https://fortinetcloudcse.github.io/ai-101/04mcp/index.htmlThis page covers the theory behind MCP: the problem it solves, how the protocol works at the wire level, and what dynamic tool discovery means for both capability and security. The hands-on portion is in Lab 3. By the end of this page you should be able to explain: What the M×N integration problem is and how MCP collapses it The three MCP transports and which one this workshop uses The two-phase interaction: discovery (list_tools) and execution (call_tool) How tool schemas flow from the MCP server into the LLM request Why dynamic discovery creates an attack surface that static tool lists do not The problem MCP solves Before MCP, every AI application that wanted to call an external tool had to write a custom integration. A security posture check tool, a ticketing system, a CMDB, a code execution sandbox — each one required its own client library, auth flow, schema definition, and error handling. N applications times M tools equals N×M bespoke connectors to build and maintain.Hugoen-UShttps://fortinetcloudcse.github.io/ai-101/04mcp/1_lab.htmlMon, 01 Jan 0001 00:00:00 +0000https://fortinetcloudcse.github.io/ai-101/04mcp/1_lab.htmlLab 3 switches the agent from hardcoded tools to MCP-discovered tools — without changing a line of agent code. You will see dynamic discovery in action, add a new tool to a running system without restarting the agent, and observe that the agent loop behaves identically regardless of which backend is active. Your path: Docker ComposeKubernetes / Helm Locked in — every lab page follows this choice. ​ Docker Compose Kubernetes / Helm Docker Compose — every command on this page runs on your own machine.