This n8n workflow creates an intelligent chatbot system that responds to chat messages by leveraging multiple AI and MCP (Model Context Protocol) services. When a message is received via webhook, the workflow triggers various nodes for processing, including a language model, memory buffer, and MCP servers. The AI agent is designed to answer questions specifically about MCP, using data fetched from MCP servers, including the RAG MCP Server for general MCP knowledge and the Search Engine MCP Server for real-time searches. It utilizes a GPT-4 mini model for natural language understanding and maintains context with a memory buffer. The workflow is well-suited for deployment on customer support, technical assistance, or informational Q&A platforms where accurate, context-aware responses are essential. Overall, the workflow demonstrates effective integration of AI, MCP servers, and real-time search to deliver precise and contextually relevant answers in an automated chatbot environment.

Node Count	6 – 10 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.mcpClientTool, @n8n/n8n-nodes-langchain.memoryBufferWindow, n8n-nodes-mcp.mcpClientTool, stickyNote