Your analytics data already holds the answers your team needs.
The problem is getting to them fast enough.
You need to check last week’s campaign performance. Compare traffic sources. Understand why conversions changed. Pull the right numbers before a meeting. All of that, before you can even answer the original question…
Matomo MCP helps reduce that friction.
With the new Matomo Model Context Protocol (MCP) Server, you can connect Matomo to AI tools like Claude, ChatGPT or OpenAI Codex, then ask questions in plain language and get answers based on your real analytics data.
Your team shifts from « Where can I find the right data to understand the situation? » to « What should we do next? ».
Why this new AI feature matters
Analytics should help your team make better decisions. But too often, the gap between question and answer slows the work down. And this matters even more with AI-assisted work becoming a normal part of modern data workflows.
Matomo MCP reduces that gap at every stage:
- Faster answers for marketers, analysts, product teams and team leads, with less time spent navigating reports.
- Less friction across teams, because people can self-serve insights instead of waiting for someone to pull the numbers.
- More room for actual analysis, because data gathering stops being the bottleneck.
- A single conversation flow that supports follow-up questions, so you can dig into the why behind a number without starting from scratch.
This is especially relevant for teams that report on performance regularly, monitor campaigns across channels, or just want a quick read before a meeting. Matomo MCP helps your team get to a first answer faster.
It’s also relevant if you are evaluating Matomo against other analytics platforms. AI-assisted analytics is becoming a baseline expectation. Matomo MCP brings that capability into your workflow without turning your analytics data into another black box. You choose the AI tool, you control permissions, and Matomo remains the place where your analytics data is stored and managed.
What Matomo MCP does
MCP stands for Model Context Protocol. It’s an open standard that lets AI tools connect to your data and tools in a secure, structured way.
In Matomo, the MCP Server works as a bridge between your AI tool and your analytics data.
Here’s how it works:
- The AI tool turns that data into a clear answer.
- You ask a question in your AI tool.
- The AI tool sends the request through the Matomo MCP Server.
- Matomo retrieves the relevant analytics data.
No time to explore everything now? Download our MCP guide and keep the practical prompts, setup links and use cases ready for when your team starts using Matomo MCP.
What our MCP changes in your daily work
Three ways teams are starting to use Matomo MCP.
| Use case | Without MCP | With MCP |
|---|---|---|
| Explore performance faster | Open Matomo, filter by date, browse several reports, note key numbers | Ask a plain-language question to your AI tool, get the picture in seconds |
| Summarise reports and changes | Compare periods manually, screenshot charts, write up the changes | Ask the AI to summarise what changed, then refine the draft |
| Analyse patterns across segments | Build segments one by one, switch between reports to compare | Ask cross-cutting questions in a single conversation, chain follow-ups |
| Prepare meetings | Pull numbers from multiple places | Get a quick overview before discussing actions |
Some questions you can ask straight away:
- « What were my top 5 traffic sources last week on [your site]? »
- « Summarise our top traffic sources this quarter and highlight the main changes compared with last quarter. »
- « Which campaigns brought the most conversions and revenue last quarter? »
- « Compare conversion rates between mobile and desktop users for the past quarter. »
A note worth flagging: AI tools summarise well, but they can also make mistakes. We recommend verifying important numbers in Matomo before sharing them with stakeholders or clients.
What you stay in control of
Because Matomo MCP connects your analytics to an external AI tool, you decide:
- Which AI tool connects to your Matomo instance.
- What data the tool can access.
- Which permissions are granted through API tokens or OAuth 2.0 scopes.
- Whether access is read-only or includes broader permissions.
This is the part of the announcement we want to be clear about. AI in your analytics workflow raises two questions: who controls the data, and how accurate that data is. Matomo MCP is built for both. Your team keeps full control of access, by design. And because Matomo collects unsampled, first-party data, your AI tool works from a complete picture, so the insights you get reflect what’s actually happening. Learn more about Security considerations for the MCP Server in our Knowledge Base.
Where to start
Matomo MCP is now available on Matomo Cloud and on Matomo On-Premise.
If you are already using Matomo, head to our resource guide How you can use Matomo MCP to make faster, smarter decisions. It walks you through what MCP enables for marketers, analysts and product teams, with prompt examples, setup links, and tips for responsible use.
If you are evaluating Matomo, start a free trial to see how the platform combines privacy-first analytics with the kind of speed your team actually needs.
Analytics, in your team’s language
Matomo MCP helps your team move faster from analytics data to business decisions.
You can ask questions in plain language, explore results faster and turn your Matomo data into clearer next steps.
Matomo MCP adds AI to your analytics workflow without changing what makes Matomo trusted: your data stays with you, your team controls access, and your AI tool works from complete, unsampled data.
Faster decisions, in plain language, on data you can trust.
Want to learn more about our MCP? Download our free guide now to learn how to ask better questions, summarise reports faster and turn Matomo analytics into business decisions you can act on.
