Reading Time: 5 minutes AI assistants are getting better at helping marketers work smarter. But there’s still one big challenge: tools and data don’t always talk to each other.  Lifecycle marketers know this struggle all too well. They manage campaigns across multiple platforms and often depend on engineering or BI teams just to get basic tasks done. However, Model Context Protocols (MCPs) could be a major breakthrough. This new open standard makes it possible for AI tools to connect directly with systems like CRMs, ESPs, analytics tools, and more, without needing custom integrations every time. To better understand what MCPs are and how they could reshape lifecycle marketing, we spoke with Aboli Gangreddiwar, a marketing leader who has been exploring MCPs and recently published a deep dive on Lifecycle Luminaries.  In our conversation, we explored how MCPs could potentially streamline marketing workflows, unlock deeper personalization, and even reduce dependency on engineering support. Let’s jump in.   What Are Model Context Protocols and Why Should Marketers Care Think of MCPs like a universal translator for your marketing stack. Just like HTTP allows any browser to access any website, MCPs allow AI agents (like ChatGPT or Claude) to interact with your marketing tools using a shared standard. “I think of it kind of like a USB-C for your marketing stack,” Aboli explained. “If you’re using Databricks as your CDP and Hubspot as your ESP, MCP could potentially let them talk to each other in a more seamless way. You wouldn’t need a BI ticket every time you want a new data field.” You still need to connect each tool to a Model Context Protocol, but once that’s done, any AI agent that supports the protocol can securely access and act on the tool’s data or capabilities, without needing a custom integration for each new agent or use case. This concept is exciting for lifecycle marketing because this function of marketing is very complex. It uses personalized, multi-channel campaigns to engage customers throughout their entire journey by leveraging data and technology. With lifecycle marketing, businesses can deliver targeted messages at the right time and through the right channel, maximizing customer lifetime value and achieving sustainable competitive advantage.  But that’s easier said than done, especially when your systems don’t play nicely together. Some of the most common challenges marketers face today include: Disconnected data across CRMs, ESPs, CDPs, and analytics tools Slow campaign execution due to manual workflows and tool-hopping Dependence on engineering for things like data access, new integrations, or field availability Time-consuming analysis of A/B tests and campaign performance “These pain points are why the potential of MCPs feels so exciting,” Aboli said. “If we could use a single interface to access campaign data, build emails, QA them, and even send them, it would fundamentally change the way we work.”   What Model Context Protocols Could Unlock The real power of MCPs is in how they can bring together all the disconnected parts of a marketer’s workflow. With the right setup, AI agents could pull data from your CDP, generate content in your ESP, QA the emails in Litmus, and trigger the send, all from a single prompt. “We’ve always had these disconnected steps in lifecycle marketing,” Aboli shared. “Building emails, testing them, pulling performance data. MCPs give you a vision where those tools can operate together more fluidly through natural-language interfaces.” Here are some of the most promising use cases marketers are starting to explore: Smarter segmentation using real-time data from multiple sources More personalized content based on live behavior and approved messaging Automated test analysis, including stat sig calculations and performance summaries Cross-channel orchestration, where AI picks the right message, timing, and channel based on user behavior Aboli pointed out that reporting alone is a huge opportunity. “Imagine your AI agent connects directly to Tableau, pulls campaign performance, calculates statistical significance, and summarizes the results for you. That would save hours of work every week.”   How to Get Started with MCPs as a Marketer: 4 Steps Even though most teams aren’t using MCPs at scale just yet, there are plenty of ways to start preparing and experimenting. Aboli shared a few low-lift ideas for teams who want to get ahead of the curve. 1. Start with documentation “Whatever lives in a marketer’s head needs to be written down,” she said. That includes campaign rules, funnel stages, brand guidelines, and compliance requirements. AI needs this context to be useful. 2. Try custom GPTs for everyday tasks You don’t need deep technical skills to build a custom GPT. Aboli recommends starting with high-volume tasks like email copywriting or proofing. “You can upload your templates, brand voice, common legal disclaimers, even your QA checklist. It won’t get you to 100%, but it can get you to 70 or 80.” 3. Test Zapier’s MCP integration Zapier recently launched MCP support in beta, giving marketers access to thousands of tools through a single interface. “If you’re already using tools like Databricks or BigQuery, you can explore simple automations without involving too much engineering resources,” Aboli said. 4. Start mapping your first agentic use case Not sure where to begin? Look at what’s slowing you down. “One area I see over and over is data activation,” Aboli said. “Marketers want to personalize campaigns but often don’t have access to the data they need. If MCP can help solve that, it’s a great place to start.”   How MCPs Could Reshape the Future of Lifecycle Marketing Model Context Protocols are still in their early stages, but they signal a shift in how lifecycle marketers can approach automation, personalization, and execution. For years, marketers have been forced to work around the limitations of their tools: waiting on data access, dealing with disconnected systems, and relying on manual processes that drain time and energy. MCPs offer a different vision, one where AI agents are not just helpful assistants but true collaborators. By allowing tools to “speak the same language,” MCPs make it possible for marketers to connect insights to action faster than ever before. Whether it’s building a segment, generating personalized email content, or analyzing campaign results, the pieces start to click into place more naturally. Of course, there’s still a gap between where the technology is today and the fully automated, AI-assisted workflows marketers dream about. But the path forward is clear, and it’s more accessible than it might seem. As Aboli emphasized, starting small with documentation, simple GPT setups, or lightweight integrations can provide real value while preparing your team for what’s coming next. Marketers who embrace these tools early will have a distinct advantage. They’ll be the ones moving faster, experimenting more confidently, and unlocking personalization at scale without burning out their teams. And as more vendors build support for Model Context Protocols, the barrier to entry will only continue to drop. “You don’t have to do it all today,” Aboli reminded us. “But you can start now.” If you’re a lifecycle marketer feeling the pressure of disconnected tools and data silos, this may be the moment to lean in, explore the possibilities, and take the first step toward a smarter, more connected future.   To learn more about MoEngage’s AI capabilities and how our platform supports B2C lifecycle marketers across industries, request a demo today. The post Model Context Protocols (MCPs): The Next Big Shift for Lifecycle Marketers? appeared first on MoEngage.