"A command-line fuzzy finder" matching MCP servers:

A secure Model Context Protocol server that allows AI models to safely interact with Windows command-line functionality, enabling controlled execution of system commands, project creation, and system information retrieval.

Allows AI assistants to safely execute common Unix/macOS terminal commands through a controlled interface with comprehensive security features.

A flexible MCP server that enables users to define and execute arbitrary command-line tools through secure, JSON-based configuration files. It features parameter sanitization, directory scoping, and execution controls to safely integrate CLI utilities with Claude Desktop.

It enables AI assistants to run installed command-line tools and scripts, drive persistent terminals and browsers, and retrieve saved jobs, screenshots, and other evidence on a server. It also provides a dashboard for tracking sessions, installed tools, and connection settings.

Enables execution of shell commands, directory navigation, and interactive program automation through an enhanced command-line interface. Provides tools for running commands, managing working directories, and handling interactive programs using expect/send sequences.

MCP server for building and driving VMware Workstation VMs from an AI agent, enabling unattended OS installs, guest command execution, file transfer, screenshots, and fleet management.

A proxy server that enables AI assistants to run and interact with command-line applications like Expo through the Model Context Protocol (MCP), capturing logs and allowing keypress forwarding.

This server enables Claude to execute shell commands, read and edit files, and perform git operations on the host machine via a remote MCP endpoint.

A server implementation for the Model Context Protocol (MCP) that allows Claude AI to execute commands through a command-line interface, enabling direct system interactions from within Claude.

Secrets manager for AI coding agents. The model only sees secret names; values are injected into the child process at exec time, every command needs your approval in a native dialog, and output is redacted before it returns to the model.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Stateless command execution and process management MCP server for Claude. Enables searching file contents, executing commands with safety limits, listing processes, and terminating processes.

Interactive, streaming SSH tool for LLM agents that enables spawning long-running remote commands with live line-by-line output, signal handling, stdin input, and SFTP file transfer.

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

MCP server for managing remote servers via SSH, enabling command execution, file transfer, rsync, tunnels, health checks, backups, and database operations.

Provides read-only SSH access to network devices (routers, switches, firewalls) with command allow/deny policies, nt-templates output parsing, and an audit trail, enabling an AI agent to query device state securely.

Self-hostable remote terminal assistance over MCP. Agents create one-command connection invitations, execute commands, and manage interactive sessions on user-authorized macOS, Linux, and Windows computers without requiring an SSH daemon.

A Node.js/TypeScript MCP server that facilitates interactive communication between LLMs and users, allowing AI assistants to request user input, display notifications, and manage command-line chat sessions.

Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.

Enables managing multiple remote Linux hosts over SSH via MCP, with command execution, SFTP file operations, and Windows DPAPI-protected credentials.

A high-performance MCP server that manages persistent SSH sessions via a local tmux instance, enabling command execution, file transfer, and session monitoring for AI agents.

A persistent, stateful MCP server that exposes a detached tmux session to clients, enabling shell command execution, terminal buffer reading, and control signal sending via JSON-RPC over stdio.

Enables AI to execute registered system commands across platforms using a stable program + args interface, without requiring shell-specific syntax or tool discovery.

Offline server that explains any shell command token-by-token and flags destructive ones (rm -rf /, curl | sudo bash, dd/mkfs/shred to a disk device, chmod -R 777 /) — a safety gate for agentic shell execution.

Percival Ubuntu is a security-focused MCP server for safe Ubuntu operations, optimized for the Nanobot agent. It enables file management and command execution under strict security policies.

Provides comprehensive PC control capabilities including file operations (read, write, edit, delete), directory management, file search, and shell command execution through the Model Context Protocol.

An enhanced Model Context Protocol filesystem server that fixes common limitations and adds features like glob pattern search, head/tail reading, intelligent file editing with syntax validation, and new tools for delete and command execution.

Cross-platform MCP server for policy-controlled command execution on Linux and Windows, with no SSH dependency.

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.

MCP server for managing multiple SSH servers via AI assistants, offering tools for remote command execution, file operations, and system monitoring.