This MCP server provides a productivity framework for DevOps engineers using AI assistance to streamline the development of proof-of-concept projects by centralizing reusable DevOps instructions.
From the registry: Productivity framework for DevOps engineers using AI assistance (Claude Code) while working on PoCs
Please install the `devops-practices` MCP server into my current AI client (that's you).
Canonical MCP server config (stdio transport):
- command: `uvx`
- args: ["devops-practices-mcp"]
Note: DevOps practices framework for Claude Code. Also available from clone-and-run (python3 mcp-server.py) — uvx is the simplest canonical path.
Add this MCP server to my current client's config in the correct format for you. If you need secrets or credentials I haven't provided, ASK me — do not invent values or leave raw placeholders. After adding it, tell me how to verify the server is connected.PYTHONUNBUFFEREDrequiredEnsures real-time logging for debuggingReal-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Persistent codebase knowledge graph. Survives session restarts and context compaction.
Validate oh-my-posh configurations and segment snippets against the official schema.