"Setting up an MCP server in Kubernetes" matching MCP servers:

Enables authorized web/API security analysis as a stateful, multi-stage workflow with persistent session state, human-controlled validation, candidate versus confirmed finding tracking, and stop conditions.

An MCP server that lets an AI agent probe a live URL and confirm whether sensitive files (e.g., .git, .env, source maps) are genuinely served by fetching and validating the content, avoiding false positives.

GhostHunt is an MCP server that scans your development machine for API keys, tokens, and credentials hiding in places you forgot to check.

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.

An MCP server that audits zero-knowledge circuits (Circom, Noir, Halo2) for soundness and constraint bugs, powered by the Cysic Minimax model.

Gives AI agents threat-intelligence verdicts for IPs, domains, URLs and hashes, CVE lookups with EPSS and CISA KEV data, and a prompt-injection gate that scans untrusted text before the agent acts on it. Agents can also batch-check up to 100 indicators, hunt brand-lookalike domains, and track scan and request quotas.

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.

Enables AI assistants to run Kali Linux security tools in an isolated Docker container for tasks like network scanning, port checking, and service enumeration.

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.

Keeps bug-hunting AI agents within an authorized scope by checking every target against declarative allow/deny rules, refusing out-of-scope findings, and scrubbing secrets from evidence. It also computes CVSS v3.1 base scores and records findings in an append-only ledger.

Provides an MCP interface to a full Kali Linux environment running in Docker, enabling AI assistants to execute security tools like nmap, sqlmap, and metasploit. It allows users to start/stop the container, run shell commands, and transfer files for security testing and educational purposes.

An MCP server for identifying SQL injection vulnerabilities in web applications using various techniques like error-based, time-based, and union-based scanning. It supports bulk URL processing, WAF bypass strategies, and authenticated testing across multiple database systems.

An MCP server that provides passive and low-impact active reconnaissance tools for authorized bug bounty and security assessments, enabling LLMs to perform structured recon and generate reports.

An AI-native code security audit MCP server that supports multi-language AST analysis, call graph analysis, vulnerability detection, and AI deep audit.

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

Exposes seven MCP tools that let an AI coding agent detect a project's stack, fetch the priority security checks for that platform, search 2,057 OWASP-derived check cards with file-and-commit provenance, and record evidence-backed pass/fail results in a report.

An MCP server for the OnSecurity API that allows Claude to query Rounds, Findings, Prerequisites, Blocks and Notifications.

Enables cybersecurity training, purple-team collaboration, and executive readiness through tools for scenario generation, attack simulation, telemetry analysis, incident investigation, forensics, and reporting with an immutable audit trail.

An MCP server for authorized bug bounty work that enforces an evidence-driven workflow with session management, preflight checks, surface discovery, and verified scanning.

An intentionally vulnerable case management system designed for security training that provides MCP tools for SOC analyst workflows like case handling and indicator search. It enables users to explore and demonstrate common security weaknesses such as prompt injection, SQL injection, and broken authorization in an MCP-integrated environment.

Enables cyber defenders to query ATT\&CK techniques, list tactics, map incidents to techniques, look up threat actor groups and mitigations, all via the MCP protocol.

A deliberately vulnerable MCP server for practicing exploitation of tool poisoning, command injection, and path traversal. Includes fixed versions and an agent demo to reproduce the issues in a controlled environment.

An AI-powered penetration testing reasoning engine that provides automated attack path planning, step-by-step guidance for CTFs/HTB challenges, and tool recommendations using Beam Search and MCTS algorithms.

An AI-powered dependency decision engine that lets agents analyze blast radius, simulate upgrades, trace security attack paths, and visualize dependency topology in a 3D galaxy viewer.

Exposes every operation in the ConnectSecure OpenAPI specification as an MCP tool, enabling vulnerability management, assets, assessments, integrations, and reporting.

A Model Context Protocol (MCP) server for integrating with StackHawk's security scanning platform. Helps developers set up StackHawk, run security scans, and triage findings to fix vulnerabilities — all from within an LLM-powered IDE or chat.

Enables coding agents to run security scans on repositories through a local stdio bridge to a hosted endpoint. Includes browser-based OAuth sign-in and local token storage.

Enables management of capture sessions, rules, certificates, and protocol communication through an MCP endpoint, controlling a sing-box core.

Cyber Host Artificial Intelligence (C.H.A.I) An autonomous penetration testing MCP (Model Context Protocol) server with an integrated AI decision engine, multi-provider LLM support, and an extensible plugin architecture.