"Managing Kubernetes Clusters on AWS Elastic Beanstalk" matching MCP servers:

An MCP server for managing AWS ECS clusters, services, tasks, and container logs. Enables AI assistants to perform operations like scaling, deployments, and log retrieval via natural language.

A Model Context Protocol server that integrates with AWS CodePipeline, allowing users to manage pipelines through Windsurf and Cascade using natural language commands.

A boilerplate TypeScript MCP server with Express.js designed for AWS AppRunner deployment. Provides sample tools, resources, and prompts with Docker containerization and GitHub Actions CI/CD workflow.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

Enables natural language management of GitHub Actions Runner Controller (ARC) in Kubernetes clusters. Supports automated installation, scaling, monitoring, and troubleshooting of GitHub Actions runners through conversational AI commands.

Enables AI assistants to interact with Argo CD applications, managing clusters, applications, and resources through natural language.

An MCP server for managing Modal — apps, containers, volumes, and secrets — and for deploying & running Modal apps directly from Claude Code and other MCP clients.

Enables AI agents to audit Kubernetes manifests for configuration traps that pass linters but silently break production, via read-only tools to audit YAML, list known traps, and explain trap details.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

Uptime monitoring your AI agent can set up: create HTTP, SSL, ping, TCP and DNS monitors checked from multiple regions, run checks on demand, read and acknowledge incidents, manage cron heartbeats, maintenance windows and status page updates.

MCP server that audits npm dependencies against the live registry, providing per-dependency reports on versions behind, deprecation, and license.

Before you move to Python 3.15 (or 3.15t), find every dependency with no wheel for it on your platforms — and the bump that fixes it. CLI, GitHub Action, MCP server.

Enables LLMs to migrate Docker Compose applications to Kubernetes, including inspection, planning, manifest generation, validation, deployment with approval, verification, and diagnosis.

A production-ready MCP server for Jenkins that enables managing jobs, pipelines, builds, and nodes through natural language, with configurable security and guardrails.

Enables AI agents to manage Google Play Console reviews and Android app releases, including replying to reviews, promoting releases, managing staged rollouts, and checking crash/ANR vitals.

An MCP server providing comprehensive Gitea API coverage with 186 tools for managing repositories, issues, pull requests, and CI/CD workflows. It enables autonomous AI agents to perform complex development and administrative tasks directly through a Gitea instance.

Enables AI coding agents to deploy and manage full multi-service applications on Constructor from a single request, covering image builds, service configuration, start/stop lifecycle, logs, and file syncing on research desks. It handles browser-based sign-in and token renewal automatically so agents can inspect deployments and report results without manual setup.

MCP server for Bitbucket Cloud that enables reviewing, managing, and merging pull requests, assigning reviewers by name, reading files at a ref, and inspecting pipeline status from any MCP client.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Lets coding agents manage apps in App Store Connect through workflow-level tools: shipping TestFlight builds, managing testers and groups, editing listings, replacing and reordering screenshots, handling subscriptions, replying to reviews, downloading sales reports, and submitting for App Review. It is read-only unless writes are explicitly enabled, and destructive actions run as dry runs until confirmed.

repo-release-tools mcp-server automates the software release process by managing version bumps, changelog generation, and releases. It streamlines repository maintenance by handling repetitive release tasks directly through your AI assistant.

Enables management of Railway.app infrastructure through natural language, including deploying services from GitHub repos or Docker images, managing environment variables, monitoring deployments, and configuring networking and volumes.

Enables coding agents to build, test, archive, and run iOS apps on a remote Mac fleet from any environment, with XcodeBuildMCP-compatible tools and live simulator access.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Enables AI clients to deploy static sites, track deployments, and manage sites on a Shiplo account through the Model Context Protocol.