"Resources and Information on DevOps" matching MCP servers:

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.

Enables safe, local DevOps inspection through a JSON-lines server with schema validation, path isolation, and redaction, supporting read-only Git operations, Kubernetes YAML validation, Terraform plan summaries, and sanitized log analysis.

Enables AI assistants to perform DevOps tasks including Kubernetes management, cloud provider operations, CI/CD, security scanning, and infrastructure monitoring through natural language.

Enables DevOps Agent to troubleshoot VPC networking problems by running live probes (dig, nc, ping, traceroute) via SSM and querying VPC Flow Logs via Athena.

Enables AI-assisted DevOps by exposing scoped, role-based tools to inspect and remediate a Docker app stack, with audit logging and allow-listed commands for safe incident response.

Exposes DevOps/SRE operations like Kubernetes pod status, Prometheus metrics queries, and deploy history as tools for MCP-compatible clients.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

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.

Enables AI assistants to interact with local Docker containers, Kubernetes clusters, and system logs using the Model Context Protocol.

AI-powered assistant that connects Claude to video encoding workflows, translating cryptic errors into plain English and providing actionable solutions for troubleshooting encoding jobs.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

MCP server that enables DevOps infrastructure Q&A, providing tools to search infrastructure docs, look up hosts, and query logs.

Real-time GitHub Actions observability through VS Code with GitHub Copilot, providing DevOps metrics and interactive dashboards.

MCP server that diagnoses ML model regressions by correlating drift reports, eval runs, and deploy logs, providing evidence-cited incident reports through a set of investigation tools.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

A production-oriented reliability, benchmarking, and evaluation system that layers multi-version protocol negotiation, adaptive streaming, connection pooling, and resilience onto an MCP agent runtime.

Provides governed MCP tools for querying optionally restricted Microsoft Sentinel/Log Analytics tables and optional Defender XDR hunting data, retrieving incidents and entities, and—for agent identities only—adding attributed incident comments, with Entra ID authentication, KQL validation, rate limits, and redacted audit logging.

MCP server that wraps Drain3 for streaming log template mining, read-only matching, parameter extraction, and model persistence, exposing tools and resources to train on logs and query learned templates.