"Parrot Security" matching MCP servers:

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

Enables AI agents to execute arbitrary Python code securely in a sandboxed environment with resource limits and security constraints via MCP protocol.

A proof-of-concept tool that integrates AI into security operations, allowing users to perform offensive security tasks like network scanning and reconnaissance through natural language commands to GitHub Copilot.

MCP server for security bug-finding that proves every finding by running exploits, enabling agents to verify changes and find bugs with execution-based evidence.

Enables Codex to delegate bounded engineering jobs to Claude Code CLI in isolated Git worktrees with strict security and allowance pacing.

Connects Claude Code to local Jupyter kernels for code execution, kernel management, and notebook execution, with security gating and output capture.

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.

Enables LLMs to safely execute code in isolated Docker containers with resource limits and security controls, supporting session management and automatic dependency installation.

A demonstration tool that showcases potential security attack vectors against Model Control Protocol, illustrating how malicious plugins can exploit weaknesses in MCP architecture.

A comprehensive implementation of Model Context Protocol servers enabling natural language interactions with security platforms including Splunk SIEM, CrowdStrike EDR, and Microsoft MISP for threat intelligence querying and analysis.

Local security layer for AI coding agents: MCP policy proxy, kernel sandbox, tamper-evident audit log

A Kubernetes command processing service that converts natural language requests into valid kubectl commands, providing command validation and security checks.

A Model Context Protocol server that provides secure curl command execution capabilities, allowing AI assistants to make HTTP requests with configurable parameters and built-in security protections.

Provides isolated Docker environments for code execution, enabling users to create and manage containers, execute multi-language code, save and reproduce development environments, ensuring security and isolation.

Enables MCP clients to remotely execute server-side JavaScript in ServiceNow via a single tool, allowing full CRUD and API access with audit logging and security controls.

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.

An MCP server that executes TypeScript/JavaScript code in a sandboxed Bun environment with permission-based security controls, code snippets, and a web management UI.

Enables interaction with Arcanna's AI-powered security use cases, allowing users to manage jobs and integrations, query security events, provide feedback for model training, and generate/execute Python code for security automation.

MCP server that reviews and fixes code across four dimensions (security, standards, production readiness, sustainability), runs tests to verify fixes, and provides findings with diffs.

GhostLink is a security-hardened MCP server that gives AI coding agents safe, deterministic access to local repositories through sandboxed, policy-gated tools for searching, reading, patching, and running curated commands.