Toolbox - MCP Server Manager

Name: Toolbox - MCP Server Manager
Author: AlexanderOllman

@AlexanderOllman

リポジトリ

Toolbox - MCP Server Manager について

Agnostic MCP server addition for FastAgent

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

AlexanderOllman

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Toolbox - MCP Server Manager?

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.

How to use Toolbox - MCP Server Manager?

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.

Key features of Toolbox - MCP Server Manager

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

Use cases of Toolbox - MCP Server Manager

Centralizing and managing multiple MCP server repositories
Automatically generating MCP configuration files from repository metadata
Searching through MCP server repositories using semantic similarity
Maintaining a local catalog of MCP servers with automatic documentation extraction

FAQ from Toolbox - MCP Server Manager

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.

Where is repository data stored and how is it managed?

Repository data is stored in a Qdrant vector database. The connection parameters can be configured in the Vector Settings section of the application.

What CLI tools are available and how do I use them?

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.

Is the OpenAI API key handled securely?

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.