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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 AI-powered security audit tool that analyzes codebases for vulnerabilities using real-time data from MITRE CWE and npm audit. It enables deep analysis of authentication, API security, and dependencies to provide structured findings and remediation steps.
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    MIT
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    An adversarial code verification system that uses a Verifier-Critic debate loop to systematically uncover security, correctness, and performance issues. It implements the Socratic method to provide deep semantic analysis and dialectical reasoning beyond traditional static linting.
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    MIT
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    An efficient MCP server for performing accurate, deep comparisons between JSON objects or strings using the deepdiff engine. It provides AI agents with standardized difference reports, supporting nested structures and various input formats to ensure precise data analysis.
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    Provides AI agents with deep visibility into a running web page's UI by capturing DOM, styles, and screenshots through a lightweight bookmarklet. It facilitates design-to-code comparisons, accessibility audits, and automated CSS debugging directly within an IDE.
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    MIT
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    Full-stack security for AI agents — static analysis + MCP runtime interception. 31 rules detect prompt injection, data exfiltration, backdoors, tool poisoning, and cross-file attack chains. Includes MCP proxy for real-time blocking, Python AST taint tracking, multi-language injection detection (8 languages), and AI-powered deep analysis. Free, offline, zero-config.
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    Enables AI assistants to inspect and automate Windows desktop UI elements by exploring UI trees, checking properties, performing actions like clicking and typing, and generating Python automation scripts.
    Last updated
    MIT