"Resources and Information about DevOps Practices" matching MCP servers:

Provides structured DevOps practices and templates (tracking, documentation, runbooks) to streamline AI-assisted PoC development, reducing CLAUDE.md bloat and ensuring consistency across projects.

An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.

An MCP server designed to retrieve DevOps skills, code standards, and SAP Fiori documentation templates from a GitHub repository. It allows users to list available resources and fetch specific best practices to integrate directly into their development workflow.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

An MCP server for Azure DevOps work item management that enables AI assistants to create, query, update, and manage work items, sprints, and more.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Unified MCP server for DevOps engineers that provides real-time read and write access to Kubernetes, ArgoCD, Prometheus, and PagerDuty from any MCP-compatible AI agent.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Enables AI assistants to query and manage Azure DevOps projects, boards, work items, repos, pull requests, and pipelines while enforcing governance boundaries such as access modes, project scoping, protected projects, delete gating, and typed confirmations.

A Model Context Protocol (MCP) server for producing better Terraform through CLI analysis (tflint, checkov, trivy, kics, infracost), best-practice guidance from terraform-best-practices.com, cloud provider recommendations (Azure, AWS, GCP), and Terraform Registry resource and module guidance.

Enables automated deployments, environment management, snapshots, and deployment monitoring through DevOps Deploy's REST API.

An MCP server that connects Claude to video encoding workflows, enabling smart error translation, real-time job analysis, and automated email drafting for troubleshooting encoding issues.

Enables explicit multi-account routing to Azure DevOps Services for managing projects, repositories, pull requests, work items, and pipelines with isolated credential profiles and strict scoped tools.

Enables AI agents to execute read-only DevOps operations including kubectl, terraform, helm, docker, and AWS cost analysis through natural language.

Enables AI assistants to interact with an on-premise Azure DevOps Server 2022, allowing users to list, view, create, and update work items through natural language.

Enables searching ServiceNow's public best-practices library across content types without authentication.

Enables AI assistants to monitor and manage Linux infrastructure including services, logs, processes, disk, memory, ports, cron, nginx, Docker, and system health checks via the Model Context Protocol.

Production-ready, zero-knowledge AI DevOps deployment, infrastructure provisioning, self-healing execution, and persistent documentation engine for VPS servers.

Enables querying local MySQL databases and managing Docker containers (listing, logs) through natural language via the Model Context Protocol.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.