How do I use Cocktails RAG MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Cocktails RAG MCP Server give me a refreshing gin-based cocktail for a summer evening" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Cocktails RAG MCP Server

MCP tool for cocktail recommendations using RAG (Retrieval-Augmented Generation).

Requirements

Python 3.11+
uv package manager - https://docs.astral.sh/uv/getting-started/installation/

Quick Start

Get Groq API key (free): https://console.groq.com/keys
Setup:
# Clone the repository git clone https://github.com/00200200/cocktails-rag-mcp.git cd cocktails-rag-mcp # Copy environment template cp .env.example .env # Edit .env and add your GROQ_API_KEY nano .env # Install dependencies uv sync
Pre-download models (required):
Download embeddings and reranker models:
uv run python -c "from src.rag.rag import RAG; RAG(); print('Models downloaed!')"
Install for Claude Desktop:
Automatic (Recommended)
uv run fastmcp install claude-desktop fastmcp.json --name cocktails --env-file .env
Manual
Edit config file:
- macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
- Windows: %APPDATA%\Claude\claude_desktop_config.json
{ "mcpServers": { "cocktails": { "command": "uv", "args": [ "run", "--with","faiss-cpu", "--with","fastmcp", "--with","jq", "--with","langchain", "--with","langchain-community", "--with","langchain-groq", "--with","langchain-huggingface", "--with","pandas", "--with","python-dotenv", "--with","sentence-transformers", "fastmcp", "run", "/ABSOLUTE/PATH/TO/src/mcp/server.py:mcp" ], "env": { "GROQ_API_KEY": "your_groq_api_key_here" } } } }
Replace /ABSOLUTE/PATH/TO/ with your project path and GROQ_API_KEY with your API key.

Example Usage

Local Testing

# Test RAG pipeline directly uv run python -m src.rag.rag # Test MCP server locally uv run python src/mcp/server.py

Development

Code Formatting

# Format code with black uv tool run black . # Sort imports with isort uv tool run isort .

Project Structure

RAG/ ├── src/ │ ├── mcp/ # MCP server implementation (FastMCP) │ ├── rag/ # RAG pipeline (retrieve, rerank, generate) │ ├── db/ # FAISS vector database handler │ └── data/ # Data loading utilities ├── data/ # Cocktail dataset ├── faiss_index/ # Generated FAISS index (auto-created on first run) ├── notebooks/ # EDA notebook ├── fastmcp.json # FastMCP configuration ├── pyproject.toml # Project dependencies └── .env.example # Environment template