Enables AI agents to control serial port devices (modems, instruments, embedded boards) via MCP tools for listing ports, connecting, and sending/receiving commands.
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.
Provides LLMs with direct access to official vendor PDF documentation for electronics components (TI, ST, ADI) via a local SQLite full-text index and PDF retrieval tools.
Exposes tools for AI assistants to query a persistent SQLite+FTS5 index of C/C++ symbols parsed from real build commands, enabling sub-millisecond lookup, full-text search, and natural-language explanation without hallucination.
A Model Context Protocol (MCP) server for ROS 2 that enables GitHub Copilot and other AI agents to interact with ROS 2 systems. This server provides tools for monitoring, debugging, and managing ROS 2 nodes, topics, services, and TF2 frames.
A read-only MCP server for AI agents to understand KiCad projects through progressive disclosure, providing compact summaries and drill-down tools for components, nets, traces, and ERC/DRC checks without blowing context budgets.
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 AI assistants to communicate with serial port devices, supporting port management, data transmission in text/binary modes, interactive terminal sessions, and automatic reconnection.
Enables AI assistants to control Betaflight flight controllers over serial via MSP and CLI, providing real-time sensor reads, full CLI access, and auto-generated variable tools for configuration and tuning.
Serial communication and protocol analysis MCP server that gives AI coding assistants direct access to serial ports for reading, writing, decoding, and capturing embedded device output.
Provides tools to search and retrieve LILYGO hardware documentation, including product listings, full specs, and sectioned guides, with live fetching from GitHub.
Enables AI assistants to connect to and control the IAR C-SPY debugger through MCP tools, supporting session lifecycle, run control, breakpoints, memory inspection, stack and locals viewing, disassembly, symbol lookup, and terminal I/O capture.