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MCP Daemon

@Pixeladed

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

Pixeladed

关于 MCP Daemon

Model Context Protocol Daemon - a tool for installing, running and managing MCP servers

#mcpd#model-context-protocol#server-management

MCP Daemon 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

MCP Daemon 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 Model Context Protocol Daemon?

Model Context Protocol Daemon is a tool for managing Model Context Protocol (MCP) servers. It allows users to quickly install new MCP servers, manage multiple instances, and perform related operations. It is currently a work in progress.

How to use Model Context Protocol Daemon?

The project is under development; a CLI binary can be built using PyInstaller. For development, create a Python virtual environment, install dependencies via Poetry, and run the project. The final CLI executable will be placed in a dist folder after building.

Key features of Model Context Protocol Daemon

  • Manage Model Context Protocol (MCP) servers
  • Quickly install new MCP servers (planned)
  • Manage multiple MCP server instances
  • Build Docker images for components
  • Fetch packages from GitHub
  • Run an MCP server

Use cases of Model Context Protocol Daemon

  • Centralized management of several MCP servers from a single daemon
  • Automating deployment of MCP servers via Docker images
  • Quickly fetching and testing MCP server packages from GitHub
  • Running multiple MCP server instances for different contexts

常见问题

1

What functionalities are currently implemented?

The project has implemented a protocol for components, building Docker images, fetching packages from GitHub, and running an MCP server.

2

What is still under development?

Installing MCP server packages, a local MCP server registry, and the CLI are not yet complete.

3

How can I set up the development environment?

Create a Python virtual environment (`python -m venv venv`), activate it, install Poetry, then run `poetry install` to install dependencies.

4

How do I build the CLI?

Use PyInstaller by running `pyinstaller cli.spec`. The executable will be created in a `dist` folder.

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