Artificial intelligence (AI) has the potential to help marketers make smarter decisions, execute campaigns faster, lower costs, and achieve higher ROI. Model context protocol (MCP) will play a critical role in realizing that potential by helping reduce the complexity in adopting AI workflows and scaling them across the enterprise.
Ever since generative AI tools emerged, marketing teams have been using them to assist with creating, managing, and personalizing content. Agentic AI represents an opportunity to boost productivity and efficiency even further by deploying AI agents that can autonomously perform actions like optimizing campaign creative and sending offers to engaged prospects.
The challenge is that the growing plethora of AI tools adds a whole new layer to an already unwieldy martech stack. According to the 2025 MarTech State of the Stack Report, 62.1% of respondents use more tools than they did two years ago.
The tech sprawl shows no signs of stopping, either: while more than 58% plan to continue deploying products from commercial software vendors, nearly a quarter expect to see a rise of homegrown solutions within the next one to two years.
Connecting AI to all those tools and platforms involves far more than simply launching an application and walking through some setup menus. It’s forcing marketing teams to lean more heavily on their IT and developer teams. As it stands, Gartner Inc. research found 77% of engineering leaders see AI integration in applications as a major challenge.
WordPress is actively embracing MCP because it solves for this challenge while improving the way data works with AI to enhance the marketing journey from idea to intelligent content. This post will give you the low-down on what MCP is, how it brings value to enterprise marketers, and how it will enhance the way you use WordPress VIP.
What is MCP, and how does it work?
Originally developed by Anthropic, MCP is a standard that aims to help AI produce better, more relevant responses by connecting it to content repositories, development environments, and business tools.
MCP is like a USB port for connecting AI to marketing applications, or as a universal API layer.
Think about an enterprise marketing team whose stack includes a CMS, CRM, CDP, marketing automation platform, social media management tools, and analytics. There are AI solutions and use cases to support infusing the technology into every one of those areas. AI could help build a better audience for targeting ads, personalize campaigns to customer segments, and optimize campaign performance in real-time.
There are just two problems: the data sources that power each piece of the martech stack, and the number of integrations required to connect them.
The math here is as simple as it is frustrating: if you have five AI tools and 10 data sources, for instance, you’ll need 50 different integrations. This means turning to your IT department for connectors that are expensive to develop and difficult to effectively maintain.
MCP provides a single protocol that can connect any AI tool to any data source. By providing context such as schemas, user histories, and analytics, you can discover what functions and data are available that an AI agent can use on a particular system. Examples include publishing content, building a target audience segment for a campaign, building message variants, or processing a refund in a payment.
This means you’re using a single protocol to integrate AI everywhere within your martech stack. This not only allows for greater scalability in using AI throughout marketing departments, but also serves to future-proof organizations as AI evolves.
Traditional content structures are built for humans and display, not AI.
MCP turns content into an AI-ready dataset — enabling smarter tools, assistants, and automations.
MCP works in two ways: your marketing tools expose their capabilities through MCP servers, while AI applications connect to the servers as MCP clients. As a result, MCP can pull from internal, brand-safe data rather than relying on its own training data or long prompts, which reduces the risk of hallucination.
What are some of the top MCP use cases for AI in marketing?
Some of the most promising MCP use cases for marketers include:
Content discovery and analysis
Enterprise marketers create a lot of content, to the point where some can be lost or forgotten. MCP will allow marketers to use AI to prioritize which content needs to be refreshed, such as product pages that require updated descriptions and pricing, or blog posts that lack meta descriptions.
MCP can also help marketing teams determine content gaps they need to fill by making it easy for AI tools to find content that mentions competitor brands but not their own.
Instead of static API endpoints, your frontend applications can make dynamic requests like “find the most relevant case study for a healthcare visitor from California,” and MCP intelligently queries WordPress VIP, cross-references customer data, and returns relevant content.
Automated content operations
The premise of most AI deployments is freeing up employees from manual, repetitive, or otherwise onerous work so they can concentrate on higher-value tasks. MCP allows organizations to deliver on that premise by streamlining this work on marketers’ behalf.
Whether it’s updating product descriptions to include new security certifications, localizing website content for international audiences, or repurposing social media and blog posts, MCP will allow marketers to finally get the value they expected from AI.
Omnichannel content intelligence
The martech stack has expanded in part because brands are increasingly looking at how to show up in emerging channels where their audiences are likely to be found. We saw this with the rise of social media and messaging apps, and it will only continue.
Instead of creating bottlenecks that risk putting brands behind, MCP will let enterprises instantly access their entire content ecosystems through platforms like WordPress VIP without custom API development.
How is WordPress VIP using MCP?
MCP for marketing isn’t a future trend. It’s a shift that’s well underway. Automattic has already developed a WordPress MCP adapter and WordPress MCP plugin. These will allow enterprises to connect LLMs to WordPress data and workflows securely. By feeding AI with fresh content, context, and metrics, your CMS becomes the beating heart of your martech stack.
While MCP offers marketers considerable flexibility and autonomy, there are risks to integrating AI without effective guardrails. WordPress VIP helps by addressing security threats such as DDoS attacks and enabling the scalability large organizations expect, and offers developer tools that will foster greater AI innovation.
In time, enterprise marketers may not need to pay much attention to MCP, or may even take it for granted. There will be no surer sign that they can finally work at the speed of AI.
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Shane Schick
Founder, 360 Magazine
Shane Schick is a longtime technology journalist serving business leaders ranging from CIOs and CMOs to CEOs. His work has appeared in Yahoo Finance, the Globe & Mail and many other publications. Shane is currently the founder of a customer experience design publication called 360 Magazine. He lives in Toronto.