"Radix UI" matching MCP servers:

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.

Connects an AI assistant to an already-running mitmweb session so it can read, search, diff, replay, and generate code from the same network flows shown in the UI.

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

Enables users to retrieve and display CVE vulnerability information from the National Vulnerability Database (NVD) with support for keyword search and detailed lookup.

MCP server that exposes 31 OSINT checks from Lissy93/web-check as tools for website analysis, including SSL, DNS, headers, WHOIS, and security presets. Enables natural-language-driven web recon and health checks.

Enables AI assistants and the WYRE Conduit gateway to access Telivy's security assessment data for MSPs, including external scans, deep-scan risk assessments, device inventory, M365/Google Workspace user exposure, PII summaries, and finding-level details.

MCP server for AI-driven VAPT orchestration, enabling agents to plan and execute authorized security scans through a control plane that enforces scope, sanitization, budget, rate limits, human approval, and audit logging.

An authorization-first MCP-governed control plane for executing security-tool workflows in explicitly approved, sandboxed environments with auditable campaigns and AI collaboration boundaries.

Enables red-team and blue-team security workflows on BlackArch Linux by wrapping local tools like nmap, gobuster, nikto, and hydra as MCP tools, with scope-gating that prevents unauthorized scanning against any target not explicitly listed in a local scope.yaml file.

Enables structured robustness and security testing by scanning text for policy/safety issues and generating test suite outlines.

Provides AI coding assistants with real-time security scanning superpowers, including SAST, secrets detection, dependency CVE scanning, and web vulnerability assessment.

Provides on-machine security scanning for Copilot-generated code, including SAST, secrets, dependency, container, and configuration checks, plus AI-specific risk detection, with findings and fixes available via MCP tools.

Lets MCP-compatible AI clients read your getdebug projects, findings, and proposed fixes using your existing bearer token.

Security Scanner AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

The Checkmarx Security MCP server bridges your AI assistant (Claude, Cursor, Copilot, etc.) with Checkmarx One's enterprise application security platform. It exposes security workflows as natural-language-accessible MCP tools, allowing developers to scan code, investigate findings, and receive context-aware fixes without leaving their development environment.

Read-only observation of a single live URL: parses static HTML to report security posture, forms, links, accessibility signals, and leaks, with described fixes. SSRF-gated and safe, never executes JavaScript.

Voyager-net is a read-only, authorized network auditing MCP server that scans a single host or domain for DNS, port, TLS, and HTTP hygiene issues, returning findings with severity and suggested fixes. It enables AI agents to audit infrastructure safely without mutation, requiring explicit authorization.

A Model Context Protocol server that enables AI assistants to search and retrieve information about security exploits and vulnerabilities from the Exploit Database, enhancing cybersecurity research capabilities.

Enables AI agents to conduct authorized mobile banking reverse engineering and security research through 50+ MCP tools spanning APK analysis, Frida instrumentation, malware detection, Play Integrity bypass detection, no-root traffic interception, and evidence reporting.

AI-powered security vulnerability detection for MCP-compatible agents, offering real-time scanning of code against a knowledge graph of 24,000+ vulnerability patterns.