"Amazon Web Services" matching MCP servers:

Enables natural language command control of robots via ROS2, with a web portal for real-time visualization and interaction.

A headless MCP server that enables AI tools (like Claude Code) to read and analyze serial logs from embedded boards (ESP32, STM32) for firmware debugging, with read-only tools for log retrieval and a built-in web viewer.

AI-powered FPGA power estimation assistant that wraps Xilinx PDM API as MCP services for natural language power modeling and analysis.

A Model Context Protocol (MCP) server for ROS 2 that enables GitHub Copilot and other AI agents to interact with ROS 2 systems. This server provides tools for monitoring, debugging, and managing ROS 2 nodes, topics, services, and TF2 frames.

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

Enables MCP-speaking coding agents to talk directly to Home Assistant and the ESPHome dashboard: discovering entities and areas, reading live states, history and logs, rendering Jinja templates, calling services, and creating, editing or triggering automations and dashboards. Also allows ESPHome device configs to be read, validated, compiled and flashed, with all write operations off by default behind an explicit safety policy.

Enables LLM coding agents to inspect, control, and verify remote ROS2 robotics applications without a local ROS2 installation, supporting topics, services, actions, parameters, TF transforms, and automated test suites.

Build, deploy, and debug Smart TV web apps on Samsung Tizen and LG webOS TVs from any AI agent.

Enables local MCP clients to run Sailfish OS device, SDK, OBS, and Android/AppSupport development workflows via typed tools for SSH access, screenshots, touch injection, builds, logs, services, and repository checks.

This MCP server enables AI models to interact with ESP32 devices, providing built-in tools for web search, note management, calculator, and custom tools like todo lists and timers.

Enables AI-powered automotive diagnostics by connecting LLMs to vehicle ECUs over UDS/CAN, indexing workshop manuals locally, and augmenting with web search, while enforcing a human-in-the-loop approval gate for any write operations.

Enables humans and AI agents to collaboratively control serial ports via MCP tools or Web UI, with real-time data sharing across all participants.