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Overview

The MAX Microcontrollers SDK (MSDK), now a part of Analog Devices, contains the necessary software and tools to develop firmware for the MAX32xxx and MAX78xxx Microcontrollers. That includes register and system startup files to enable low-level development for its supported parts. It also provides higher-level peripheral driver APIs (written in C) alongside various utilities, third-party libraries, Board Support Packages (BSPs), and a set of example programs for each microcontroller.

Additionally, the MSDK includes a GCC-based toolchain, and builds are managed by a system of Makefiles (see GNU Make). A custom fork of OpenOCD enables flashing and debugging. The MSDK's toolchain and build system offers a Command Line Interface (CLI), and project files for supported development environments are maintained that build on top of that CLI.

This document describes the MSDK's installation, setup, and usage.

Supported Operating Systems

  • Windows (Windows 10 only)

  • Linux (Ubuntu only)

  • MacOS

Supported Parts

The MSDK officially supports the following microcontrollers and evaluation platforms.



  • MAX32572 (Not Yet Publicly Available)
    • MAX32572EVKIT (Not Yet Publicly Available)


  • MAX32651: Ultra-Low-Power Arm Cortex-M4 with FPU-Based Microcontroller (MCU) with 3MB Flash and 1MB SRAM



  • MAX32660: Tiny, Ultra-Low-Power Arm Cortex-M4 Processor with FPU-Based Microcontroller (MCU) with 256KB Flash and 96KB SRAM


  • MAX32662: Arm Cortex-M4 Processor with FPU-Based Microcontroller (MCU) with 256KB Flash and 80KB SRAM



  • MAX32670: High-Reliability, Ultra-Low-Power Microcontroller Powered by Arm Cortex-M4 Processor with FPU for Industrial and IoT


  • MAX32672: High-Reliability, Tiny, Ultra-Low-Power Arm Cortex-M4F Microcontroller with 12-Bit 1MSPS ADC


  • MAX32675: Ultra-Low-Power Arm Cortex-M4F with Precision Analog Front-End for Industrial and Medical Sensors


  • MAX32680: Ultra-Low-Power Arm Cortex-M4F with Precision Analog Front-End and Bluetooth LE 5.2




  • MAX78002: Artificial Intelligence Microcontroller with Low-Power Convolutional Neural Network Accelerator


Supported Development Environments

Supported Languages

  • C
  • C++
  • Assembly (Arm and/or RISC-V instruction set depending on the microcontroller)