"Extracting Images from Search Results" matching MCP servers:

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

Enables AI agents to capture high-quality screenshots from running QEMU virtual machines using the QEMU Machine Protocol (QMP), automatically discovering VMs and returning screenshots as PNG images.

Enables LLMs to search Docker Hub repositories, discover container images, and manage Docker Hub repositories and tags through natural language queries. Supports both public content access and authenticated operations with Docker Personal Access Tokens.

Provides Docker management tools for AI agents, including inspecting containers, images, Dockerfiles, and Compose configurations.

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 AI assistants to search, analyze, and manage Docker images on Docker Hub through standardized MCP tools, with features including security scanning, layer analysis, and image comparison.

Exposes Arcane's Docker-management API (containers, images, volumes, networks, Compose projects, environments, system) as MCP tools over Streamable HTTP, with automatic tool generation from the live OpenAPI spec and confirmation for destructive operations.

Enables users and AI assistants to search LinuxServer.io images, audit Compose and docker run configurations, research image requests, validate service specifications, generate Dockerfile/Compose/README scaffolds, and access guidance and best-practice checklists.

Enables running ephemeral Kubernetes Jobs/pods with caller-chosen images and commands, returning results and artifacts while automating cleanup. Supports synchronous and background execution, repository cloning, and strict security controls.

MCP server for Podman and Docker container runtimes, enabling management of containers, images, networks, and volumes via AI assistants.

Automatically installs and containerizes MCP servers from GitHub repositories using MCP sampling to analyze repositories and create appropriate Docker images.

A production-ready Model Context Protocol (MCP) server that provides comprehensive DockerHub integration for AI assistants. This server enables AI assistants to search, analyze, and manage Docker images through standardized MCP tools.

Enables secure Docker command execution from isolated environments like containers through MCP protocol. Provides tools for managing Docker containers, images, and Docker Compose services with security validation and async operation support.

Enables AI assistants to manage Docker containers, images, networks, and services through the Portainer API.

A code-mode MCP server for the Unraid 7.2+ GraphQL API that exposes search and execute tools, allowing LLM agents to introspect and call any GraphQL field via sandboxed JavaScript.

Enables AI coding agents to safely execute commands, run tests, and modify project files inside disposable, policy-enforced Docker sandboxes that are isolated from the host machine and its credentials.

Enables coding agents to deploy and manage game server containers on Edgegap, from creation through player connection, without manual API reference.

TypeScript stdio MCP server for operating Docker-based local-ydb deployments from AI coding agents. Supports local and SSH-backed profiles, bootstrap, diagnostics, auth hardening, schema permissions, storage workflows, dump/restore, upgrades, and plan-first mutating operations.

Enables AI coding assistants to search local log files, inspect Docker containers, and clean up JSON payloads through a local stdio MCP server.

Enables MCP-aware agents to read and explore Oracle Cloud Infrastructure — listing, fetching, and searching across 39 resource types spanning Identity, Compute, Block Volume, Networking, Object Storage, and OKE. Runs locally over stdio using credentials from ~/.oci/config, with fail-closed safety gates and audit logging governing future write operations.

Enables MCP clients to rent GPUs from ParalonCloud using natural language, including browsing available GPUs, starting and stopping rentals, and retrieving connection URLs.

Enables management of LunaNode VPS resources including VMs, images, volumes, floating IPs, SSH keys through natural language with tiered safety controls.

Manage Docker infrastructure across multiple homelab hosts including Unraid, Proxmox, and bare metal servers. Enables container lifecycle management, log retrieval, resource monitoring, and Docker operations across your entire homelab from a single interface.

Control and automate FlexSim simulations through AI assistants like Claude, enabling manufacturing and warehouse digital twin analysis, parameter studies, and real-time model manipulation via tools for opening models, running simulations, evaluating FlexScript, and exporting results.

Enables AI assistants to run shell commands, read, write, edit, search, and stream files on remote SSH servers and Docker containers, including nested multi-layer chains, without installing any runtime on the target hosts. It auto-injects a self-contained Go helper with adaptive zstd compression for fast transfers and process control.

Enables AI agents to run CP/M, MP/M, and DOS packages on Z80/x86 emulators, inspect byte-exact results and files, and debug the emulators themselves over the Model Context Protocol.

MCP server for securely discovering, pricing, renting, connecting, and releasing GPU compute instances from AI Galaxy with budget checks and two-phase approval.

Docker container, image, volume, network, and compose management from your AI assistant.

Enables AI agents to manage WSL containers and images via the wslc CLI, supporting container lifecycle, network, volume, and registry operations through natural language.

An MCP server that enables AI assistants to manage Docker containers, images, networks, and volumes through a standardized interface. It supports comprehensive operations like container lifecycle management and image pulling while ensuring correct handling of command and environment variable arrays.