vibe-coder-mcp-v4

# Vibe Coder MCP Server - v4 Final Release > **IMPORTANT NOTICE**: This is the final v4 release of the Vibe Coder MCP Server, which includes the Automatic Contextual Retrieval System (ACRS) tools. Development has moved to v5 in a separate repository. This version is being made available to the community as a stable, feature-complete release. ## New in v4: Automatic Contextual Retrieval System (ACRS) The v4 release introduces the Automatic Contextual Retrieval System, which enhances AI assistant capabilities through: - **Contextual memory**: Stores and retrieves relevant information based on the current context - **Advanced caching**: Reduces redundant LLM calls and improves response times - **Semantic search**: Finds related content based on meaning rather than exact text matching - **Sequential thinking**: Breaks down complex problems into manageable steps These tools enable more coherent, context-aware interactions with LLM-based assistants. ## Getting Started with GitHub Version ### Quick Installation 1. **Clone the repository**: ```bash git clone https://github.com/jsscarfo/vibe-coder-mcp-v4.git cd vibe-coder-mcp-v4 ``` 2. **Setup**: - For Windows: `setup.bat` - For macOS/Linux: ```bash chmod +x setup.sh ./setup.sh ``` 3. **Configure OpenRouter API Key**: - Create a `.env` file by copying `.env.example` - Add your OpenRouter API key to the `.env` file 4. **Integrate with your AI Assistant**: - Update your AI assistant's MCP configuration to include Vibe Coder - See the full Setup Guide below for detailed instructions ### ACRS Tools Usage To use the Automatic Contextual Retrieval System tools: 1. **Add memory entries**: ``` Add to memory: [content to remember] ``` 2. **Process requests with contextual enhancement**: ``` Process request [your request] with context ``` 3. **Enhance prompts for LLMs**: ``` Enhance prompt: [your prompt] ``` 4. **Get performance metrics**: ``` Get retrieval metrics ``` See the detailed documentation below for more information.