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MCP Key Server

@suchetaslalom-sf

基本信息

分类

其他

传输方式

stdio

作者

suchetaslalom-sf

关于 MCP Key Server

MCP server for storing API keys and providing npm installation

#mcp-key-server#api-keys#npm-installation

MCP Key Server 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-key-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

MCP Key Server 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 Key Server?

MCP Key Server is a Model Context Protocol (MCP) server for securely storing API keys and providing npm package installation capabilities. It includes user authentication and authorization, Docker containerization, and AWS deployment support.

How to use MCP Key Server?

Clone the repository, set up the backend with Python and the frontend with Node.js, then start services using docker-compose up -d. For local development, run python app.py in the backend directory and npm start in the frontend directory. AWS deployment is done via ./deploy.sh.

Key features of MCP Key Server

  • Secure API key storage and management
  • NPM package installation service
  • User authentication and authorization
  • Docker containerization
  • AWS deployment support

Use cases of MCP Key Server

  • Securely store and manage API keys in an MCP environment
  • Install npm packages through the MCP server
  • Authenticate and authorize users for access control

常见问题

1

What is MCP Key Server used for?

It securely stores API keys and provides npm package installation capabilities within the Model Context Protocol.

2

What are the dependencies?

Python 3.9+, Node.js 16+, Docker, and AWS CLI.

3

How can I run MCP Key Server locally?

You can run the backend with `python app.py` and the frontend with `npm start` or use Docker with `docker-compose up -d`.

4

How do I deploy to AWS?

Run `./deploy.sh` from the deployment directory.

5

What technology stack does it use?

React (frontend), Python (backend), PostgreSQL (database), Pydantic (data validation), Docker (containerization), and AWS (cloud).

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