# Automated deployment

The Pulumi MCP Server is a service that implements the Model Context Protocol (MCP) and interacts with the Pulumi CLI through the Pulumi Automation API and the Pulumi Cloud API, enabling clients to perform infrastructure operations without directly installing the Pulumi CLI.

1Panel MCP Server is an experimental project for automatically deploying websites to 1Panel servers through the Model Context Protocol (MCP) standard protocol, supporting website creation and static file upload.

This project demonstrates how future DevOps engineers can use the MCP and A2A protocols to simplify workflows, improve efficiency, and automate complex tasks by installing Nginx in three ways: manual simulation, MCP, and A2A.

An MCP service for automated GitHub repository creation and Vercel template deployment, supporting team collaboration, zero-configuration deployment, and secure credential management.

This is a project for managing and deploying MCP servers, including configuration files, scripts, and automated tools, supporting monitoring and performance optimization.

A service tool for installing other MCP servers, supporting the installation of Node and Python versions of MCP servers through npm or PyPi.

The Azure Policy MCP Server project aims to help LLM generate, validate, and deploy custom Azure policies by providing a toolset, including policy discovery, structural validation, deployment management, and compliance query functions.

GitHub Actions automated workflow configuration, including version update and NPM package publishing functions

The Cloudflare MCP service is a standardized protocol based on the Model Context Protocol (MCP) for managing context interactions between large language models (LLMs) and external systems. This project provides an installer and an MCP server, supporting the management of various resources in a Cloudflare account, such as Workers, KV storage, R2 storage, and D1 databases, through natural language instructions. Users can perform various operations in a Cloudflare account using natural language via MCP clients such as Claude Desktop, VSCode (Cline), and Windsurf.

This project demonstrates a test repository that interacts with the GitHub API through the GitHub MCP server, showcasing repository creation, file operations, and search functions.

Guide to setting up the SUSE AI demonstration environment. Deploy Rancher Fleet and the SUSE AI stack through a K3s cluster, and integrate the MCP service and Open-WebUI to achieve Kubernetes interaction functions.