"A server for auditing code security" matching MCP servers:

Multi-language SAST and AI-powered fuzzing MCP server for Claude Code integration, enabling static and dynamic security analysis of code.

MCP server that provides a 216-rule, framework-aware Kotlin/JVM security analyzer, enabling AI coding agents to query real security findings while writing code.

MCP server that guides LLM security reviews step-by-step, tracking progress and ensuring all assigned source code is read before completing each plan step.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

Integrates Checkov, Semgrep, Bandit, and ASH to provide comprehensive code security analysis for AI coding assistants.

Security scanning for MCP servers from the inside out. Provides runtime inspection, AST-based static analysis, config audit, dependency analysis, and OWASP MCP Top 10 compliance in a single MCP server.

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.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Enables comprehensive security scanning of code projects, detecting vulnerabilities in dependencies, code patterns (XSS, eval, etc.), and exposed secrets, with detailed reports in Spanish prioritized by severity.

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A lightweight MCP server for security reviews that injects security requirements before code generation, scans dependencies for CVEs, and verifies generated code without disrupting workflow.

Enables comprehensive security scanning of code repositories to detect secrets, vulnerabilities, dependency issues, and configuration problems. Provides real-time security checks and best practice recommendations to help developers identify and prevent security issues.

Fetches GitHub Code Scanning alerts and applies minimal local patches to fix vulnerabilities, without creating branches, commits, or PRs.

Automatically detects security vulnerabilities in AI-generated code, scanning for hardcoded secrets, injection flaws, XSS, weak cryptography, authentication issues, path traversal, and vulnerable dependencies across JavaScript, Python, Java, and Go.

Official Model Context Protocol server exposing static AST security tools (audit_mcp_repository, audit_local_directory) to scan MCP tools for vulnerabilities before connecting them to Claude or Cursor.

An MCP server that provides CVE-driven security prompts for code review, enabling coding agents to get actionable security checks based on real vulnerabilities.

Enables AI assistants to interact with VS Code for language intelligence, debugging, and code execution.

Zero-execution static AST security scanner and vulnerability auditor for MCP servers. Detects Command Injection (CWE-78), Path Traversal (CWE-22), Hardcoded Secrets (CWE-798), and Unauthenticated Transports (CWE-306).