"Resources or information on analysis techniques or methods" matching MCP servers:

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

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.

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.

Enables MCP-compatible AI clients to operate a RIGOL MHO98 oscilloscope over USB, including configuration, waveform and measurement acquisition, FFT analysis, and protocol decoding.

Enables lossless parsing, inspection, validation, simulation, and creation or editing of FATEK .ldr ladder-logic files through local stdio MCP tools, including a user-import-verified start/stop template. New files are written to an artifacts directory so existing files and original samples are never overwritten.

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.

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 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.

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 Android Automotive developers to explore and implement Vehicle Hardware Abstraction Layer (vHAL) properties with intelligent tools for property analysis, source code lookup, implementation guidance, and automated code generation for automotive systems like climate control and seat management.

Enables AI agents to start or attach to Lauterbach TRACE32 PowerView, inspect embedded targets, run PRACTICE commands and scripts, read window output, and control target execution.

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 Claude Code sessions to control a Rigol DS1054Z oscilloscope over USB, reading identity, settings, measurements, screenshots and waveforms, and applying undoable or destructive changes such as channel, timebase, trigger and acquisition configuration, run control, autoscale and reset. Tool calls come with read-only and destructive hints so safe operations can be auto-approved while risky ones stay behind user approval.

Enables AI assistants to operate a Fishball7020/PlutoSky software-defined radio, including tuning, spectrum analysis, band scanning, IQ capture, FPGA filtering, and optional transmission.

A local MCP server that connects Claude Code or any MCP-compatible AI assistant to a Robonine robot arm.

Enables LLMs to control RIGOL oscilloscopes over SCPI via LAN or USB, including configuring channels/timebase/trigger, taking measurements, capturing waveforms and screenshots, decoding serial protocols, running FFT analysis, and controlling the built-in AFG.

MCP server for controlling CNC machines via Universal GCode Sender. Lets Claude (or any MCP-compatible AI assistant) connect to a CNC machine, inspect G-code, and issue motion commands — all through the UGS Pendant REST API.

Enables AI assistants to query a verified bilingual technical knowledge base for the Thermia Duo 12 heat pump and verify facts against original manuals via section search, terminal and register lookup, schematic access, and PDF page rendering or text extraction.

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

Enables AI tools to perform full-featured embedded microcontroller debugging via pyOCD and CMSIS-DAP probes, including probe management, flashing, breakpoints, register/memory access, fault analysis, and RTT communication.

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.

Enables AI agents to control a tinySA spectrum analyzer over USB, discovering the device, capturing or scanning spectra, configuring RBW/attenuation/units, and finding peaks, with CSV and JSON exports. It runs headless with automatic port detection and no GUI or network listener.

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 agents to discover and manage Raspberry Pis and other SSH devices on a LAN, including authentication, command execution, file and directory operations, reboots, and ctrlPi API installation.

Enables an AI agent to control one or more remote GPIO agents through a conversation by proxying tool calls to their REST APIs. It supports API-key authentication, LAN discovery, and both stdio and Streamable HTTP transports.

A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.

Enables agents to observe a desktop and perform mouse and keyboard actions through ESP32-based BLE or USB HID hardware, with local action translation and no second model in the MCP path.

Enables MCP clients to list serial ports, open sessions, send firmware commands, read and filter output, and safely flash STM32 or ESP32 boards with explicit confirmation and allow-listed firmware paths.

Enables AI agents to debug embedded systems by providing a comprehensive interface for GDB operations across multiple architectures like ARM and x86. It supports remote debugging via gdbserver or QEMU, allowing for detailed inspection of memory, registers, stack frames, and variables.

Provides read-only retrieval of STM32 datasheet and reference manual content with exact citations, page numbers, register details, and source hashes so Claude can answer questions or generate code from verified evidence.

Enables LLMs to control a Nordic Power Profiler Kit II over USB serial for current capture (500 nA–2000 mA at 100 kSa/s plus 8 logic channels) and DUT power sourcing (0.8–5 V), with samples written to npz files. Also supports offline analysis such as statistics, activity/duty-cycle segmentation, and battery-life estimation.

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-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 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.