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    Turbo Mcp Client

    A FastAPI-based application that provides a web interface for interacting with Multiple Control Protocol (MCP) servers while utilizing OpenAI's API for processing messages.

    1 stars
    Python
    Updated Apr 24, 2025

    Table of Contents

    • Overview
    • Tech Stack
    • Features
    • Screenshots
    • Installation
    • Environment Variables
    • Configuration
    • Usage
    • Usage
    • Project Structure
    • API Endpoints
    • Contributing
    • Support
    • License

    Table of Contents

    • Overview
    • Tech Stack
    • Features
    • Screenshots
    • Installation
    • Environment Variables
    • Configuration
    • Usage
    • Usage
    • Project Structure
    • API Endpoints
    • Contributing
    • Support
    • License

    Documentation

    Turbo MCP Client 🚀

    A FastAPI-based application that provides a web interface for interacting with Models Context Protocol (MCP) servers while utilizing OpenAI's API for processing messages.

    Overview

    This application allows users to:

    • Connect to multiple MCP servers simultaneously
    • Process messages through OpenAI's API
    • Interact with the system via a web-based chat interface
    • Configure and store API license keys

    Tech Stack

    Client: html, css, js, bootstrap, animatedjs

    Server: FastAPI, Openai, MCP

    Features

    • Connect multiple servers at a time
    • Use websocket any where you want

    Screenshots

    App Screenshot

    App Screenshot

    Installation

    1. Clone the repository:

    bash
    git clone https://github.com/techspawn/Turbo-MCP-Client.git
       cd openai-mcp

    2. Install dependencies:

    bash
    uv pip install -r requirements.txt

    3. Set up your environment variables:

    bash
    export MODEL_NAME="gpt-4o" # or your preferred OpenAI model

    Environment Variables

    To run this project, you will need to add the following environment variables to your .env file

    MODEL_NAME=gpt-4o

    Configuration

    1. Create a config.json file in the root directory:

    json
    {
         "mcpServers": {
           "server1": {
             "command": "your_command",
             "args": ["arg1", "arg2"]
           },
           "server2": {
             "command": "another_command",
             "args": ["arg1", "arg2"]
           }
         }
       }

    2. Initialize the SQLite database:

    python
    import sqlite3
    
       conn = sqlite3.connect("mcp_config.db")
       cursor = conn.cursor()
       cursor.execute("CREATE TABLE IF NOT EXISTS config (license_key TEXT)")
       conn.commit()
       conn.close()

    3. Configure your OpenAI API key through the web interface.

    Usage

    1. Start the application:

    bash
    uvicorn main:app --reload

    2. Open your browser and navigate to http://localhost:8000

    3. Enter your OpenAI API key in the web interface to save it to the database

    4. Use the chat interface to send messages that will be processed through the MCP servers and OpenAI

    Usage

    1. Start the application:

    bash
    uvicorn main:app --reload

    2. Open your browser and navigate to http://localhost:8000

    3. Enter your OpenAI API key in the web interface to save it to the database

    4. Use the chat interface to send messages that will be processed through the MCP servers and OpenAI

    Project Structure

    code
    ├── images/                    # Directory for storing image assets
    │   ├── chat_window.png        # Screenshot of the chat window
    │   └── setting_page.png       # Screenshot of the settings page
    ├── models/                    # Contains Python modules related to data models
    │   ├── __init__.py            # Makes the 'models' directory a Python package
    │   ├── client.py              # Defines client-related logic (e.g., API client, user handling)
    │   ├── config.py              # Handles application configuration settings
    │   └── py.typed               # Indicates that this package supports type hints
    ├── static/                    # Placeholder for static assets (CSS, JavaScript, images)
    ├── templates/                 # Directory for HTML templates
    │   ├── base.html              # Base template for consistent layout across pages
    │   ├── chat.html              # Template for the chat interface
    │   └── settings.html          # Template for the settings page
    ├── .env                       # Environment variables (e.g., API keys, credentials)
    ├── .gitignore                 # Specifies files to be ignored by Git
    ├── .python-version            # Defines the Python version for this project
    ├── config.json                # JSON configuration file for application settings
    ├── database.py                # Handles database connection and operations
    ├── folder_structure.txt        # Text file describing the project structure
    ├── LICENSE                    # License file specifying usage terms
    ├── main.py                     # Entry point of the application
    ├── mcp_config.db               # SQLite database file or config storage
    ├── pyproject.toml              # Python project metadata and dependency management
    ├── README.md                   # Project documentation and setup instructions
    ├── requirements.txt            # List of required dependencies
    └── uv.lock                     # Lock file for package versions (possibly from `uv` or another package manager)

    API Endpoints

    • GET /: Main chat interface
    • POST /get_settings: Save OpenAI API license key
    • WebSocket /chat: Real-time chat communication

    Contributing

    Contributions are always welcome!

    See contributing.md for ways to get started.

    Support

    For support, email support@techspawn.com

    License

    MIT

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