DevOps MCP Servers
by a37ai
This repository provides Model Context Protocol (MCP) server implementations for DevOps tools, enabling Large Language Models (LLMs) to interact with and automate DevOps systems. It offers a standardized way to control infrastructure, deployment pipelines, monitoring, and other DevOps operations.
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What is DevOps MCP Servers?
This is a collection of Model Context Protocol (MCP) server implementations designed for DevOps tools and platforms. These servers allow Large Language Models (LLMs) to interact directly with popular DevOps systems, providing a standardized way to automate and control various DevOps operations.
How to use DevOps MCP Servers?
Each server implementation includes its own README with detailed documentation on installation, configuration, and available tools. Navigate to the specific server directory for more information. Most servers require API credentials or tokens to interact with their respective services, often configured in a .env file. Refer to the individual server documentation for setup instructions.
Key features of DevOps MCP Servers
Comprehensive API integration with various DevOps platforms
Standardized interface for LLMs to interact with DevOps tools
Support for automating infrastructure, deployment pipelines, and monitoring
Individual server implementations with detailed documentation
Use cases of DevOps MCP Servers
Automating infrastructure provisioning and management
Orchestrating CI/CD pipelines using LLMs
Monitoring system performance and automatically responding to alerts
Managing and configuring various DevOps tools through a unified interface
FAQ from DevOps MCP Servers
What is MCP?
What is MCP?
Model Context Protocol (MCP) is a protocol that enables LLMs to interact with external systems and tools.
What DevOps tools are supported?
What DevOps tools are supported?
The repository includes MCP servers for Ansible Tower, Argo CD, Artifactory, AWS, Azure, Bitbucket Cloud, CircleCI, Consul, Datadog, Docker, Elasticsearch, GCP, GitHub, GitLab, Grafana, Jenkins, Kubernetes, New Relic, Nexus, Prometheus, and Puppet.
What are the common requirements for using these servers?
What are the common requirements for using these servers?
Common requirements include Python 3.7+, the FastMCP framework, service-specific API tokens or credentials, and required Python packages (install requirements.txt).
Where can I find more documentation?
Where can I find more documentation?
Each server implementation includes its own README with detailed documentation. You can also find documentation for the Model Context Protocol (MCP) and FastMCP Framework in the provided resources.
Will adding too many servers to the Claude config impact performance?
Will adding too many servers to the Claude config impact performance?
Yes, adding too many servers to the Claude config may result in performance decreases. Commenting out unnecessary tools will reduce the impact to performance.