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    Provides a human-in-the-loop security layer for AI agents by intercepting file operations, explaining them with a local LLM, and enforcing a deterministic policy that requires user approval for risky actions.
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    MIT
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    Mandatory human approval gate for autonomous AI agents. Before any critical, irreversible, or financially significant action executes — file deletion, production deployment, financial transaction — the agent calls oracle_validate. A human receives a real-time Telegram notification with full context and taps Approve or Reject. The agent waits for the decision before proceeding.
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    A demonstration server that reveals security risks by accessing sensitive environment variables, illustrating how MCP tools can potentially leak user data without explicit consent.
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    MIT
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    Enables comprehensive threat analysis for Indicators of Compromise (IoCs) including IP addresses, file hashes, domains, and URLs. It provides detailed reputation scores, security vendor evaluations, and network metadata to facilitate security assessments and risk detection.
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    MIT
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    A Model Context Protocol (MCP) server that provides integration with the Have I Been Pwned API to check if your accounts or passwords have been compromised in data breaches.
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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 interaction with the AssemblyLine 4 malware analysis platform, allowing file submissions, URL analysis, and search capabilities via natural language.
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    MIT
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    A local stdio MCP server that enables coding agents to discover credential handles and create scoped action requests with local approval and sanitized output.
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    Apache 2.0
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    Connects AI assistants to the Vectra AI security platform to enable intelligent analysis of threat detection data and automated incident response workflows. It allows users to investigate threats, take response actions, and generate security reports using natural language.
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    MIT
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    Enables detection of AI-generated content from ChatGPT, GPT-4, and Gemini models through the BACH AI Content Detector API.
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    MIT
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    Governance engine for MCP tool calls, providing deterministic rule enforcement to block destructive actions like SQL drops, shell commands, and file system modifications before execution.
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    Apache 2.0
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    A proxy server that sits between MCP clients and servers, providing authentication, tool discovery, caching, and guardrail enforcement to protect MCP servers from malicious inputs.
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    Apache 2.0
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    缔零法则MCP是基于LLM和RAG技术搭建的实现完全替代人力的全自动化风险识别的内容安全审查平台,致力于通过代理AI技术减少人力成本,高效高精度为用户提供分钟级接入的内容风控解决方案,破解安全威胁,提供从风险感知到主动拦截策略执行的全链路闭环与一体化解决方案。This MCP tool is an AI-powered content security review platform built on LLM and RAG technologies, designed to achieve fully automated risk identification that completel
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    MIT