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    MCP server for AgentMinds collective intelligence platform, enabling AI agents to scan websites for security/SEO/performance issues, pull personalized recommendations, and share findings across the network.
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    MIT
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    MCP server for Android APK triage, providing tools to parse APK headers, list DEX classes, and decode AndroidManifest.xml using apktool or androguard backends.
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    Automates Android app analysis using Frida via AI commands, connecting a rooted Android phone to a computer and running dynamic analysis scripts without manual command execution.
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    Enables AI assistants to perform vulnerability scanning using Grype, supporting scans of directories, container images, and packages via the Model Context Protocol.
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    Apache 2.0
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    Enables AI assistants to perform domain reconnaissance using theHarvester OSINT tool, including email harvesting, subdomain discovery, DNS brute force, and Shodan integration, via SSH on a Kali Linux host.
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    AI-powered penetration testing reasoning engine (MCP server) for attack path planning, step scoring, and tool recommendations using Beam Search and Monte Carlo Tree Search.
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    MIT
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    Enables AI assistants to perform web content discovery scans using feroxbuster on a remote system via SSH, with support for recursive scanning, filtering, and background execution.
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    MIT
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    Enables out-of-band interaction testing by integrating ProjectDiscovery's interactsh service as an MCP server. Allows AI agents to create callback domains, send probes, and capture DNS/HTTP interactions for security testing and verification workflows.
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    MIT
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    Enables AI assistants to perform password security auditing using John the Ripper on a remote Kali system via SSH, supporting cracking, hash management, and session control.
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    MIT
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    Exposes the five Enternovate security tools as 23 Model Context Protocol tools, enabling agents to scan attack surfaces, query knowledge graphs, audit websites, check email security, and run POPIA compliance assessments via a single MCP connection.
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    MIT
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    Enables users to query BloodHound Active Directory graph data using natural language, finding attack paths, Kerberoastable accounts, and other AD security insights.
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    An AI-powered penetration testing reasoning engine that provides automated attack path planning, step-by-step guidance for CTFs/HTB challenges, and tool recommendations using Beam Search and MCTS algorithms.
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    Enables LLMs to perform Active Directory penetration testing using tools like NetExec, Bloodhound, Nmap, Certipy, and John the Ripper. Automates vulnerability discovery, attack path analysis, and documentation generation for security assessments.
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    MIT