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    Blocks dangerous operations: rm -rf, sensitive file access, privilege escalation, and more are denied before execution. Gates risky commands behind human approval (optional): configurable commands require explicit operator sign-off via a web GUI before the agent can proceed. Simulates blast radius: wildcard operations like rm \*.tmp are evaluated against real files before running, and blocked if th
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    MIT
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    Blocks dangerous operations — rm -rf, sensitive file access, privilege escalation, and more are denied before execution. Gates risky commands behind human approval Simulates blast radius — wildcard operations like rm \*.tmp are evaluated before running Automatic backup of files Full audit of commands
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    MIT
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    ai-runtime-guard is an MCP server that sits between your AI agent and your system, enforcing a policy layer before any file or shell action takes effect. No retraining, no prompt engineering, no changes to your agent or workflow, just install, configure once, and your agent operates within the boundaries you set.
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    Enables LLM agents to execute arbitrary Python code in secure, isolated sandbox environments with automatic dependency management and file handling. Each code execution runs in a fresh virtual environment that gets destroyed after completion, providing safe and reproducible Python code execution.
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    MIT
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    Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.
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    MIT
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    The m2m-mcp-server-ssh-client provides a unified MCP server interface, securely connecting via SSH to the m2m-mcp-server-ssh-server back-end which aggregates MCP servers. This setup offers secure, single-point access to diverse remote tools using robust SSH key-based authentication.
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    MIT
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    An MCP server that enables AI assistants to execute shell commands and manage files on remote servers via SSH. It supports recursive directory uploads, archive extraction, and direct file creation from text content.
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    MIT
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    A self-hosted MCP server that enables AI coding agents to read, edit, search, and run code in local projects with human review loops and policy controls.
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    MIT
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    A FastMCP server that enables AI agents to safely execute shell commands, run code in Python/Node.js/Go, and install packages, all packaged in Docker for secure deployment.
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    Enables secure remote command execution and file operations over SSH/SFTP with automatic authentication resolution. Features built-in diagnostics that identify connection issues—such as stale host keys, unloaded agents, or permission errors—and provide specific commands to fix them.
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    MIT
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    SSH Session MCP fills a gap in the MCP ecosystem by offering a persistent shared SSH PTY runtime, not just stateless command execution. It features browser collaboration, input locking, safe/full execution modes, async command tracking, configurable policy rules, and multi-device profiles. Ideal for remote development, embedded systems, infrastructure workflows, and hardware control scenarios.
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    Apache 2.0