"Security" matching MCP servers:

CP server for RAD Security, providing AI-powered security insights for Kubernetes and cloud environments. This server provides tools for querying the Rad Security API and retrieving security findings, reports, runtime data and many more.

Provides deterministic, standards-based calculations for data center critical power infrastructure. Enables site selection, generator sizing, UPS sizing, NFPA 110 compliance, and more via 50+ AI agents and 8 compound chains.

Detect live website vulnerabilities and security flaws in GitHub repositories using automated DAST and SAST scanning. Safeguard applications by identifying exposed secrets, insecure dependencies, and common code patterns prone to exploitation. Receive structured fix plans with precise code remediation steps to resolve identified risks and improve security posture.

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.

MCP server for Android app security auditing that integrates ADB, VirusTotal, and MobSF to extract, analyze, and recommend actions on apps for ethical hacking learning.

Security for the MCP servers you use: detects tool poisoning, rug pulls, shadowing, secrets and supply-chain risk (OWASP MCP Top 10), with runtime guards and approved-server policy. Runs locally.

An MCP server that enables AI agents to perform comprehensive GitHub security audits across org settings, repositories, Actions workflows, secrets, supply chain, and access control using 39 tools and 45 checks.

MCP server for automated AWS security scanning — 19 modules, risk scoring, zero write operations.

MCP server for scanning smart contracts for security vulnerabilities. It detects issues like reentrancy, overflow, access control, and provides security scores with NEAR-specific recommendations.

Provides a security governance layer for AI agents to safely access upstream MCP servers, enforcing tool-level RBAC, parameter constraints, authentication via static tokens or OIDC, and tamper-evident audit logging.

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.

Comprehensive DNS security toolkit for AI agents: 103 tools across 13 categories including DNSSEC validation, subdomain takeover detection, email security audit, and more, all running locally with no external API calls required.

Enables file operations, npm package management, and configuration checking through MCP.

Enables evolving scan and policy configurations by inferring security phenotypes from observed findings, seeding competing genomes, measuring fitness, and generating bounded trial plans with ancestry lineage.

Enables unified security workflows with secret scanning, dependency CVE auditing, TLS/SSL inspection, and DNS/SPF/DMARC checks through a single MCP server.

Audit any MCP server for tool-poisoning, prompt-injection, and data-exfiltration risk before connecting an agent.

Integrates authoritative security compliance frameworks (ISO 27001, NIST 800-53, OWASP ASVS, NIST SSDF) into AI-assisted development, offering control lookups, cross-framework mappings, build-time guardrails, and automated audit evidence generation.

Enables secure interaction between LLMs and MCP tools by applying zero-trust security controls, including sensitive data masking, file system protection, and policy enforcement.

Enables querying and analysis of a unified database of security detection rules across multiple formats, including Sigma, Splunk, Elastic, KQL, and CrowdStrike CQL.

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.

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.

MCP server that provides a security gateway for AI agents, enforcing allow/confirm/deny policies on tool calls and requiring human approval for risky operations, with full audit logging.

Enables authenticated MCP clients to query Security Context tools against a git tag or commit ref while returning only vulnerabilities and fix fingerprints that predate that snapshot, so agents do not receive live bugs at the tag.

MCP server for static security analysis of Android application source code.

Enables creation of secure-by-default MCP servers with 5-layer validation to protect against injection, path traversal, and other attack vectors.

Enables scanning OpenAPI specifications for security gaps and generating security test checklists for APIs.

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

MCP server that checks URLs against the URLhaus malware database to identify malicious URLs.

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.