MCP Assistant Playground

@niawjunior

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

niawjunior

关于 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.

#gpt-4o#mcp-server #mcp-client

MCP Assistant Playground 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-assistant-playground": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

MCP Assistant Playground 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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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