Introducing the SegmentStream MCP Server

Today we’re launching the SegmentStream MCP Server — a way for AI assistants like Claude to directly connect to SegmentStream’s measurement and optimization engine and take action through it.

What is an MCP Server?

Model Context Protocol is an open standard developed by Anthropic that allows AI models to plug into external tools and data sources. Instead of just reading data, AI can now pull reports, run analyses, and execute changes — all in real time.

Why does this matter?

A lot of marketing tools are adding AI features right now. But most of them stop at “chat with your data” — you ask a question like “What was my ROAS last week?” and get a nicely formatted answer. It’s convenient, but it doesn’t fundamentally change how you work. You’re still the one interpreting the data, making decisions, and executing changes manually.

We think the real opportunity is much bigger. It’s not about making dashboards conversational — it’s about delegating entire workflows to AI. Performance analysis, forecasting, decision-making, and execution. End to end.

That’s what the SegmentStream MCP Server enables.

A few examples of what becomes possible

→ Ask AI to analyze channel performance and get recommendations grounded in ML-based attribution and incrementality — not misleading last-click metrics

→ Have AI identify underperforming budget allocations and reallocate spend across channels using SegmentStream’s optimization algorithms

→ Get AI-generated forecasts for next week’s performance and proactive suggestions before problems emerge

→ Delegate routine performance reviews entirely — the AI pulls the data, finds the insights, and surfaces what actually needs your attention

The underlying principle

AI is only as good as the data and tools it has access to. Give it broken attribution data, and it will make confidently wrong decisions. Give it SegmentStream’s measurement infrastructure — and it becomes a genuinely capable marketing co-pilot.

We’ll be gradually rolling this out over the coming weeks. If you’re interested to learn more or get early access — let us know in the comments or reach out directly.