Toolbox - MCP Server Manager

by AlexanderOllman

137 downloads Not rated yet
GitHub

About

A web application for managing MCP servers and generating configuration files, featuring a FastAPI backend and React frontend. It automatically extracts repository information using GPT, supports YAML and JSON config generation, and provides vector-based search via Qdrant.

Explore

- Repository management (add, view, delete)
- Automatic extraction of information from README files using GPT
- YAML and JSON configuration generation
- Modern UI with React and Tailwind CSS
- Command-line tools for repository management and config generation
- Vector-based search for repositories

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Toolbox - MCP Server Manager
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

- Python 3.8+
- Node.js 18+
- Git
- OpenAI API key
- Qdrant vector database (for repository storage and search)

1. Navigate to the backend directory:

cd backend

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run the FastAPI server:

python run.py

The API will be available at http://localhost:8020.

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

The web application will be available at http://localhost:5173.

This tool provides functionality to manage the configuration:

python backend/cli.py generate-yaml

Available commands:
- generate-yaml: Generate a YAML configuration file
- -o, --output: Specify the output file path
- -p, --print: Print the YAML to stdout
- list: List all repositories in the database

--name

Custom name for the repository

--description

Custom description for the repository

--command

Custom command for running the repository

--args

Custom arguments for the command

generate-yaml

Generate a YAML configuration file

list

List all repositories in the database

A web application for managing MCP servers and generating configuration files.

The application includes two command-line tools:

This tool allows you to add Git repositories to the database:

python backend/add_server.py https://github.com/username/repo.git

Optional arguments:
- --name: Custom name for the repository
- --description: Custom description for the repository
- --command: Custom command for running the repository
- --args: Custom arguments for the command

This tool provides functionality to manage the configuration:

python backend/cli.py generate-yaml

Available commands:
- generate-yaml: Generate a YAML configuration file
- -o, --output: Specify the output file path
- -p, --print: Print the YAML to stdout
- list: List all repositories in the database

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "toolbox - mcp server manager": {
            "Toolbox": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    "venv"
                ]
            }
        }
    }
}

McpServers

{
    "Toolbox": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            "venv"
        ]
    }
}

A web application for managing MCP servers and generating configuration files.

Features

- Repository management (add, view, delete)
- Automatic extraction of information from README files using GPT
- YAML and JSON configuration generation
- Modern UI with React and Tailwind CSS
- Command-line tools for repository management and config generation
- Vector-based search for repositories

Project Structure

The project is divided into two main parts:

- Backend: FastAPI server for API endpoints
- Frontend: React application with Tailwind CSS

Prerequisites

- Python 3.8+
- Node.js 18+
- Git
- OpenAI API key
- Qdrant vector database (for repository storage and search)

Getting Started

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run the FastAPI server:

python run.py

The API will be available at http://localhost:8020.

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

The web application will be available at http://localhost:5173.

API Documentation

Once the backend is running, you can access the API documentation at:

- Swagger UI: http://localhost:8020/docs
- ReDoc: http://localhost:8020/redoc

Command-Line Tools

The application includes two command-line tools:

Add Server Tool

This tool allows you to add Git repositories to the database:

python backend/add_server.py https://github.com/username/repo.git

Optional arguments:
- --name: Custom name for the repository
- --description: Custom description for the repository
- --command: Custom command for running the repository
- --args: Custom arguments for the command

Configuration Tool

This tool provides functionality to manage the configuration:

python backend/cli.py generate-yaml

Available commands:
- generate-yaml: Generate a YAML configuration file
- -o, --output: Specify the output file path
- -p, --print: Print the YAML to stdout
- list: List all repositories in the database

Development Notes

- The OpenAI API key is hardcoded in backend/app/services/openai_service.py. In a production environment, this should be replaced with an environment variable.
- Repository data is stored in Qdrant vector database. Make sure your Qdrant instance is properly configured and backed up regularly.
- Qdrant connection parameters can be configured in the Vector Settings section of the application.

License

MIT

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