Building Better AI Agents for Laravel with Neo4j Boost

Laravel applications are complex systems of services, dependencies, models, and components. As applications grow, understanding how these pieces connect becomes increasingly difficult.

Knowledge Graphs represent these relationships as connected, queryable context. In this session, we’ll explore how we built Neo4j Boost, an open-source Knowledge Graph for Laravel, and how it transforms Laravel application architecture into graph-powered context.

In this session, you'll see how Neo4j represents Laravel architecture and how MCP (Model Context Protocol) connects this context with AI assistants. You'll learn why we built it, how it works, and how to use it in Laravel projects.

The session focuses on three key benefits: increased observability, efficiency, and correctness. We'll demonstrate how AI can use Knowledge Graph context to better understand Laravel architecture and how graph-based context can complement traditional code search.

The goal is to show how Knowledge Graphs + Neo4j + MCP + AI can give developers a deeper understanding of Laravel applications and their relationships.

1. Understand how Knowledge Graphs can represent Laravel architecture, dependencies, and relationships.

2. Learn how Neo4j and MCP connect Laravel application context with AI assistants.

3. See how graph-powered context can increase observability across complex Laravel applications.

4. Explore how it can increase efficiency in debugging, onboarding, and architecture exploration.

5. Understand how richer architectural context can support correctness, and learn why we built and how to use Neo4j Boost.