAI API key in environment configuration ### collect_code Collects all code from a directory into a single markdown file with syntax highlighting and navigation. Parameters: - `directory` (required): Directory path to collect code from - `outputPath` (optional): Path where to save the output markdown file - `ignorePatterns` (optional): Array of patterns to ignore (similar to .gitignore) Example usage: ```json { "directory": "/path/to/project/src", "outputPath": "/path/to/project/src/FULL_CODE_SRC_2024-12-20.md", "ignorePatterns": ["*.log", "temp/", "__pycache__", "*.pyc", ".git"] } ``` ### install_base_servers Installs base MCP servers to your configuration file. Parameters: - `configPath` (required): Path to the MCP settings configuration file Example usage: ```json { "configPath": "/path/to/cline_mcp_settings.json" } ``` ## 🔧 Features The server provides: - Code Analysis: - OpenAI API integration - Structured feedback - Best practices recommendations - GitHub issues generation - Code Collection: - Directory traversal - Syntax highlighting - Navigation generation - Pattern-based filtering - Base Server Management: - Automatic installation - Configuration handling - Version management ## 📄 License MIT License - feel free to use this in your projects! ## 👤 Author **Aindreyway** - GitHub: [@aindreyway](https://github.com/aindreyway) ## ⭐️ Support Give a ⭐️ if this project helped you!