"Information about network devices" matching MCP servers:

Enables AI agents to query a verified, sourced knowledge base about NVIDIA Jetson devices via the Model Context Protocol, with every claim cited and knowledge gaps explicitly stated.

Connects AI assistants to physical devices via MCP, enabling LLMs to reason about sensor data, perform cross-device correlation, and interpret anomalies.

An MCP server that lets an AI assistant manage your Keenetic router in plain language — list connected devices, pin static DHCP leases, rename devices, check WAN status, and reboot.

Enables AI agents to control serial port devices (modems, instruments, embedded boards) via MCP tools for listing ports, connecting, and sending/receiving commands.

MCP server that lets LLMs talk to serial devices: microcontrollers, routers, modems, embedded Linux, anything with a UART.

Standalone TypeScript MCP server for micrOS devices. Enables discovering devices, inspecting device cache, running micrOS commands, and discovering each device's available module commands.

Enables controlling multiple USBTMC (USB Test and Measurement Class) devices simultaneously using SCPI commands through a unified MCP interface.

Enables LLMs to communicate with hardware devices via serial ports. Provides tools for listing ports, opening/closing connections, reading/writing data, and controlling serial signals.

Enables MCP clients to drive a LEGO Mindstorms EV3 over Wi-Fi SSH, with tools for movement, turning, stopping, beeping, and listing connected devices. Includes a CLI chat client that translates natural language into robot commands via Hugging Face Inference Providers.

Provides an MCP knowledge base and tools for porting LuneOS to Android devices, covering kernel porting, boot images, GSI building, Yocto bring-up, nyx-modules, and a staged debugging playbook.

Enables AI agents to interact with physical embedded target boards over a dual-CDC USB bridge using MCP tools. It exposes console reading, pattern waiting, command sending, reboot/login state machines, and in-RAM MicroPython execution while a single-owner daemon safely arbitrates access to the serial devices.

An MCP server that enables AI assistants to control Siglent SDS oscilloscopes over a local network using SCPI commands. It allows users to measure signals, configure channel and acquisition settings, and capture waveforms or screenshots through natural language.

Enables LLMs to interact with embedded devices by reading and writing Segger RTT data through a J-Link debugger.

Enables AI agents to search a catalog of MCP servers for physical hardware such as ESP32, Arduino, Raspberry Pi, 3D printers, Home Assistant devices, cameras, Zigbee and lab gear, returning install commands and ready-to-paste client configs. It also supports browsing device families and getting ranked recommendations for a specific device or model.

Enables management and control of OpenWrt devices via a simple API, including reboot, status checks, log reading, and LED control.

MCP server for managing large fleets of BLE devices with connection pooling, scheduling, retries, and partial-failure handling. Enables AI agents to run fleet-level reads/writes without worrying about radio connection limits.

Allows AI agents to interact with serial devices via RS232/UART, enabling port listing, connection, read/write, control line manipulation, and protocol specification for automated debugging and testing.

MCP server that lets AI assistants control Siglent SDG waveform generators over a local network using natural language, supporting signal generation, modulation, sweep, burst, and arbitrary waveforms.

A stateful Bluetooth Low Energy (BLE) MCP server that enables AI agents to scan, connect, read/write characteristics, and subscribe to notifications on BLE devices.

Enables AI agents to perceive and quantitatively verify physical hardware through USB webcams and RTSP/HTTP network streams, returning inline image content plus numerical metrics such as brightness, contrast, edge density, motion, SSIM baseline comparisons, and OCR text. Agents can watch feeds for visual conditions, correlate buffered frames with serial/log/MQTT events, and apply privacy masks and access controls.