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    CodeSafer is an MCP server that scans AI-generated code for 9 categories of hidden security threats — including invisible Unicode, Trojan Source, homoglyphs, and rules file backdoors — using static analysis plus CodeBERT deep learning. Runs locally, free tier available.
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    MIT
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    An MCP server for 7-Zip archive operations (list, extract, create) with dual-engine architecture and sandbox security features. Note: currently a learning project and not yet functional.
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    MIT
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    Provides crowdsourced package intelligence and security alerts for AI coding assistants by analyzing project dependencies and framework co-occurrence. It enables automated project scans, package alternative discovery, and data-driven recommendations across multiple programming ecosystems.
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    MIT
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    Provides centralized security instructions for AI-assisted code generation by matching context-aware rules to the user's programming language and file patterns. It ensures generated code adheres to security best practices without requiring manual maintenance of instruction files across individual repositories.
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    MIT
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    IMCP - Insecure Model Context Protocol The DVWA for AI Security! Welcome to IMCP – a deliberately vulnerable framework that exposes 16 critical security weaknesses in AI/ML systems. Whether you're a security researcher, developer, or educator, IMCP is your playground for hands-on learning about real
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    Enables comprehensive interaction with Elasticsearch APIs through natural language queries, specifically optimized for security analysis, threat detection, incident investigation, and compliance monitoring with advanced machine learning capabilities for anomaly detection.
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    Apache 2.0
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    A remote MCP server implementation that demonstrates authentication and authorization capabilities using OAuth 2.1. This is a workshop project for learning how to build secure MCP servers with user authentication.
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    MIT
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    Provides essential security and CTF tools including hash identification, encoding/decoding, XOR bruteforce, JWT decoding, reverse shell generation, SQL injection payloads, CVE lookup, and port service identification for learning security concepts and solving challenges.
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    Enables AI-assisted development of CodeQL queries for security analysis through the Model Context Protocol. Provides tools for compiling, testing, and executing CodeQL queries across multiple programming languages.
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    Provides secure access to Exegol penetration testing tools for CTF competitions and red team learning. Enables AI assistants to perform web penetration testing, network reconnaissance, password cracking, OSINT analysis, and more for educational purposes.
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    An enterprise-grade AI processing platform that provides advanced code analysis, automated documentation generation, security scanning, and knowledge extraction capabilities through a scalable MCP architecture. Features iterative neural processing, support for 100+ programming languages, and real-time streaming updates.