"How to run Docker and view logs" matching MCP servers:

Enables MCP-compatible AI agents to deploy and manage applications on Google Cloud Run, including service deployment, listing, logging, and project creation.

Enables MCP-compatible AI agents to deploy applications to Google Cloud Run by providing tools for deploying code, listing services, and managing Google Cloud projects.

MCP server for GitHub Actions — view workflow runs, read logs, re-run failed jobs, and manage CI/CD.

Connects AI assistants to GitHub Actions workflows to monitor CI/CD pipelines, view run logs, diagnose failures, and optionally trigger or manage workflows with granular permission controls.

Hosted remote MCP server for issuing run receipts, summarizing agent changes, checking test evidence, flagging review risks, and exporting run logs for Antigravity agents.

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.

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.

An MCP server that provides Azure DevOps integration for AI assistants, enabling them to list projects, run pipelines, analyze failures, view logs, and troubleshoot builds directly from chat interfaces.

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

Enables users to manage Travis CI builds, view logs, compare builds, and get insights through natural language.

MCP server with the watch_ci tool that polls GitHub Actions until a commit's CI run finishes, then returns the outcome and failed log tail in one call.

Provides disposable email inboxes for AI agents to automatically receive and extract OTPs and magic links, enabling seamless email verification during autonomous workflows.

A Model Context Protocol server for Bitbucket Cloud that lets agents read pull request diffs, comments, and pipeline logs, as well as write PR comments and edit PR details.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

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.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

MCP server that lets Claude diagnose failed GitHub Actions runs by fetching and parsing CI logs into structured failure signals, enabling natural-language questions like 'Why did the last run fail?'.

Provides coding agents read-only access to Depot's CI failure diagnoses, container build forensics, run history, cache effectiveness, registry contents, and usage data through MCP tools.

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

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp