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    An MCP server that lets an AI agent probe a live URL and confirm whether sensitive files (e.g., .git, .env, source maps) are genuinely served by fetching and validating the content, avoiding false positives.
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    1
    MIT
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    Connects AI coding assistants to Snyk API & Web for onboarding scan targets, configuring authentication, running DAST scans, and triaging findings through natural language.
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    Apache 2.0
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    Enables AI assistants to search and analyze vulnerabilities and exploits from multiple intelligence sources, including NVD, CISA KEV, ExploitDB, Metasploit, and more, with tools for CVE research, exploit analysis, and report generation.
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    MIT
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    Enables AI models to search and retrieve offline security knowledge from over 20 curated sources including HackTricks, PayloadsAllTheThings, and OWASP guides, via the Model Context Protocol.
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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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    A comprehensive reconnaissance toolset that provides AI agents with 37 tools across 12 data sources like Shodan and VirusTotal for automated intelligence gathering. It enables agents to perform domain reconnaissance, attack surface mapping, and cross-platform data correlation within a single conversational interface.
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    MIT
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    Provides AI agents with 37 OSINT tools and 12 data sources to perform unified reconnaissance, domain analysis, and attack surface mapping. It enables agents to query, correlate, and reason across platforms like Shodan, VirusTotal, and Censys in parallel.
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    MIT
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    Enables deep security auditing of web applications directly from AI IDEs including Cursor and Claude Code. Scans URLs for vulnerabilities, returns security scores with SHIP/BLOCK verdicts, and provides specific fix prompts for remediation.
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    The most comprehensive steganography analysis toolkit for AI agents, providing 60 tools across 7 categories for detecting and extracting hidden data from images, audio, text, and files, all running 100% offline.
    Last updated
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    MIT
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    A Model Context Protocol server designed for testing backend APIs for security vulnerabilities like authentication bypass, injection attacks, and data leakage.
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    MIT