"Spring Security" matching MCP servers:

Provides AI agents with 25 security analysis tools including vulnerability scanning, package hallucination detection, prompt injection firewall, and CI/CD integration.

Automates 85-95% of the Secure Software Development Lifecycle (SSDLC) planning phase through multi-role AI orchestration, enabling business analysis, threat modeling, test strategy design, and security code review.

Security auditor for CI ecosystems that detects supply-chain and injection flaws in CI/CD configuration files across seven CI platforms, providing taint analysis, remediation, and compliance scoring.

A security-focused MCP server for self-hosted n8n Community Edition, providing 44 bounded tools to manage workflows, nodes, executions, credentials, tags, and more via the n8n Public API.

Enables reviewing GitHub Actions workflows for outdated actions, deprecated Node runtimes, retired runners, deprecated commands, and security risks, with file, line, and fix for each finding.

MCP server for the StepSecurity platform that enables investigating supply-chain and CI/CD security issues through natural language.

A production-ready MCP server for Jenkins that enables managing jobs, pipelines, builds, and nodes through natural language, with configurable security and guardrails.

MCP security trust layer. Continuously monitors 800+ MCP packages on npm for install scripts, command injection, hardcoded secrets, capability drift, and publisher posture. Ships a GitHub Action policy gate for PR-level allow/warn/block decisions. 5 MCP tools, no API key required.

Enables AI coding agents to run fast, sandboxed pre-flight validation—tests, type-checking, linting, security audits, Git safety scans, and fix suggestions—before committing or pushing code, with instant caching and optional Docker isolation.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

Enables AI agents to scan code for security vulnerabilities using multiple static analysis tools, with support for filtering, deduplication, and CI/CD integration.

Safety-first GitOps operations for ArgoCD via the Model Context Protocol. Enables listing, diagnosing, syncing, and managing ArgoCD applications with progressive disclosure and defense-in-depth security.

Generates complete, production-ready REST, GraphQL, and microservice APIs with built-in security, validation, and deployment configurations.

Connects AI assistants to GitHub repositories, pull requests, issues, commits, and code search while enabling repository visibility controls, CI/CD monitoring, sandboxed local filesystem access, and code quality/security analysis.

A local-first AWS security tool that uses graph theory to discover attack paths (e.g., Internet → Role → DB) and prioritize remediations. It allows agents to perform read-only security audits and generate Terraform fixes without data exfiltration.

Enables AI assistants to interact with devpipe, a local pipeline runner, allowing them to list tasks, run pipelines, validate configurations, debug failures, analyze security findings, and generate CI/CD configs through natural language.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.

The Model Context Protocol (MCP) Jenkins integration is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

MCP server for npm package management — publish, install, audit, search, security & dependency health