mcp-assistant-playground

# 💬 MCP Assistant Playground https://github.com/user-attachments/assets/c60a59c0-5ff5-487e-be47-bdcc8253fbc8 https://github.com/user-attachments/assets/85e7453f-950d-41a4-a1f5-1abd3a587067 A Streamlit-based chatbot interface powered by OpenAI GPT-4o that intelligently routes user input to custom MCP tools such as GPT chat, image generation, Supabase queries, and text-to-speech. Built for rapid experimentation with AI-powered tool routing, inspired by Claude-style confirmation flows. --- ## ✨ Features - Natural language tool selection using GPT-4o - MCP tool execution via `fastmcp` - Real-time OpenAI image generation (DALL·E 3) - Text-to-speech audio synthesis (GPT-4o mini TTS) - Supabase integration for member CRUD operations - Streamlit UI with tool result rendering (image/audio) --- ## 🛠️ Prerequisites - Python 3.10+ - OpenAI API key - Supabase project (optional, for member tools) --- ## 🧪 Getting Started ### 1. Clone the repository ```bash git clone https://github.com/niawjunior/mcp-assistant-playground.git cd mcp-assistant-playground ``` ### 2. Set up virtual environment ```bash python -m venv .venv source .venv/bin/activate # or `.venv\Scripts\activate` on Windows ``` ### 3. Install dependencies ```bash pip install -r requirements.txt ``` ### 4. Set up environment variables Create a `.env` file in the root directory with the following variables: ```bash OPENAI_API_KEY=your_openai_api_key SUPABASE_URL=your_supabase_url SUPABASE_KEY=your_supabase_key ``` ### 5. Run the application ```bash python launch.py ``` ### 6. Access the chat interface Open your web browser and navigate to `http://localhost:8501`. ---