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    Exposes persistent, stateful remote Bash sessions to AI agents via SSH, enabling command execution with preserved working directory and environment.
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    MIT
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    AI-native security research platform that integrates Claude with MCP to execute real offensive security tools in an isolated Docker container, enabling natural language-driven recon, CVE scanning, Active Directory enumeration, and cryptographic posture assessment.
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    MIT
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    Your sysadmin co-pilot — an AI that administers Linux through typed, approval-gated, Ed25519-audited actions instead of shell strings. Reference implementation of the LACS standard.
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    MIT
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    A secure shell command execution server implementing the Model Context Protocol (MCP). This server allows remote execution of whitelisted shell commands with support for stdin input.
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    MIT
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    Enables execution and management of Babashka scripts using the Model Context Protocol, offering features like caching, command history access, and configurable timeouts for enhanced scripting workflows.
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    Enables execution of ROS 2 CLI commands through the Model Context Protocol, supporting configurable timeouts, working directories, and secure command whitelisting.
    MIT
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    A secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.
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    Apache 2.0
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    This project implements a customizable MCP server to execute RTE protocol. The intention of this project is to be easily extensible. You can add your own MCP tools by using RteUtils class. Also is needed to define the RTE connection parameters and the RTE flow in a yaml format.
    19
    Apache 2.0
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    An MCP server that allows AI assistants to manage background processes, enabling start, stop, monitoring, and querying of long-running shell commands without blocking the conversation.
    MIT
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    ht-mcp is useful for enabling Agents to use terminals (e.g. bash, zsh, fish) in the same way a human does. It solves the challenge of agents stalling when they encounter interactive terminal commands.
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    Apache 2.0
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    A Python implementation of the Model Context Protocol that allows applications to provide standardized context for LLMs, enabling creation of servers that expose data and functionality to LLM applications through resources, tools, and prompts.
    MIT