"Parrot Security" matching MCP servers:

MCP server that provides a 216-rule, framework-aware Kotlin/JVM security analyzer, enabling AI coding agents to query real security findings while writing code.

Enables AI agents to interact with Google NotebookLM and Gemini API for document analysis, deep research, and notebook creation with enterprise-grade security including post-quantum encryption and 14 security layers.

Enables deep security auditing of web applications directly from AI IDEs including Cursor and Claude Code. Scans URLs for vulnerabilities, returns security scores with SHIP/BLOCK verdicts, and provides specific fix prompts for remediation.

MCP server for the Codex Security Cloud service, enabling agents to list, inspect, close, reopen findings, request PRs, and apply generated patches.

Enables AI assistants to scan project dependencies and Infrastructure as Code files for security vulnerabilities and misconfigurations. It also provides automated fixing capabilities to remediate identified security issues.

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

Audits npm package dependencies for security vulnerabilities, providing detailed reports and fix recommendations with MCP integration.

Provides a zero-install security baseline for AI coding agents, with tools to retrieve curated security rules and check actions against them for self-correction.

A Python-based MCP server that enables integration with Microsoft Security Copilot and Microsoft Sentinel, allowing users to run KQL queries, manage skillsets/plugins, and execute prompts in Security Copilot.

MCP server providing a searchable security knowledge base for AI coding assistants, enabling retrieval of secure-coding instructions and feature-specific security guidance.

Provides Trivy security scanning capabilities through a standardized interface, allowing users to scan projects for vulnerabilities and automatically fix them by updating dependencies.

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.

A TypeScript MCP server with strict schema validation and security guards, currently implementing echo, get_time, hash_text, uuid_generate, and json_validate tools.

Collects, analyzes, and verifies security patches for the eGovernment framework, including PDF analysis and diff previews.

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.

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

Release gate agents call before they tell users a public website is ready to ship. Scans public websites across security, SEO, accessibility, legal compliance, and sustainability.

Enables AI agents to interact with the npm registry, covering package intel, dist-tags, trusted publisher configuration, access and team governance, tokens, security advisories, and publishing, with read-only tools by default.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Provides a persistent memory and governance layer that allows AI coding agents to query documented architecture rules and validate code against team standards. It enables agents to verify compliance across categories like security and testing before suggesting changes to ensure consistency across development sessions.