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DevOps MCP Servers

MCP servers for DevOps tools and integrations. Created and maintained by the a37 team.

#docker#kubernetes
Created by a37ai2025/04/09
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What is DevOps MCP Servers?

What is DevOps MCP Servers? DevOps MCP Servers is a collection of Model Context Protocol (MCP) server implementations designed for DevOps tools and platforms, enabling Large Language Models (LLMs) to interact with popular DevOps systems for automation and control of infrastructure and deployment pipelines. How to use DevOps MCP Servers? To use the DevOps MCP Servers, navigate to the specific server directory in the repository, follow the README documentation for installation and configuration, and ensure you have the necessary API credentials set up in a .env file. Key features of DevOps MCP Servers? Integration with various DevOps tools like Ansible, AWS, Azure, Docker, and more. Standardized API interactions for automating DevOps operations. Comprehensive documentation for each server implementation. Use cases of DevOps MCP Servers? Automating deployment pipelines using Jenkins or CircleCI. Managing cloud resources on AWS or Azure. Monitoring infrastructure with Datadog or Prometheus. FAQ from DevOps MCP Servers? What programming language is used? The project is primarily developed in Python. Is there a license for this project? Yes, it is licensed under the MIT License. How can I contribute to the project? Contributions are welcome! Please refer to the GitHub repository for guidelines.

As an MCP (Model Context Protocol) server, DevOps MCP Servers enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

How to use DevOps MCP Servers

To use the DevOps MCP Servers, navigate to the specific server directory in the repository, follow the README documentation for installation and configuration, and ensure you have the necessary API credentials set up in a .env file. Key features of DevOps MCP Servers? Integration with various DevOps tools like Ansible, AWS, Azure, Docker, and more. Standardized API interactions for automating DevOps operations. Comprehensive documentation for each server implementation. Use cases of DevOps MCP Servers? Automating deployment pipelines using Jenkins or CircleCI. Managing cloud resources on AWS or Azure. Monitoring infrastructure with Datadog or Prometheus. FAQ from DevOps MCP Servers? What programming language is used? The project is primarily developed in Python. Is there a license for this project? Yes, it is licensed under the MIT License. How can I contribute to the project? Contributions are welcome! Please refer to the GitHub repository for guidelines.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.

Use Cases for this MCP Server

  • No use cases specified.

MCP servers like DevOps MCP Servers can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.

About Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like DevOps MCP Servers provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.

Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.