Laravel Is Becoming an AI Platform – and That Changes More Than You Think

• by Tobias Schäfer • 6 min read
#Laravel #AI #PHP #E-Commerce #MCP

At Laracon India 2026, Taylor Otwell unveiled something that goes far beyond a new package: an official AI SDK, an MCP server framework, and an AI assistance system for developers. Together, they make Laravel the first major PHP platform to treat AI as a first-class citizen.

What does this mean – not for developers who love new toys, but for businesses that make money with Laravel?

What Happened: Three Announcements, One Strategy

1. Laravel AI SDK

An official first-party SDK for AI integration. Not a community package, not a wrapper – an official part of the framework.

What it can do:

  • Agents as PHP classes with their own instructions, tools, and structured output
  • Text, image, audio, transcription through a unified API
  • Embeddings and vector search with PostgreSQL integration
  • Provider failover between OpenAI, Anthropic, Gemini, and more
  • Queues, streaming, testing – all Laravel-native

The key point: it feels like Laravel. Not like a foreign body that someone bolted on.

2. Laravel MCP (Model Context Protocol)

MCP is a standard that defines how AI clients (Claude, ChatGPT, Cursor) communicate with your application. Laravel MCP makes it easy to set up your Laravel app as an MCP server.

Why this matters: instead of you integrating AI into your app, any AI can access your app – with defined tools, resources, and prompts.

3. Laravel Boost

An MCP server with over 15 tools that gives AI coding agents (Claude Code, Cursor, Copilot) deep insight into your Laravel app – database, routes, Artisan commands, logs, and over 17,000 pieces of Laravel documentation.

This isn’t a feature for your end users. It makes your developers faster.

What This Means for Shop Owners

If you run a Shopware or Laravel-based shop, here’s what changes:

AI Features Get Cheaper

Until now, developing AI features for a shop was a custom project: your own API connection, your own abstractions, your own error handling. The AI SDK reduces the effort significantly.

Specifically: what used to take weeks – for example, an intelligent product advisor that answers questions about your catalog – can now be implemented in days.

// A product advisor in under 50 lines
$agent = agent(
    instructions: 'You are an advisor for OutdoorPro...',
    tools: [
        SimilaritySearch::usingModel(Product::class, 'embedding'),
    ],
);

return $agent->stream('Which backpack works for a 5-day tour?');

The built-in vector search means: your shop can find products even when the customer doesn’t know the right words. “Something light for my back on long hikes” finds the ultralight backpack – even without the word “backpack.”

This used to be enterprise technology. Now it’s an Eloquent query.

Automated Content with Quality Control

The SDK makes structured output trivial. You define a schema, and the AI delivers exactly the format you need – title, description, meta tags, keywords. No parsing, no hoping.

For mitKai, this was one of the biggest technical challenges. Now it’s a single method in an agent class.

What This Means for Agencies

New Services Become Possible

With the AI SDK, agencies can add AI features as a standardized offering to their portfolio:

  • Intelligent product search – Vector-based, integrable into any Laravel project
  • Content generation – Product descriptions, blog articles, FAQ answers
  • Chatbots and advisors – Based on real shop data, not generic ChatGPT
  • Automated workflows – Order classification, support triage, review analysis

Development Effort Drops

The testing tools alone are reason enough. Agent::fake() means: AI features can be integrated into CI/CD pipelines without real API calls. This was an unsolved problem at many agencies.

MCP as a New Channel

When your client has an MCP server, AI assistants can interact directly with their app. This opens entirely new possibilities – for example, a Claude agent that checks orders, creates invoices, or queries inventory levels, without anyone opening a dashboard.

What This Means for the PHP Ecosystem

Let’s be honest: PHP hasn’t played a role in the AI space in recent years. Python and JavaScript have the tools, the frameworks, the community. Anyone who wanted to integrate AI into a PHP project had to either build HTTP calls manually or rely on community packages like Prism.

That’s changing now.

Laravel as an AI Platform

The AI SDK isn’t just a package – it’s a statement. Laravel is saying: AI integration isn’t a niche, it’s a core feature. And they’re doing it better than most alternatives:

  • Provider-agnostic – You’re not locked into OpenAI
  • Testable – No other framework has comparable testing tools for AI
  • Laravel-native – Queues, events, middleware, Eloquent – everything works together
  • MCP as standard – Your app becomes an AI endpoint, not just an AI consumer

Prism Isn’t Going Anywhere

The community package Prism by TJ Miller is approaching version 1.0. It’s leaner than the official SDK and remains a good choice for projects that only need text generation. Laravel has even officially acknowledged Prism – a sign that community and official tools will coexist.

My Take

I’ve been building AI features with Laravel for years – most recently for mitKai, a platform that has generated over 60,000 product descriptions for dozens of shops. Much of what the AI SDK now offers, I built myself: provider abstractions, structured output, queue handling, embedding pipelines.

Here’s my honest conclusion:

The Laravel AI SDK is the most important Laravel release since Eloquent.

Eloquent defined how PHP developers work with databases. The AI SDK will define how PHP developers work with AI.

For shop owners, this means: AI features become cheaper, faster to implement, and more maintainable. The barrier to entry drops from “need a specialized developer” to “any good Laravel developer can do this.”

For agencies: anyone who doesn’t start getting familiar with the SDK now will be explaining in 12 months why their competitors are delivering AI features faster and cheaper.

Next Steps

If you have a Laravel project and are planning AI features:

  1. Install the SDK and build a simple agent – just to get a feel for it
  2. Identify a concrete use case in your project – product search, content generation, support automation
  3. Start small – One agent, one tool, one structured output. Not everything at once.

If you want to know what this could look like in your specific project – drop me an email. I’m happy to help assess whether and where AI integration makes sense for you.

For the developers among you: in the companion article Laravel AI SDK: A Practical Guide with Real Code Examples, I show the SDK hands-on – from agents to embeddings to testing.