"Information about Docker software and containerization" matching MCP servers:

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

Enables Claude to function as a full-stack software engineer with comprehensive development capabilities including project creation, database management, frontend/backend development, testing, deployment, and DevOps operations across multiple frameworks and technologies.

Manages Docker containers, images, and Compose stacks on a remote host over SSH, with file sync and deploy orchestration.

A comprehensive MCP server that provides advanced Docker operations through a unified interface with 16 MCP tools and 25+ CLI aliases, enabling secure container lifecycle management, multi-container orchestration, registry publishing, and system maintenance.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

Provides tools and slash commands to onboard developers and manage DevOps workflows including Git operations, Docker containerization, GitHub Actions CI/CD, GitHub Container Registry, SonarCloud code analysis, and Azure container deployments.

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.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Enables AI agents to retrieve the latest semantic version tags for container images from Docker Hub, GHCR, Quay, and other OCI registries, allowing them to pin specific versions for reproducible deployments.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

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 scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

Autonomous coding pipeline exposed as an MCP server: plan, dispatch, review, and merge software stories through worktree-isolated agents. A frontier model (Claude) handles judgment — planning, review, risk adjudication — while a local model does the implementation, gated by TDD and a merge-time test rerun on the rebased branch.

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

Enables Claude to run structured software development pipelines by directing it through sequential phases, validating evidence before advancing, and persisting state in SQLite for resumption across sessions.

Checks whether software dependencies (npm packages, GitHub Actions, MCP servers, Docker images) are alive, dormant, abandoned, archived, or deleted using dated observations from lastseen.dev.

Enables AI agents to enforce a software delivery standard by validating artifacts against declarative rules, providing templates, glossary terms, and pass/fail verdicts with actionable blockers.

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.