💬 MCP Assistant Playground
@niawjunior
About 💬 MCP Assistant Playground
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.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-assistant-playground": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is 💬 MCP Assistant Playground?
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.
How to use 💬 MCP Assistant Playground?
Clone the repository, set up a Python 3.10+ virtual environment, install dependencies from requirements.txt, create a .env file with OPENAI_API_KEY (and optionally SUPABASE_URL and SUPABASE_KEY), then run python launch.py and access the chat interface at http://localhost:8501.
Key features of 💬 MCP Assistant Playground
- Natural language tool selection using GPT-4o
- MCP tool execution via fastmcp
- Real-time image generation with DALL·E 3
- Text-to-speech synthesis (GPT-4o mini TTS)
- Supabase integration for member CRUD operations
- Streamlit UI with image and audio rendering
Use cases of 💬 MCP Assistant Playground
- Chat with GPT and generate images on the fly
- Query and manage Supabase database members via natural language
- Create text-to-speech audio from conversational prompts
- Experiment with AI-driven tool routing and confirmation flows
FAQ from 💬 MCP Assistant Playground
What are the prerequisites?
Python 3.10+ is required. You need an OpenAI API key; a Supabase project is optional for member tool features.
How do I start the application?
Clone the repository, set up a virtual environment, install dependencies, create a .env file with your keys, and run python launch.py. Then
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