AIGoat v2.0 released as an agent and MCP attack-defense playground

AIGoat v2.0 released, adding attack surfaces such as tool-calling agents, MCP hosts and clients, agent memory, and end-to-end attack chains. This version includes 46 experiments, of which 23 are LLM, 12 are agent-type, and 11 are MCP, covering three OWASP frameworks, and provides a comprehensive Agentic Kill Chain experiment with three modes: Vulnerable, Defended, and Guardrailed. New Learn page, threat modeling workbench, unified hub UI, and Google Colab notebook and Docker deployment options are added. Experiment numbering has switched to 2026 numbering; old bookmarks and lecture notes need updating, and existing kill chain users need to perform a one-time Hard reset. Running requires Python 3.11, Node 18+, and Ollama; tool-calling experiments require models with native tool-calling support, e.g., ollama pull qwen3.5:9b.