nhivp/Awesome-Embedded

nhivp.github.io/Awesome-Embedded/

A curated list of awesome embedded programming.

embeddedmicrocontrollerlinux-programmingrtosraspberry-pibeaglebonefreertosbootloaderoperating-systemsautosartm4c123stm32
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feb 2018dic 2020oct 2023sept 2026
README

Awesome-Embedded

A curated list of awesome embedded resource.

Table of content

Interview

Embedded Software Skill

Common

MCU programming

General

  • McuOnEclipse - Everything about Eclipse, microcontrollers, software and tools.

Bare-metal programming (Don't need MCU)

MSP430

TM4C123

MSP432

STM32

STM32F7

STM8

ESP8266

Raspberry

Beaglebone

Linux kernel and device driver development

Assembly

RTOS

Automotive

OS

WindowCE

Compiler

Bootloader

Makefile

Peripheral

Memory Protection Unit

USB

  • tinyusb - An open source USB stack for a variety of Embedded Systems.

Others

Embedded GUI Development

  • Embedded Wizard - Sophisticated GUI for Your Embedded Platform
  • lvgl - Graphics library to create an embedded GUI with easy-to-use graphical elements, beautiful visual effects and low memory footprint. It offers anti-aliasing, opacity, and animations using only one frame buffer.

Machine Learning & AI on MCU

  • nnom - A higher-level Neural Network library for microcontrollers.
  • nn4mp
  • Embedded Learning Library (ELL) - Microsoft's library to deploy intelligent machine-learned models onto resource constrained platforms and small single-board computers.
  • Qualcomm Neural Processing SDK for AI - Libraries to developers run NN models on Snapdragon mobile platforms taking advantage of the CPU, GPU and/or DSP.
  • CMSIS NN - A collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Cortex-M processor cores.
  • ARM Compute Library - Set of optimized functions for image processing, computer vision, and machine learning.
  • uTensor - AI inference library based on mbed (an RTOS for ARM chipsets) and TensorFlow.
  • EmbededAI - A library that provides elements of AI to C++ applications.
  • kann - A lightweight C library for artificial neural networks.
  • m2cgen - A CLI tool which allows to transpile trained classic ML models into a native code of various programming languages with zero dependencies including C.
  • nn2 - Tiny zero-dependency neural network inference engine in pure C with hand-written SIMD kernels (AVX-512 / AVX2 / NEON). Runs the FaceX face recognition stack on Apple Silicon, ARM SBCs and ESP32-P4. Apache 2.0.
  • edge-agents (ForestHub) - Open-source (AGPL-3.0) 30 MB AI agent runtime for edge devices. Offline by default; GPIO/UART/MQTT as first-class nodes; local SLMs alongside cloud LLMs. Runs on Raspberry Pi 5, Jetson Orin Nano, STM32MP25, ctrlX CORE.
  • TiGrIS - Ahead-of-time compiler that tiles ONNX models to fit microcontrollers with fixed RAM and flash budgets, executed by a dependency-free C runtime.
  • voicute - Lightweight keyword spotting and wake word detection engine for ESP32 with INT8 quantization (~74KB per keyword), multi-language support including Chinese, and cross-platform ONNX Runtime inference.

Utilities

  • Jumpstarter - Open source hardware-in-the-loop testing framework for automated testing on real and virtual embedded hardware with CI/CD integration.
  • flashgate - Hardware-in-the-loop verification gate for AI coding agents: build, flash over ST-Link, then assert the board's boot banner, SWD RAM signature and console-probe register readbacks before "done" is accepted. Ships as a Claude Code plugin (Stop hook + MCP server).
  • lm4tools
  • EmbedEval - Benchmark that measures how well LLMs write embedded firmware. 233 cases across Zephyr, ESP-IDF, STM32 HAL, FreeRTOS, Linux drivers and Yocto, verified through static checks, SDK compilation, runtime execution and mutation testing.
  • mspdebug - Debugging tool for MSP430 MCUs
  • pycs - Python Based ARM CoreSight Debug and Trace Tools
  • NaiveSystems Analyze - Static Analysis Tool for Code Security and Compliance
  • CRA Kit SBOM - Zero-dependency CI script that reads Zephyr, Yocto, Buildroot, PlatformIO, ESP-IDF and STM32Cube build manifests and emits CycloneDX SBOMs.
  • Serial Studio - Visualize, analyze and stream over the internet data generated by your MCU project
  • Scrutiny Debugger - An open source debugging, visualization and testing tool for C/C++ embedded applications that works through instrumentation.
  • MemBrowse - Memory footprint tracking for ELF binaries with CLI and CI integration to monitor flash/RAM usage across commits.
  • aem-modbus-simulator - Open-source Python Modbus RTU/TCP slave simulator emulating an industrial DC voltage monitor (147 holding registers, 6 baudrates). Lets SCADA/PLC firmware engineers test Modbus integration in CI pipelines without physical hardware on the bench.
  • memprobe.dev - ELF firmware analysis as a web app, CLI, and GitHub Action. Break down flash and RAM usage by section, file, library, and symbol, compare builds, track project history and memory growth over time, and set CI size budgets.
  • SiliconRig - Cloud-hosted embedded boards (ESP32-S3, STM32, RP2350) for remote flashing, serial console, and hardware-in-the-loop testing in CI. Open-source CLI, Python SDK, and GitHub Action.
  • Velxio - Fully local, open source Arduino simulator with real AVR8, RP2040 and ESP32 emulation, a visual circuit canvas and an in-browser code editor. Runs in the browser or self-hosted via Docker.
  • BARR-C Enforcement Kit - Drop-in clang-format and clang-tidy configurations, compiler warning gates, a one-command conformance check and ready-made CI enforcing BARR-C, Barr Group's Embedded C Coding Standard for firmware.

Tips & tricks

Awesome Cheat Sheets for Developer Utility, like Git, Vim , Tmux, SublimeText, Markdown, Shell.

Tech blogs

FAQ_Embedded

Looking for more lists like this?

BOOKs

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

  • Fork the repository
  • Create your feature branch (git checkout -b feature/amazing-feature)
  • Commit your changes (git commit -m 'Add amazing feature')
  • Push to the branch (git push origin feature/amazing-feature)
  • Open a Pull Request
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