What is MCP?
MCP (Model Context Protocol) by Anthropic is an open standard that connects AI applications to tools and data sources, allowing large language models to understand and use tools securely without hard‑coding.
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基本情報
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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。
This project simulates three approaches to installing an Nginx server: a traditional manual method, an automated installation using Anthropic’s Model Context Protocol (MCP) via a GitHub MCP server running in Docker, and a simulated collaborative setup using Google’s Agent2Agent Protocol (A2A). It is designed for DevOps engineers who want to explore how MCP and A2A can simplify and automate infrastructure workflows.
Install prerequisites: Python 3.x, Docker, Visual Studio Code and the Copilot Plugin. Configure MCP by creating a JSON file with a GitHub Personal Access Token and running the github-mcp-server Docker container. Open Copilot in VSCode, set mode to Agent, and allow the MCP agent to automate the Nginx installation. The project also includes standalone scripts for the manual installation (install_nginx.sh, nginx_install.py) and the A2A simulation (a2a_simulation.py).
MCP (Model Context Protocol) by Anthropic is an open standard that connects AI applications to tools and data sources, allowing large language models to understand and use tools securely without hard‑coding.
A2A (Agent2Agent Protocol) by Google is an open protocol enabling AI agents from different vendors to discover, communicate, and collaborate on complex tasks.
Python 3.x, Docker, Visual Studio Code, and the Copilot Plugin are required. A GitHub Personal Access Token is needed for the MCP configuration.
Go to GitHub Settings → Developer settings → Personal access tokens and generate a token with appropriate permissions. Paste it into the Copilot input field when prompted.
The manual and A2A methods are simulated; only the MCP method uses a real connection (via the Docker‑based GitHub MCP server) to automate the installation process.
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