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    Enables AI agents to control serial port devices (modems, instruments, embedded boards) via MCP tools for listing ports, connecting, and sending/receiving commands.
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    MIT
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    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.
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    AGPL 3.0
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    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.
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    9 npm
    MIT
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    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.
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    MIT
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    MCP server that wraps STM32CubeMX CLI to let AI load .ioc projects, modify pin/peripheral configurations, generate HAL code, and export pinout tables.
    5
    88 PyPI
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    MIT
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    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.
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  • F
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    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.
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    This MCP server acts as a local stdio proxy for whatic.io's remote IC-discovery server, enabling MCP clients to search electronic components and retrieve part specs, comparisons, and images.
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    MIT
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    Enables MCP-compatible AI clients to operate a RIGOL MHO98 oscilloscope over USB, including configuration, waveform and measurement acquisition, FFT analysis, and protocol decoding.
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    MIT
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    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.
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    1,982 PyPI
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    Apache 2.0
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    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.
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    Apache 2.0
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    Enables AI assistants like Claude to directly debug microcontrollers via JLink, supporting breakpoints, single-step, memory/register access, variable inspection, RTT logging, and firmware flashing.
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    MIT
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    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.
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    Apache 2.0
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    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.
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    17 npm
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    MIT
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    Enables searching and retrieving native EMS registers, SunSpec models and points, and closed-loop control recipes for Wattsonic MATIC hybrid inverters, validating planned Modbus writes against the documentation, and generating client code. It provides documentation only and never connects to an inverter.
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    Apache 2.0
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    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.
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    MIT
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    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.
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    MIT
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    Enables AI assistants to flash firmware, program memory, modify option bytes, erase chips, reset boards, and capture SWO printf traces for STM32 microcontrollers via STM32CubeCLT.
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    MIT
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    An MCP server that enables AI agents to operate an oscilloscope through high-level tools like signal capture and measurement, abstracting vendor-specific SCPI commands.
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    MIT
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    Local serial and USB hardware access for coding agents, with typed YAML protocol commands, checksum validation, audited writes, lossless captures, hardware-free replay, and MCP App visualizations. Runs locally over stdio; live hardware use requires a serial device connected to the same machine.
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    MIT
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    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.
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    MIT
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    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.
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    MIT
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    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.
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    Enables AI assistants to operate a Fishball7020/PlutoSky software-defined radio, including tuning, spectrum analysis, band scanning, IQ capture, FPGA filtering, and optional transmission.
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    Enables AI coding assistants to perform complete headless STM32 embedded firmware development, including project creation, pin configuration, code generation, building, and flashing, by driving the official STM32 command-line toolchain.
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    MIT