"A repository for hosting and sharing Java libraries" matching MCP servers:

Scans GitHub repositories for security vulnerabilities by cloning, performing static analysis, secret detection, build verification, and AI-powered OWASP-aligned code review, producing a scored SECURITY.md report.

Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.

Enables Claude Code to leverage OpenAI models for expert code review, deep architecture analysis, and security audits, with automatic markdown report generation.

GDB Enhanced Features MCP server for remote debugging and CTF exploitation with 41 specialized tools including ROP search, format-string detection, and memory patching.

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

Enables LLMs to perform automated penetration testing and Active Directory reconnaissance through Mythic, with tools for executing PowerShell, AD recon, domain user enumeration, and Kerberoasting.

Free deterministic security scan of a public git repository (GitHub, GitLab, Codeberg, Bitbucket): vulnerable dependencies via OSV.dev, secret patterns, and config lint, returned as structured JSON. Tools: scan_repository(url), audit_pricing(). Runs locally over stdio (python3 web/mcp_stdio.py or the Dockerfile) and is also hosted at https://project-feldspar.com/mcp. MIT licence, stdlib-only. Buil

A local MCP server that scans repository dependencies for known vulnerabilities (CVEs) using OSV.dev, enriches findings with NVD and CISA KEV data, and supports triage, remediation, and accepted risk management directly from an AI coding assistant.

Enables Claude to scan a website's HTTP security headers and receive an A–F grade against OWASP best practices, including per-header pass/warn/fail results and copy-paste fixes for missing headers.

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.

A Model Context Protocol (MCP) server for Gobuster that enables AI assistants to perform directory/file, DNS, virtual host, S3 bucket, and TFTP enumeration on a remote Kali Linux host via SSH.

Enables policy-first defensive security operations for MCP, providing repository and web-security analysis with controlled authorization, scoped execution, and auditability.

Enables dynamic management and execution of proxy chains on a remote Linux host via SSH, allowing AI assistants to route network traffic through proxies for privacy and security testing.

A security gate MCP server that audits agent extensions (skills, MCP servers, tools) by scanning for risks, adversarial analysis, and sandbox execution, returning a trust verdict of allow, quarantine, or block.

A universal digital fingerprinting MCP server that combines 103 techniques across TCP, TLS, SSH, HTTP, DNS, and more into a single interface for AI agents, enabling full-spectrum fingerprinting on demand.

An MCP server that exposes Prof. Null, an uncensored cybersecurity professor, as a set of specialized tools for learning hacking, CTFs, and security concepts through Q\&A, roadmaps, cheatsheets, labs, and more.

Exposes a pentest toolbox (sqlmap, nuclei, ffuf, etc.) via Docker to an LLM orchestrator for authorized security audits, with strict whitelisting and timeout controls.

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.

Enables MCP-compatible agents to audit an entire repository through one question, detecting stacks and running parallel checks for dead code, dependencies, security, CVEs, complexity, and lint across Laravel/PHP, Python, TypeScript/React, and Flutter/Dart. It returns normalized, severity-sorted findings with false positives flagged and secret values kept out of the output.

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.