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    Enables AI assistants to interact with physical serial port devices across platforms (Windows COM/Linux tty) with support for asynchronous communication, URC pattern recognition, and structured logging.
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    An MCP server that enables AI assistants to control Siglent SDS oscilloscopes over a local network using SCPI commands. It allows users to measure signals, configure channel and acquisition settings, and capture waveforms or screenshots through natural language.
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    MIT
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    MCP server for controlling CNC machines via Universal GCode Sender. Lets Claude (or any MCP-compatible AI assistant) connect to a CNC machine, inspect G-code, and issue motion commands — all through the UGS Pendant REST API.
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    MIT
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    Enables AI tools to perform full-featured embedded microcontroller debugging via pyOCD and CMSIS-DAP probes, including probe management, flashing, breakpoints, register/memory access, fault analysis, and RTT communication.
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    MIT
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    Enables AI agents to debug embedded systems by providing a comprehensive interface for GDB operations across multiple architectures like ARM and x86. It supports remote debugging via gdbserver or QEMU, allowing for detailed inspection of memory, registers, stack frames, and variables.
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    Enables MCP clients to connect to and interact with Siemens PLCs via python-snap7, supporting read/write operations on data blocks, memory, timers, counters, and CPU management.
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    MIT
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    Enables LLM control of Moku devices through network discovery, connection management, configuration deployment, and signal routing. Supports graceful ownership handoff between different interfaces (CLI, iPad, LLM) for seamless workflow integration.
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    BSD 2-Clause "Simplified"
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    An MCP server for controlling Rigol oscilloscopes from an AI assistant. It translates MCP tool calls into SCPI commands over PyVISA.
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    MIT
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    Control a Siglent SPD1305X (or SPD1000X series) programmable DC power supply from Claude Code over Ethernet using SCPI commands, with safety limits and monitoring tools.
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    MIT
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    Enables Android Automotive developers to explore and implement Vehicle Hardware Abstraction Layer (vHAL) properties with intelligent tools for property analysis, source code lookup, implementation guidance, and automated code generation for automotive systems like climate control and seat management.
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    MIT