What is Vibe Coder Mcp V4

Vibe Coder MCP v4 is the final release of the Vibe Coder MCP Server, featuring an Automatic Contextual Retrieval System (ACRS) that enhances AI assistant capabilities by providing contextual memory, advanced caching, semantic search, and sequential thinking.

Use cases

Use cases include improving user interactions in chatbots, enhancing virtual assistants’ performance, and facilitating more coherent responses in AI-driven applications.

How to use

To use vibe-coder-mcp-v4, clone the repository, set up the environment according to your OS, configure the OpenRouter API key in a .env file, and integrate it with your AI assistant by updating its MCP configuration.

Key features

Key features include contextual memory for storing relevant information, advanced caching to improve response times, semantic search for meaning-based content retrieval, and sequential thinking to break down complex problems.

Where to use

Vibe Coder MCP v4 can be used in various fields such as AI development, customer support automation, and any application requiring enhanced contextual interactions with AI assistants.

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:

   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:

     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.