"Building a Sequencer with Arduino in C++ and Enhancing Performance" matching MCP servers:

A local stdio MCP server wrapping arduino-cli to let agents detect boards, manage cores/libraries, compile and upload sketches, and communicate over serial, enabling hardware control without shell gymnastics.

A comprehensive Model Context Protocol (MCP) server for Arduino CLI interactions, built with FastMCP. This server enables AI agents to seamlessly interact with Arduino CLI for development, debugging, code verification, and more.

MCP server for Arduino IDE 2.0 sketches. It exposes a small REST API plus an MCP stdio bridge so agents can read and write the main .ino file, list sources, and optionally compile with arduino-cli.

Enables AI assistants to compile, upload, and monitor Arduino boards via natural language, with electrical safety checks and dependency management.

Enables AI clients to compile and upload Arduino sketches, manage boards, cores, and libraries via arduino-cli, scaffold projects, and read serial output over stdio.

Automates Arduino CLI workflows including dependency checks, compile/upload, serial monitoring, and safety preflight checks, all running locally on your machine.

Enables AI agents to detect boards, manage cores and libraries, compile and upload sketches, and perform serial I/O through a local MCP server.

Enables interaction with Arduino development through arduino-cli, allowing sketch management, code compilation and uploading, library and board operations, serial monitoring, and AI-powered circuit diagram generation using WireViz.

Enables AI agents to interact with Arduino boards for compiling, uploading sketches, and serial communication.

Enables AI assistants like Claude to control Arduino boards in real-time, allowing users to turn LEDs on and off through natural language commands using the Model Context Protocol and Firmata.

Enables AI assistants to build and simulate Tinkercad Circuits through a real Chrome session, including placing parts, wiring pins, writing Arduino code, running simulations, and reading serial output.

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

Enables AI agents and humans to control various hardware boards (ESP32, Arduino, Raspberry Pi, etc.) through a unified API via MCP, with real-time dashboard support.

MCP server for firmware verification in MCU development, exposing a five-stage pipeline (Detect, Review, Build, Flash, Verify) as tools for AI agents to compile, flash, and verify firmware on Arduino boards.

Enables planning Arduino/ESP32/Raspberry Pi robotics builds with correct pinouts, wiring diagrams, board references, and code skeletons based on verified component specs.

A fully local MCP server for Mixly that lets AI clients discover boards, scan blocks, build/validate/open projects, generate code, and compile via Arduino CLI—all without uploading source or relying on a remote server.

Provides AI agents with instant, structured access to electronic component datasheets, pinouts, and electrical specifications without requiring PDF uploads. It enables seamless part searching, design validation, and side-by-side component comparisons across major hardware providers.

An MCP server that lets an AI assistant manage your Keenetic router in plain language — list connected devices, pin static DHCP leases, rename devices, check WAN status, and reboot.

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.

Enables AI agents to control serial port devices (modems, instruments, embedded boards) via MCP tools for listing ports, connecting, and sending/receiving commands.