Architecting Stateful AI Agents in Laravel: Bridging n8n, MCP, and RAG for Production Workflows

Описание и применение

<p>The demo works flawlessly. You ask the AI agent to analyze a customer's billing history, query the internal documentation via a Retrieval-Augmented Generation (RAG) pipeline, and draft a personalized support response. The Large Language Model (LLM) thinks, calls a tool via the Model Context Protocol (MCP), observes the immediate JSON result, and outputs a flawless answer in your local development environment. </p> <p>Then you deploy it to an enterprise production environment. </p> <p>Within hours, your Laravel application starts throwing 504 Gateway Timeouts. Your PHP-FPM workers are entire

Задача

<p>The demo works flawlessly. You ask the AI agent to analyze a customer's billing history, query the internal documentation via a Retrieval-Augmented Generation (RAG) pipeline, and draft a personalized support response. The Large Language Model (LLM) thinks, calls a tool via the Model Context Protocol (MCP), observes the immediate JSON result, and outputs a flawless answer in your local development environment. </p> <p>Then you deploy it to an enterprise production environment. </p> <p>Within hours, your Laravel application starts throwing 504 Gateway Timeouts. Your PHP-FPM workers are entire

Результат

<p>The demo works flawlessly. You ask the AI agent to analyze a customer's billing history, query the internal documentation via a Retrieval-Augmented Generation (RAG) pipeline, and draft a personalized support response. The Large Language Model (LLM) thinks, calls a tool via the Model Context Protocol (MCP), observes the immediate JSON result, and outputs a flawless answer in your local development environment. </p> <p>Then you deploy it to an enterprise production environment. </p> <p>Within hours, your Laravel application starts throwing 504 Gateway Timeouts. Your PHP-FPM workers are entire

Доказательства

Architecting Stateful AI Agents in Laravel: Bridging n8n, MCP, and RAG for Production Workflows

Источник