What is Cloudbrain Mcp

cloudbrain-mcp is a suite of Model Context Protocol (MCP) servers designed to facilitate the integration and automation of various DevOps tools and technologies, enabling AI assistants to interact with modern infrastructure and deployment processes.

Use cases

Use cases for cloudbrain-mcp include automating Helm chart operations in Kubernetes, orchestrating CI/CD pipelines with tools like Jenkins and ArgoCD, managing cloud resources with Terraform, and implementing monitoring solutions with Prometheus and the TICK stack.

How to use

To use cloudbrain-mcp, developers can install the specific MCP servers relevant to their DevOps tools and workflows. Each server provides a standardized interface for AI agents to automate tasks, manage resources, and streamline operations across different environments.

Key features

Key features of cloudbrain-mcp include modular design for extensibility, standardized interfaces for various DevOps tools, support for Kubernetes package management, CI/CD automation, cloud orchestration, and observability and monitoring solutions.

Where to use

cloudbrain-mcp can be used in various fields including software development, cloud infrastructure management, continuous integration and delivery, and monitoring and observability of applications and services.

CloudBrain MCP Servers

A suite of Model Context Protocol (MCP) servers for DevOps tools and technologies, enabling AI assistants and automation to interact with modern infrastructure and deployment technologies.

This repository serves as the central hub for all MCP servers built to support a wide range of DevOps tools and workflows. Each MCP server provides a standardized interface for AI agents and automation platforms to interact with specific tools, services, or platforms, making it easier to integrate, automate, and extend DevOps operations across diverse environments.

• Kubernetes Package Management: For managing Kubernetes workloads, the Helm MCP Server enables AI-driven Helm chart operations and best practices.
• CI/CD, Build & Release: Dedicated MCP servers (e.g., ArgoCD MCP Server, Jenkins MCP Server) will provide automation and orchestration for continuous integration, delivery, and deployment pipelines.
• Cloud Orchestration: To manage cloud resources across providers, there will be MCP servers for tools like Terraform and Terragrunt, supporting AWS, Azure, Google Cloud, and more.
• Observability & Monitoring: For monitoring and observability, specialized MCP servers will be available for Prometheus, the TICK stack (Telegraf, InfluxDB, Chronograf, Kapacitor), and other monitoring solutions.

The vision for CloudBrain MCP Servers is to offer a modular, extensible, and unified platform where each DevOps domain—whether infrastructure as code, CI/CD, cloud orchestration, or observability—can be managed through a dedicated MCP server. This approach empowers AI assistants and automation tools to deliver intelligent, context-aware DevOps workflows, regardless of the underlying technology stack.

Table of Contents

• CloudBrain MCP Servers
  • Table of Contents
  • Available Servers
    • Helm MCP Server
    • ArgoCD MCP Server
  • Installation and Setup
  • Contributing
  • License

Available Servers

Helm MCP Server

A Model Context Protocol (MCP) server for managing Kubernetes workloads via Helm, inspired by EKS MCP and Terraform MCP architectures.

• Helm Best Practices
  • Prescriptive guidance for Helm chart usage and deployment
  • Security and compliance recommendations for Kubernetes workloads
  • Multi-cluster and context-aware operations
• Helm Operations
  • Install, upgrade, list, uninstall Helm releases
  • Search public Helm repositories (ArtifactHub, GitHub, etc.)
  • Pass complex/nested values, multiple values files, and extra CLI flags
  • Robust error handling and logging
• Multi-Cluster Support
  • Switch between clusters via kubeconfig, context, or EKS cluster name
  • Generic, production-ready Kubernetes authentication
• Documentation and Resources
  • Access Helm best practices and workflow guides as MCP resources
  • Rich metadata for Helm charts and repositories

Learn more

ArgoCD MCP Server

A Model Context Protocol (MCP) server for managing Kubernetes applications and resources via ArgoCD using GitOps principles.

• GitOps Best Practices
  • Prescriptive guidance for ArgoCD application management
  • Security and compliance recommendations for Kubernetes workloads
  • Automated sync and self-healing capabilities
  • Comprehensive resource monitoring and management
• ArgoCD Operations
  • Create, update, delete, and sync applications
  • Manage application resources and their lifecycle
  • Retrieve logs, events, and resource actions
  • Robust error handling and logging
• Resource Management
  • Get resource trees and managed resources
  • Retrieve workload logs and events
  • Execute resource actions
  • Monitor application health and status
• Documentation and Resources
  • Access ArgoCD best practices and workflow guides
  • Rich metadata for applications and resources
  • Comprehensive error handling and logging

Learn more

Installation and Setup

Each server has specific installation instructions.
See each server’s detailed README for specific requirements and configuration options.

Contributing

Contributions are welcome! Please open an issue or pull request on the project repository.

License

This project is licensed under the Apache-2.0 License.