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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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    An MCP server that provides CPU emulation, disassembly, and assembly tools for LLM agents across multiple architectures including x86, ARM, and RISC-V. It enables agents to manage isolated emulation sessions, perform memory analysis, hook syscalls, and trace execution through a standard tool interface.
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    GPL 2.0
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    Enables multi-architecture code generation and execution across platforms including x86_64, ARM, and RISC-V directly within Claude. It allows users to run code, compare outputs from multiple AI models, and perform hardware simulations for Verilog and VHDL.
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    MIT
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    Ephemeral MicroVM-isolated code execution for AI agents. Run Python, Node, or bash — fresh hardware-isolated VM per call, hard-purged after. No state persists between calls.
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    MIT
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    Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.
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    MIT
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    An orchestration platform for deploying parallel swarms of tool-enabled AI agents to perform complex tasks like code generation, system monitoring, and multi-perspective analysis. It features a unique chunked write pattern that enables the creation of large-scale documents and code files by assembling parallel agent outputs.
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    Enables AI assistants to compile, run, lint, and format ArxLang code directly through ArxNode without manual terminal commands.
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