"How to execute custom code in a Linux Docker container" matching MCP servers:

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

A powerful Python-based Model Context Protocol (MCP) server that enables AI assistants to manage remote Linux machines over SSH directly from your chat interface.

Enables LLMs to execute shell commands and perform file operations on a Linux system, exposing tools like execute_command, read_file, write_file, and more.

Provides AI assistants with the ability to control Linux desktop environments through tools for file management, application launching, and system operations like clipboard access. It includes a multi-level security model to manage permissions for safe, elevated, and restricted actions.

Exposes a Linux host with shell, Python, and filesystem tools as MCP tools over HTTPS, enabling AI agents to execute commands and manage files remotely.

AI-powered MCP server for file renaming, organization, and PDF splitting using natural language prompts and content analysis.

A comprehensive MCP server with 30+ custom tools organized into categories: date/time operations, file management, system information, text processing, and web operations. Enables async communication with robust error handling and flexible CLI integration.

Remote Linux operations via SSH, exposed as an MCP server, with tools for filesystem, systemd, Docker, network, and more, using per-user AD authentication and optional sudo elevation.

Enables secure execution of shell commands and file operations within isolated Docker containers. Provides process management, interactive input handling, and comprehensive file system operations for containerized development environments.

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

An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

An experimental MCP server that enables AI assistants to interact with VS Code workspaces through file operations, code execution, and Git management. It also provides tools for Docker integration, project scaffolding, and secure command execution using project-specific configurations.

A comprehensive MCP server that provides AI assistants with tools for file system management, Git integration, and shell command execution. It features specialized code utilities for analysis, formatting, and linting to enhance development workflows within Claude Desktop.

Enables file reading with pagination and regex-based code search across a codebase using grep.

Enables Claude AI to run terminal commands, perform file operations, and manage git in a project directory via the Model Context Protocol.

Safe local MCP server for Windows to list, read, search, patch, backup, and verify code files in allowed folders, with Git integration and dry-run diffs.

Enables saving files and folders to a local NAS over NFS with automatic share discovery, smart mounting, and seamless file transfers.

Gives a Microsoft Copilot Studio agent Claude-Code-style tools to read, edit, search, and run shell commands against your local filesystem.

A containerized MCP bridge that lets local or cloud LLMs access your filesystem and perform web searches via Ollama and FastMCP.