A few months back, a client came to me with a problem that’s becoming a bit of a pattern. They wanted their AI assistant—specifically a custom Claude setup—to be able to “check stock” and “reorder supplies” directly from their WordPress dashboard. They’d already hired someone to build a bunch of custom REST API endpoints, but it was a total mess. The AI was hallucinating half the time because the endpoints were too verbose, and the token costs were starting to look like a mortgage payment. Not good.
My first instinct was to just tighten up the REST responses. I thought, “I’ll just filter the JSON output to the bare essentials.” And yeah, that saved a few pennies, but it didn’t solve the core issue: the AI still didn’t *understand* the capabilities of the site in a structured way. It was just guessing. That’s when I started looking into the WordPress MCP integration and the official adapter that’s being developed by the core AI team.
Why the MCP Adapter v0.3.0 Actually Matters
The Model Context Protocol (MCP) is the secret sauce here. Instead of treating your WordPress site like a dump of raw data, the MCP Adapter treats it as a collection of “tools” and “resources.” I saw the recent release announcement for v0.3.0 over at the WordPress Make blog, and it’s a massive step forward for anyone trying to build agentic commerce or AI-driven workflows.
The biggest hurdle in earlier versions was transport and observability. If the AI failed to call a function, you were basically flying blind. In v0.3.0, they’ve aligned everything with the latest HTTP specifications and, more importantly, improved how we see what’s actually happening between the AI agent and the WordPress Abilities API. It’s the difference between guessing why a script failed and actually seeing the error log. Trust me on this: you do not want to debug an AI agent without proper transport logs.
Registering Abilities the Right Way
To make this work, you need to register your functions using the Abilities API. Here’s a quick look at how I’d set up a basic inventory check that the MCP Adapter can then expose to an AI agent. Notice how we’re prefixing everything—standard practice to avoid collisions with other plugins.
<?php
/**
* Registering a custom ability for the MCP Adapter.
*/
add_action( 'wp_ai_register_abilities', function( $registry ) {
$registry->register_ability( 'bbioon/check-inventory', [
'title' => __( 'Check Product Inventory', 'bbioon' ),
'description' => __( 'Returns the current stock level for a specific product ID.', 'bbioon' ),
'callback' => 'bbioon_handle_inventory_check',
'args' => [
'product_id' => [
'type' => 'integer',
'required' => true,
'description' => __( 'The ID of the product to check.', 'bbioon' ),
],
],
] );
} );
function bbioon_handle_inventory_check( $args ) {
$product = wc_get_product( $args['product_id'] );
if ( ! $product ) {
return new WP_Error( 'bbioon_no_product', 'Product not found.' );
}
return [ 'stock_status' => $product->get_stock_status(), 'quantity' => $product->get_stock_quantity() ];
}Once this is in place, the MCP Adapter v0.3.0 takes that “Ability” and turns it into a “Tool” that an AI can discover. No more hardcoding endpoints. The agent just *knows* it has the tool and how to use it. It’s clean, it’s scalable, and it actually works.
The Bottom Line on WordPress AI Integration
The shift from raw APIs to the Model Context Protocol is where things are heading. Version 0.3.0 isn’t just a minor patch; it’s about making these connections reliable enough for production environments. Here’s the kicker: if you aren’t using the Abilities API to structure your data, you’re just making life harder for yourself and more expensive for your clients. Total nightmare avoided.
Look, this stuff gets complicated fast. If you’re tired of debugging someone else’s mess and just want your site to work with the latest AI tech, drop my team a line. We’ve probably seen it before.
Are you still building custom REST wrappers for your AI projects, or are you ready to switch to a standardized protocol like MCP?
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