What are the main dependencies to run Toolbox - MCP Server Manager?
Python 3.8+, Node.js 18+, Git, an OpenAI API key, and a Qdrant vector database instance.
@AlexanderOllman
Basic information
Agnostic MCP server addition for FastAgent
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"Toolbox": {
"command": "python",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
Clone the repository, set up the backend (Python 3.8+, install dependencies, run python run.py on port 8020) and frontend (Node.js 18+, install dependencies, run npm run dev on port 5173). Use CLI tools like add_server.py to add Git repositories or cli.py to generate YAML configs.
Python 3.8+, Node.js 18+, Git, an OpenAI API key, and a Qdrant vector database instance.
Repository data is stored in a Qdrant vector database. The connection parameters can be configured in the Vector Settings section of the application.
Two tools: `add_server.py` (adds Git repositories to the database) and `cli.py` (generates YAML configs, lists repositories). Run them from the backend directory with appropriate arguments.
The README notes that the API key is currently hardcoded in `backend/app/services/openai_service.py` and recommends using an environment variable in production.
The API is served via HTTP on port 8020, with Swagger UI and ReDoc documentation. No authentication mechanism is mentioned in the README.
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