Model Context Protocol (MCP) for LLM Tool Integration › End-to-End Flow (With MCP)

Imagine typing the following into your MCP-aware development environment, such as Cursor: > “What is the latest ticker price for AAPL?” Here is what happens behind the scenes: 1. The user sends a prompt to the LLM client. 2. The client queries all connected MCP servers to discover available tools. 3. The language model selects the appropriate tool, such as `get_stock_price`, and determines the correct parameters. 4. The selected tool is invoked through the MCP server. 5. The tool returns data, which the model uses to generate a complete response. 6. The user receives a response that includes real-time data pulled from the tool. All of this happens without needing to hardcode any conditional logic to match prompts to tool calls.