"dns security mcp" matching MCP servers:

Protects AI agents from threats like prompt injection, jailbreaks, and SQL injection through a multi-layer scanning pipeline. It also enables PII redaction and rehydration to ensure data privacy during LLM interactions.

Enables AI agents to orchestrate security research workflows by connecting to containerized security tools via MCP, allowing automated vulnerability analysis and pipeline execution.

MCP server that runs offensive security testing tools (nmap, sqlmap, hydra, nuclei, etc.) inside an isolated Kali Linux Docker container, with allowlist, rate limiting, and audit logging.

Zero-trust safety & settlement rail for autonomous AI agents. Sub-10ms deterministic guardrails, secret leak defense, bounded wallet controls, and on-chain Proof-of-Safety attestations via x402.

Production-grade MCP server providing deterministic evaluation, AST sandboxed execution, DNS routing audit, and runtime guardrails for autonomous LLM agents.

A prompt-validation service that checks incoming prompts against security rules, blocking those matching high-severity security or jailbreak patterns while authorizing safe prompts.

An MCP security trust-check server that evaluates component installation risks and provides safe-install decisions for autonomous agents.

An MCP server for domain-agnostic task orchestration, turning objectives into executed workflows with built-in validation, security, and multi-agent patterns.

Enables autonomous AI agents and penetration testers to conduct authorized security audits with persistent cross-session memory, zero-trust secret scrubbing, dynamic OWASP/ASVS checklists, and hallucination-free exploit PoC generation from captured traffic.

A security interceptor for AI agents that mitigates prompt injections and data loss in autonomous workflows.

An MCP server that connects AI agents to the CrowdStrike Falcon platform for intelligent security analysis and automation across various security modules. It provides programmatic access to detections, incidents, host management, and threat intelligence to enhance security operations within agentic workflows.

Provides comprehensive security analysis tools for querying the VirusTotal API, enabling detailed security reports on URLs, files, IP addresses, and domains with automatic relationship data fetching.

A policy-based security layer for AI agents and MCP tools that evaluates tool requests against security policies before allowing, denying, or requiring human approval for execution.

Security middleware for MCP servers. Trust-based access control, rate limiting, and audit logging. Zero dependencies.

Enables building and running MCP servers from a single executable, with shared daemons, concurrency controls, retries, caching, security, and OpenAPI integration.

Enables AI agents to plan and run authorized offensive security assessments across 150+ integrated tools, with full activity logging of every scan.

A comprehensive framework for building reliable Python MCP servers that enforces incremental development practices through Cursor Rules, featuring built-in security measures and a smart rule system.

Integrates SOAR (Security Orchestration, Automation and Response) capabilities into AI clients, enabling security playbook execution, event management, and threat intelligence queries. Provides a complete security incident response platform through natural language interactions.

Integrates Security Orchestration, Automation and Response (SOAR) platform capabilities into AI clients like Claude Desktop and Cherry Studio. Enables users to execute security playbooks, manage security events, and perform automated threat response through natural language interactions.

Autonomous pentests from one command: real security tools, working PoCs, and audit-ready reports, all driven via MCP.

An enterprise-level MCP gateway and proxy that sits between an organization's MCP servers and clients. MCP Manager mitigates security threats, enables fine-grained permissions, enforces policies and guardrails, and generates comprehensive, end-to-end logs.

Enables SOC analysts to analyze security incidents, map to MITRE ATT&CK, calculate severity, and recommend remediation actions.

Provides AI coding agents with deterministic security requirements, approved patterns, and anti-patterns based on a project's threat model defined in security-context.yaml, enabling secure code generation without relying on LLMs for security advice.

Provides automated security incident remediation tools for AWS, enabling real-time threat response by quarantining malicious S3 objects, restricting IAM access, and updating security groups.

Unifies 7,283+ detection rules from Sigma, Splunk ESCU, Elastic, and KQL into a single queryable interface via MCP, with a web dashboard and autonomous agent pipeline for detection engineering.

A lightweight MCP server for managing DNS records, purging cache, and interacting with the Cloudflare API through natural language commands.

A Kali Linux-based MCP server that exposes over 45 penetration testing tools for AI-assisted security auditing and vulnerability scanning. It features strict scope enforcement, structured output parsing, and persistent finding storage to automate the offensive security workflow.

Integrates 193 Kali Linux security tools with AI for intelligent penetration testing, CTF solving, and vulnerability assessment through automated workflows and expert knowledge base.

AI-powered penetration testing framework that can operate as an MCP server, enabling automated security assessments through natural language commands.

SentinelOps is an MCP server that enables AI-powered security operations with human-in-the-loop safety. It allows agents to investigate threats, propose actions, and execute security responses only after explicit human approval.

Input/output safety gate for AI agents: detect prompt-injection/jailbreak, leaked secrets/PII, and URL/IP reputation. Deterministic, no LLM.

AI-powered MCP penetration testing framework with 150+ security tools and 12+ autonomous AI agents, featuring enhanced security and guardrails.

Enables LLMs to execute Kali Linux security tools like nmap, sqlmap, and hydra in a secure, sandboxed environment. Provides both MCP and HTTP API interfaces for penetration testing and security assessment tasks.

The security runtime for MCP servers. Every tool call inspected. Every attack blocked. Every decision logged.

An AI-powered security agent that utilizes MCP tools and Groq LLMs to analyze Azure infrastructure, audit security groups, and identify storage misconfigurations. It enables users to perform natural language security assessments and ensure compliance with CIS Azure best practices.

An automated security operations center MCP server that uses LLMs and network analysis tools like Tshark to detect threats in traffic data. It enables users to automatically ingest PCAP files, query specific packets, and generate intelligent security analysis reports.

AI-powered autonomous penetration testing framework with 80+ professional security tools across reconnaissance, web application testing, exploitation, and forensics. Integrates with LM Studio for intelligent vulnerability assessment and automated security testing workflows.

Runtime agent firewall for PII redaction, rate limits, and policy enforcement, enabling autonomous agent security via MCP integration.

An educational project that deliberately implements vulnerable MCP servers to demonstrate various security risks like prompt injection, tool poisoning, and code execution for training security researchers and AI safety professionals.

Enables security analysis of Kubernetes Role configurations using LLM-assisted prompt chaining and rule-based assessment. Provides comprehensive security scoring, hardened role generation, and runtime permission usage correlation to identify privilege escalation risks and over-permissive configurations.