This is a comprehensive security scanning tool for MCP (Model Context Protocol) servers, developed by Cisco AI Defense. It supports scanning tools, prompts, resources, and server instructions for vulnerabilities, malicious behavior, and operational readiness. The scanner uses a multi-engine architecture combining YARA rules, LLM-based semantic analysis, static dataflow/taint analysis (Python, JS/TS, Go, Java, etc.), behavioral alignment verification, VirusTotal hash lookups, and pip-audit vulnerability scanning. It can scan remote servers (SSE/HTTP), local stdio servers, static JSON files, and packages from PyPI or npm (sandboxed via Docker). The system provides a CLI tool (`mcp-scanner`), a FastAPI HTTP server (`mcp-scanner-api`), and a Python SDK for programmatic use. It also includes a Claude Code plugin for in-IDE scanning. The codebase exhibits strong engineering practices with modular analyzers, dependency injection, structured logging, and extensive test coverage. However, it has some technical drift risks due to heavy reliance on external LLM APIs, pinned LiteLLM version, and duplication in cross-file analysis modules.