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.
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.
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.
All-in-one developer tool and MCP Server for Roku development, featuring ECP device control, automated channel sideloading, BrightScript debugging, and real-time log monitoring.
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.
AI-driven USB oscilloscope control via FastMCP, enabling waveform capture, CSV export, and frequency measurements on PicoScope, Hantek, or a built-in simulator.
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.
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.