"MCP servers for full-stack development, DevOps, Supabase, QA, and AI agent orchestration" matching MCP servers:

Health doctor for a home AI stack (Ollama nodes, GPUs, tailnet) with graded confidence, as a CLI, an MCP server and a DSH plugin.

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.

Provides full Google Analytics 4 management and reporting capabilities via MCP, including property management, custom dimensions, audiences, events, data streams, and real-time reporting.

Enables AI agents to manage prompts and sessions via the ai-agent-logs API, with tools for health checks, login, listing/creating prompts, and retrieving sessions.

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.

Exposes read-only tools for OPC UA PLC tag monitoring and diagnostics, and enables template-driven, validated IEC 61131-3 SCL code generation with a mandatory human review gate before download.

A token-efficient MCP server for MySQL, PostgreSQL, and SQLite, providing tools to query databases, execute SQL, and analyze query performance.

Enables AI agents to analyze text and retrieve real-time system metrics such as CPU, memory, and uptime through LangChain tool calling, with an embedded web UI for testing queries and viewing tool execution logs.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

Monitors host CPU/RAM, local ports, and Docker containers, streaming live telemetry to a React dashboard over SSE. Exposes MCP tools to query system status, read environment logs, and execute remediation fixes via a local LLM agent.

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

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.

Checks vendor status pages, inspects SSL/TLS certificates, verifies DNS propagation, and provides incident-response playbooks. Includes 7 tools for DevOps health monitoring.

Enables real-time communication and orchestration of multiple AI agents with a web dashboard for monitoring agent activities, tasks, and artifacts.

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

Automates CI/CD pipeline control, PR review, Git operations, and monitoring/alerting with role-based access control.

MCP server that diagnoses Apache Spark job failures and optimizes performance using stack-trace analysis and LLM providers, supporting EMR and local sources.

AI-powered QA testing platform — catches JS errors, accessibility failures, visual regressions, API loops, security issues, and more via Chrome DevTools MCP

Registers a set of inert, tempting decoy tools with any MCP-capable client so that any call from a hijacked or prompt-injected agent instantly raises an alert with full attack context and a per-call trace token. Also plants worthless canary tokens in honeypot files that trigger zero-false-positive leak alerts when they surface in agent output, files, or outbound requests.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.