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MCP Daemon

@Pixeladed

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基本情報

カテゴリ

その他

トランスポート

stdio

作者

Pixeladed

MCP Daemon について

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

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

MCP Daemon の設定

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

MCP Daemon のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

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 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

よくある質問

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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