"How to deploy Docker on a server through SSH" matching MCP servers:

Enables LLMs to interact with remote servers via SSH, supporting command execution, file upload/download, and directory listing.

SSH MCP is a Model Context Protocol tool for managing and interacting with multiple virtual machines over SSH. It simplifies executing commands on remote servers using the standard SSH config file format.

More than just an MCP server that covers the entire range of Docker management tasks, it helps you create workflows to easily manage your Docker environments at scale. It allows you manage multiple local or remote (TCP, TLS, SSH) docker instances and exposes things like logs and stats as resources so that you can monitor and triage all of them.

Enables AI assistants to execute shell commands and transfer files via SFTP across remote servers using existing SSH configurations. It supports parallel execution on server groups and provides built-in safety warnings for potentially destructive commands.

Enables AI agents to establish and manage persistent SSH sessions, supporting smart command execution, async tasks, multi-host, sudo, and file operations through SFTP.

An MCP server that gives AI agents SSH access to remote machines through your local OpenSSH client, enabling remote command execution, file transfer, persistent shell sessions, and port forwarding.

MCP server for remote Linux/Unix server management via SSH, enabling command execution, system monitoring, file operations, and diagnostics through natural language.

Enables natural language control of SSH servers, allowing users to execute commands, manage files, view logs, deploy applications, and more through AI-driven conversations.

An MCP server for SSH connections through JumpServer, supporting persistent sessions, multiple bastions, and hot-reload configuration.

Enables reading, writing, editing, searching, running commands, transferring files, and using git on a remote Linux server over SSH via MCP tools.

Enables AI coding tools to read, write, search, and list files on remote machines and run commands there, including background long-running jobs and TTY-based interaction, all through a single persistent SSH connection. Bypasses the cost of establishing a new SSH session on every call, cutting typical multi-step remote operations from seconds to milliseconds.

Enables managing Docker containers and Docker Compose projects on Synology NAS via SSH, with auto-privilege escalation and full compatibility with Synology Container Manager.

轻量级跨平台 SSH MCP 服务器，复用本地 SSH 配置实现远程命令执行、文件传输和主机管理。

DEPRECATED — succeeded by SSH-Connect (Rust rewrite): https://github.com/mixelpixx/SSH-Connect

Enables AI models to access and manage SSH connections through a standardized interface, allowing AI assistants to perform SSH operations like connecting to servers, executing commands, and managing files.

Enables MCP-compatible AI clients to remotely manage a Linux server via SSH, supporting file operations, Docker control, Git pulls, and arbitrary command execution.

MCP server for managing SSH connections to remote servers, providing host registry, session pool, and secure command execution with read-only protection.

Enables coding agents on Windows clients to operate on Unix file servers through one long-lived SSH session per host, running exec/view/create/edit/grep/glob with POSIX paths and shell state (cd, env) persisting across calls. Bypasses slow or flaky SMB/CIFS mounts entirely, giving native-speed file operations without drive letters or remounts.

Enables Claude Code and ChatGPT Codex to run commands directly over SSH on multiple Debian and Red Hat servers, with automatic failover, parallel sessions, background jobs, and journalctl event watchers.

Enables running commands and uploading or downloading files on multiple preconfigured remote servers through stdio MCP, using password or private-key authentication and host-key trust policies. No local Go, ssh, or scp installation is needed, with prebuilt binaries selected automatically across macOS, Linux, and Windows.

The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.

Provides MCP clients with a persistent SSH shell on legacy Unix hosts, including session management, SFTP file transfer, and ClearCase workflow helpers.

An MCP server enabling Claude to execute commands on multiple remote servers via SSH and transfer large files (40GB+) with resume support via SFTP.

An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.

Exposes MCP tools that let DeepSeek Harness agents list configured remote hosts, run shell commands on a Linux server with a chosen working directory and timeout, and upload or download files over SFTP. Results return stdout, stderr, exit codes, and timeout markers so the agent can act on remote machines as if they were local workspaces.

Provides persistent SSH access to servers using OpenSSH ControlMaster multiplexing, allowing AI agents to run commands on registered hosts by name without re-entering credentials.

Enables agents to execute shell commands and upload/download files on remote Linux hosts over SSH/SFTP with just two tools, returning structured, verifiable results such as exit codes, separated stdout/stderr, timeout and truncation flags, and the current working directory. Supports connection reuse, host alias resolution, host-key verification, and cross-call session state so multi-step work needs fewer calls.

MCP server for SSH remote execution, file transfer, and file editing with automatic backup/trash and ~/.ssh/config integration.

Enables AI agents to SSH into Linux servers, run commands, deploy code, and manage servers via natural language, also doubles as a CLI for manual use.

An MCP server that allows managing Docker containers through natural language, enabling users to compose, introspect, and debug containers without running commands themselves.