"Amazon RDS" matching MCP servers:

Wraps the Amazon Q CLI to enable MCP hosts to interact with Amazon Q's AI capabilities for chat, command translation, and status checks.

Enables AI agents to run GDSII stream-out, KLayout DRC, Netgen LVS, and Magic extraction via MCP.

Gives Amazon Quick Desktop real shell access outside its sandbox, running commands as your own user with login-shell environment, synchronous execution, background jobs, process-tree cleanup on timeout, and an audit log. A narrow pattern-based guard blocks a handful of destructive commands while ordinary work — including targeted recursive deletes — passes through.

Enables management of multiple MikroTik RouterOS devices over SSH via two tools: device listing and command execution.

Enables controlling robots in ROS environments through natural language, supporting topics, services, actions, and GUI tools.

Facilitates robotic movement control by providing functions that enable precise manipulation of linear and angular velocities through natural language commands, compatible with both ROS and ROS2.

Enables MCP clients to drive a separately installed OrcaSlicer instance through a local stdio server, covering slicing jobs, profile and 3MF/settings editing, raw CLI options, artifact inspection and an optional desktop adapter for GUI actions. It also provides job queuing, status tracking and runtime detection of the installed binary's capabilities.

A Model Context Protocol server for ROS 2, enabling AI assistants to introspect and interact with ROS 2 systems.

Complete Google Ads API v21 MCP server with 40+ fully implemented tools for campaign, ad group, keyword, extension, and portfolio bidding management, enabling AI assistants to create, optimize, and manage Google Ads campaigns through natural language commands.

Enables large language models to interact with ROS robots seamlessly, allowing natural language control, real-time sensor monitoring, and autonomous task execution without modifying existing robot code.

Enables control of ROS/ROS2 robots through natural language commands by translating LLM instructions into ROS topics and services. Supports cross-platform WebSocket-based communication with existing robot systems without requiring code modifications.