"Server compatibility with ChatGPT or DeepSeek" matching MCP servers:

An MCP server for source-grounded, page-cited evidence retrieval tailored for embedded and firmware development, returning verbatim snippets with exact citations or 'no match' to prevent fabrications.

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

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.

An MCP server for Nordic nRF Connect SDK development that enables users to list, read, and search documentation and sample code from the nrfconnect/sdk-nrf repository. It provides Claude with specialized tools to navigate SDK resources, source files, and configuration examples directly through the GitHub API.

An MCP server that provides AI coding assistants with access to official ARM CMSIS SVD hardware register definitions for microcontrollers. It enables precise querying of register names, bit positions, and addresses to prevent hallucinations during embedded systems development.

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.

Reverse engineer Windows-only USB gadgets: capture vendor-app traffic, infer the protocol with frame-level evidence, and generate an open Python/pyusb driver. Replay needs human confirmation.

Enables AI agents to compile, flash, erase, and read serial output from embedded development boards, with guardrails such as budget limits, serial port mutexes, and mandatory human confirmation for destructive operations.

Provides AI coding tools with queryable documentation for the AK (Active Kernel) event-driven MCU framework, including API signatures, guides, and guardrails.

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.

Local, read-only MCP server for inspecting DBC files and decoding CAN capture logs, with bounded and composable tools.

Provides LLMs with direct access to official vendor PDF documentation for electronics components (TI, ST, ADI) via a local SQLite full-text index and PDF retrieval tools.

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.

Enables AI agents to design hardware by writing C-like HDL and compiling it to Verilog, with real toolchain verification including synthesis checks.

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.

MCP server for interacting with NI DAQ hardware, supporting analog/digital I/O and waveform acquisition, with safety features and simulation mode.

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

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.

Enables secure, read-only inspection and validation of KiCad PCB boards through MCP, with deterministic routing and optional AI policy plugins.

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.