What is Mcp Assistant Playground

mcp-assistant-playground is a Streamlit-based chatbot interface that utilizes OpenAI’s GPT-4o to intelligently route user inputs to various custom MCP tools, including GPT chat, image generation, Supabase queries, and text-to-speech functionalities.

Use cases

Use cases for mcp-assistant-playground include providing automated customer service responses, generating images based on user descriptions, performing database queries for user management, and converting text to speech for accessibility purposes.

How to use

To use mcp-assistant-playground, clone the repository, set up a virtual environment, install the required dependencies, configure environment variables with your OpenAI and Supabase credentials, run the application, and access the chat interface via your web browser at http://localhost:8501.

Key features

Key features include natural language tool selection using GPT-4o, MCP tool execution via fastmcp, real-time image generation with DALL·E 3, text-to-speech audio synthesis, Supabase integration for member CRUD operations, and a Streamlit UI for rendering tool results.

Where to use

mcp-assistant-playground can be used in various fields such as customer support, educational tools, creative content generation, and any application requiring intelligent interaction with users through AI-driven tools.

💬 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

git clone https://github.com/niawjunior/mcp-assistant-playground.git
cd mcp-assistant-playground

2. Set up virtual environment

python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

3. Install dependencies

pip install -r requirements.txt

4. Set up environment variables

Create a .env file in the root directory with the following variables:

OPENAI_API_KEY=your_openai_api_key
SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key

5. Run the application

python launch.py

6. Access the chat interface

Open your web browser and navigate to http://localhost:8501.