"Information on Unreal Engine" matching MCP servers:

Check 22,000+ devices with open firmware or open protocols (OpenWrt, LineageOS, coreboot, Zigbee2MQTT, Tasmota…) before reverse engineering one; claim a device while you work on it and publish your findings when done.

Enables controlling a Dirtywave M8 over USB by reading its screen as text, pressing buttons, playing notes, and retrieving system information through MCP tools.

Agentic Hardware-in-the-Loop (Agentic HIL) lets coding agents develop firmware on real embedded boards: flash, reset, read UART and exchange CAN traffic, diagnose and fix. Local, policy-gated MCP tools support OpenOCD, pyOCD and STM32CubeProgrammer, with pytest for CI.

Enables MCP clients to discover connected gadgets, read their state and events, and route commands to them over versioned device contracts on local USB and TCP transports. Ships with a configurable software simulator so device interactions can be exercised without physical hardware.

Enables Claude to create, update, and manage LED patterns on a PixelBlaze controller, including setting brightness and reading device info, through a set of tools that interact with the device's API.

Lets LLM clients control a persistent AMD/Xilinx Vivado TCL session on Windows, avoiding repeated startup cost with native process handling.

AI-driven USB oscilloscope control via FastMCP, enabling waveform capture, CSV export, and frequency measurements on PicoScope, Hantek, or a built-in simulator.

Enables AI agents to control an ESP32 board's relays, GPIO pins and analog sensors over a small HTTP API on the local network, with no cloud service in the middle.

Enables AI agents to control and display real-time notifications, telemetry, and custom apps on Ulanzi TC001 and compatible pixel clocks running Awtrix Light, including device management and declarative YAML-based metric polling.

Enables AI coding agents to run a SystemVerilog LSP for linting, formatting, navigation, rename, RTL hierarchy inspection, and automated RTL code actions on real projects.

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.

An MCP server that enables AI agents to read serial output from devices by buffering lines in the background and allowing polling for new output, preventing blocking on long-running serial monitors.

Enables MCP-capable agents to drive a real FPGA toolchain end to end—simulating, asserting, synthesizing, scanning JTAG, capturing on-chip waveforms, and configuring real silicon behind confirmation gates.

Exposes ISO 14229 Unified Diagnostic Services as MCP tools, letting any MCP client run session control, DID reads and writes, DTC queries, routine control, security access and raw requests against a real ECU on a CAN bus or against a built-in simulator. A claim/release access model lets multiple clients safely share one device under test, with hardware-free simulation for offline test-plan development.

Enables AI agents to debug STM32 firmware on real hardware by driving GDB with OpenOCD/ST-Link/J-Link to flash, set breakpoints, inspect memory, registers and RTOS state, triage HardFaults, and profile. Returns decoded, structured evidence and suggested next actions instead of raw GDB text, with composite tools that collapse multi-step debug loops into single calls.

Automates Arduino CLI workflows including dependency checks, compile/upload, serial monitoring, and safety preflight checks, all running locally on your machine.

Talk to your Flipper Zero from Claude Code — or any MCP client. Storage, app deployment, screen capture, button automation, JavaScript execution on the device, and honest answers about what is nearby.

Let an AI agent drive up to 12 hobby servos on an open-hardware USB-C controller (Pololu Maestro compatible): moves, named poses, sequences, on-board scripts and rail current/voltage readout, with per-channel travel limits and overcurrent guardrails. Includes a --mock emulator, so it runs without the board.

An MCP server that judges hardware behavior against timing or serial contracts, returning pass/marginal/fail verdicts for coding agents to iterate on real signal measurements.

Enables MCP clients to connect to and interact with Siemens PLCs via python-snap7, supporting read/write operations on data blocks, memory, timers, counters, and CPU management.

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

Read-only MCP server that lets AI assistants (Claude Code, Claude Desktop, VS Code, ...) inspect Altium Designer projects — schematics, netlist, BOM and PCB — on Linux, macOS or Windows, without Altium Designer installed.

Enables LLM agents to operate on KiCad by reading compressed schematics (TOON format), executing atomic tools, and updating context via delta and local area.

Serial terminal with a GUI that AI assistants drive over MCP: read device logs and send commands.

Enables AI coding assistants to drive Xilinx Vivado through natural language, letting users open .xpr projects, run synthesis, implementation, and bitstream generation, inspect timing, resource, and clock reports, and launch simulations to read signal values or set breakpoints. It also exposes design hierarchy queries and arbitrary TCL execution, so FPGA design flows can be operated conversationally on Windows.

MCP server for running shell commands on a Linux development board via UART serial.

Enables AI clients to create, configure, validate, and generate STM32CubeMX projects through 113 MCP tools, including pin, clock, peripheral, RTOS, and middleware setup plus C code generation. It can drive an installed CubeMX engine or run fully standalone using a bundled data pack with real pin and mode validation.

Enables AI agents to build, flash, and debug STM32 projects compiled with Keil MDK-ARM on Windows, returning structured UV4 build diagnostics and evidence-based results. It also provides pyOCD/ST-Link debugging operations such as run control, breakpoints, register/PC reads, and global/static variable inspection.

Enables an AI agent to drive a Beckhoff TwinCAT 3 setup end to end: read and write live PLC variables and system state over ADS, manage files and processes on the target IPC, build and edit projects through the XAE automation interface, capture and analyze long-running signal recordings, run scripted test benches and TcUnit suites, and look up the official Beckhoff Infosys documentation. Runs as a single Python process on the engineering PC with read-only, guarded, and full safety modes plus human-in-the-loop confirmation for destructive operations.

Enables agents to work with local hardware engineering context — registered repositories, imported PDFs and documents, and user-created system diagrams — through stdio tools for bounded source search and file reading, document text extraction and PDF page/crop rendering, and reading or drafting system architecture models. It runs entirely on local storage with no code index, hosted backend, or model provider routing, leaving the agent's own model, keys, and permissions intact.