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    Privacy-first OSINT scanning MCP server that aggregates ~25 sources into a risk report, running locally with no data leaving your machine.
    5
    1
    AGPL 3.0
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    An MCP server that scans local codebases for quantum-vulnerable cryptography (secp256k1, Ed25519, RSA, etc.) and CI signing commands, classifying each finding as quantum-broken, post-quantum, or neither. It runs entirely locally with no network calls, providing a deterministic inventory for AI agents.
    2
    Apache 2.0
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    Enables AI agents to perform passive security scans on domains, checking email spoofing (DMARC/SPF/DKIM), TLS weaknesses, security headers, exposed files, and subdomain-takeover risk without needing an API key.
    7
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    MIT
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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.
    2
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    MIT
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    Enables users to scan MCP servers for security threats, check installed servers, and analyze config files for risks, all from AI assistants like Claude, Cursor, or Windsurf.
    5
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    An MCP server that enables AI assistants to analyze Android APK and iOS IPA files for security issues through natural language conversation, including permission auditing, secret detection, and SDK enumeration.
    12
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    MIT
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    MCP server exposing LIEF for cross-format binary analysis, enabling parsing, section listing, imports/exports, disassembly, and string extraction for PE, ELF, MachO, DEX, ART, and OAT files.
    17
    MIT
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    Provides an MCP interface to a full Kali Linux environment running in Docker, enabling AI assistants to execute security tools like nmap, sqlmap, and metasploit. It allows users to start/stop the container, run shell commands, and transfer files for security testing and educational purposes.
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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.
    4
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    MIT
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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.
    100
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    MIT