Customer.io's MCP server: Your new automation superpower 

If you've been following the AI space lately, you've probably heard whispers about something called Model Context Protocol, or MCP. Don't worry if this is the first time you're hearing about it—MCP was only introduced by Anthropic in late 2024, so you're not behind the curve. In fact, you're perfectly positioned to be ahead of it.

This new protocol sounds technical—and it is—but it's also about to transform how you build, think about your audiences, and gather context from your tech stack. Whether you're a growth marketer, product manager, or marketing engineer, MCP gives you superpowers. Marketers get smarter insights faster. Technical users can build automations and integrations with AI as a real collaborator.

Here's the thing about AI assistants: they're incredibly smart at writing copy and suggesting strategies, but they're completely blind to your actual business. You can ask Claude to help optimize your email campaigns, but it has no idea who your customers are, what segments you've already built, or how your previous campaigns performed.

So you end up in this tedious dance: describe your business context, upload CSV files, explain your customer attributes, copy-paste campaign data... all before you can even start getting useful help.

It's like hiring a brilliant consultant who shows up to every meeting with amnesia.

Model Context Protocol is essentially a way for AI assistants to connect directly to your marketing tools and actually see what's there. Instead of working blind, AI can now peek into your Customer.io workspace and understand your business context instantly.

Think of it this way: instead of describing your customer segments to AI, it can just look them up itself.

Let's say you're working with Claude on a retention strategy. Here's how the conversation changes:

You: "I want to create a re-engagement campaign for users who haven't been active lately."

Claude: "Let me check what segments you already have for inactive users..."

[Claude searches your Customer.io workspace and finds your existing segments]

Claude: "I can see you have an 'Inactive subscribers' segment with 3,247 users who haven't opened an email in 60+ days, and a 'Dormant users' segment for people who haven't logged in for 30+ days. You also have custom attributes for last_purchase_date and engagement_score.

Based on your existing setup, I'd recommend creating a new segment that targets users with an engagement_score below 3 who have made a purchase in the last 90 days but haven't opened an email in 30 days. This would be your highest-value re-engagement opportunity.

Would you like me to generate the segment logic for this?"

[Claude creates the segment definition using your actual attribute names and data]

Claude: "Here's the segment I've created: 'High-value dormant customers' with 847 users. Now I can write personalized copy that references their purchase history and suggests relevant products based on your customer data."

No more explaining your business setup. No more generic advice that doesn't fit your data structure. Just AI that actually understands your workspace and can give specific, actionable recommendations.

We’ve just launched our own MCP server and are already witnessing customers leverage it as part of their marketing workflow. As part of early access, we’ve seen technical users build integrations faster by pairing themselves up with Cursor, and marketers like myself have developed user personas at lightening speed (and taken action against them) when pairing up with Claude.

We've invested in launching our MCP server because we believe the future of marketing work is collaborative, not transactional. Instead of switching between AI chat windows and your marketing tools, you should be able to work with AI that actually knows your business.

Right now, our MCP server gives AI assistants the ability to:

• Generate segments using your actual customer attributes and behavioral data
• Inspect customer profiles to understand individual user journeys
• Search your workspace to find existing campaigns, segments, or data points
• Analyze your customer base using real attributes and engagement patterns

This means AI can give you advice that's grounded in your actual data, not generic best practices.

While your competitors are still explaining their business setup to generic AI assistants, you'll be working with AI that already understands your customer base, knows your existing segments, and can generate strategies based on your real data.

Here's what becomes possible:

Smarter segmentation: AI that suggests segments based on your actual customer attributes and behavioral patterns, not theoretical examples.

Personalized strategy: Recommendations that fit your specific customer journey, product catalog, and engagement history.

Data-driven copy: Email and campaign copy that references actual customer behaviors and attributes from your workspace.

Faster iteration: No more re-explaining your setup every time you want AI help with a new campaign.

We're at the beginning of a shift toward AI that doesn't just generate ideas, but actually understands your business context. The marketers who embrace AI tools with real workspace integration will move faster and make better decisions than those still working with context-blind assistants.

This is just the start. As MCP adoption grows, we'll see AI assistants that can not only understand your marketing data, but take increasingly sophisticated actions across your entire marketing stack.

The question isn't whether this future is coming—it's whether you'll be ready for it.

Ready to work with AI that actually understands your business? Connect Customer.io's MCP server and experience marketing strategy grounded in real data.