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AI built for marketers.
Predict, create, and optimize — without waiting on data, dev, or design.
Why it matters:
In reading this post, marketers will learn how Optimove MCP connects AI tools such as Claude and ChatGPT with the data, workflows, and expertise inside Optimove. Through five practical use cases, they will see how to analyze performance, explore account data, build audiences, draft campaigns, and access platform knowledge without leaving their preferred AI environment.
Key takeaways:
The way marketers work has fundamentally shifted. AI tools like Claude have become where the thinking starts, questions are answered, strategies take form, and campaigns are shaped. At the same time, the supporting work lives anywhere else: data in spreadsheets, briefs in planning tools, context spread across a dozen different environments.
The Optimove MCP brings Optimove into the marketers' AI world, so data analysis, audience segmentation, email creation, and platform knowledge can be made without switching tools.
Here's what sets Optimove's MCP apart from the rest, and five real use cases where you can learn from.
The Model Context Protocol (MCP) is an open standard that lets AI tools connect to external platforms and take real actions inside them. Most vendors that have built MCP servers stopped reading access, meaning the AI can surface insights, but it can't take real action on them.
Optimove went further. Its MCP is built for both: AI tools can analyze what's happening inside the platform and act on it, in the same workflow. In other words, Optimove MCP is not just a way to query data, but a way to get work done using the AI tools marketers are already used to.
For a deeper look at how MCP fits into Optimove’s AI strategy, read our full overview.
The MCP works with any AI tool, such as Claude, ChatGPT, or whatever is already in a team's stack. Here are the four core functions of Optimove MCP:
By connecting the Optimove MCP to its preferred AI tool, a marketer can ask questions directly to it and get a full performance breakdown, like campaign results, KPI summaries, lifecycle coverage, and churn indicators.
From the same conversation, they can ask the tool to turn the analysis into an Excel report, build a PowerPoint summary, or more, without switching tools.
Before building anything, marketers need to know what's already there — which segments are live, which channels are configured, or which attributes already exist. An iGaming operator, for example, can ask the Optimove MCP to show all segments that include VIP customers before creating a new one, ensuring no duplicate or conflicting logic.
What used to mean navigating multiple screens or waiting on a platform team, now happens in the same conversation where the work is being done.
If a marketer needs to target, for example, high-value customers who haven't engaged in 30 days, with the Optimove MCP's Builder capabilities, they describe the audience in plain language, and the segment is created directly inside Optimove, already configured, validated, and ready to use.
The same works for email. A marketer shares a campaign brief with the target audience, offer, and context, and the MCP drafts the email inside the platform, ready for review. No back-and-forth, no separate tool.
Rather than searching through Optimove's documentation mid-workflow, marketers can ask through their AI tool. The Expert function connects directly to Optimove's knowledge base, including the Optimove Academy and the developer documentation, and returns an accurate, sourced answer in the same conversation.
For example, a marketer building a campaign with Optimove's AI Offer Decisioning agent asks "How does the AI Offer Decisioning Agent make its decisions?" and gets back an answer sourced directly from the Knowledge Base, including the role of Customer DNA and how it influences offer selection. A technical marketer or developer can ask about connector setup or API configuration and get answers sourced from the developer docs.
The real power of the Optimove MCP is when the functions chain together. A marketer spots a churn spike in their KPIs, and an analyst surfaces it. They ask the Expert how churn probability is calculated and get the Academy explanation on the spot. They use Explorer to check which high-value attributes are available. They build the at-risk segment, create the retention journey, and draft the campaign email, all through the Builder, without leaving the conversation.
Each action flows from the last. No platform-switching, no documentation tab, no support ticket. The marketer stays in context from question to activation.
The Optimove MCP meets marketers where they already work and does more than surface what's there. It acts. Performance data gets analyzed, account information gets explored, segments get built, emails get drafted, and platform questions get answered, all from a single conversation, all landing directly inside Optimove. The marketer stays in the loop from the first prompt to the final approval.
For more insights, contact us to request a demo.
Agents that let you act while others are still analyzing!
Sophie is a product marketing manager with a communications and marketing background. She specializes in go-to-market strategy, product messaging, and digital engagement for SaaS and B2B companies. She combines creative storytelling with a data-driven mindset to clarify product value and build stronger connections with target audiences. Sophie holds a degree in Communications and Marketing from Reichman University (IDC Herzliya).
What AI tools does the Optimove MCP work with?
The Optimove MCP is compatible with any AI tool that supports the Model Context Protocol, including Claude, ChatGPT, and others.
Does the Optimove MCP execute campaigns automatically?
No. Everything the MCP creates—segments, journeys, triggers—is built in draft state. Marketers review and activate through the standard Optimove interface.
What can marketers build through the Optimove MCP?
Marketers can analyze campaign performance, explore customer attributes and segments, build target groups, create campaign emails from a brief, and access Optimove's knowledge base—all through plain-language prompts in their AI tool.
How is MCP different from a standard API integration?
A standard API requires custom code for each integration. MCP is a universal protocol: once a platform publishes an MCP server, any compatible AI agent can connect to it without custom development work.
What Optimove functions does the MCP expose?
The Optimove MCP has four core functions: Analyst (campaign performance data and insights), Explorer (discovering available attributes, segments, and channels), Builder (creating segments, emails, and importing external lists), and Expert (on-demand answers from Optimove's knowledge base).
