12/19/2025

Releasing mcp-matomo - from frustration to Open Source: Building MCP Matomo in 30 Minutes

It’s Friday, December 19th. The coffee roasted spelt is still hot, and Hook0 team just pushed the "deploy" button.

We just shipped a massive update: a brand new design and completely overhauled documentation for Hook0, the open-source webhook sending infrastructure I co-founded. It feels good. But as the dust settled, I realized we needed to implement analytics on the new documentation pages.

Naturally, we reached for Matomo. It’s privacy-focused, ethical, and solid. But as I was setting it up, a thought struck me:

"Why am I still navigating dashboards, setting date ranges, and clicking through menus in 2025? Why can't I just talk to my data?"

I immediately started looking for a way to connect Matomo to Claude via the Model Context Protocol (MCP). I found exactly one solution.

The problem? It required routing my data through a third-party API and I had to ask them politely through a contact form to get access.

That was a hard No for me.

It goes against my core engineering values. I need future-proof solutions, not a solution that depends on an external black box for simple logic. I want autonomy. I want self-hosted reliability (or at least the ability to do so when needed, that's what we belive at Hook0 and Cloud-IAM). I want my data to stay mine.

So, I checked the clock. I opened my IDE along with some IA agents. And I decided to fix it myself.

I chose Rust for performance and reliability. Exactly 30 minutes later, I had a fully functional MCP server running locally. No external APIs, no subscriptions, just raw, direct access to the Matomo instance.

I’m open-sourcing it today because I believe analytics should be accessible and private.

Get the code on GitHub: FGRibreau/mcp-matomo (don't forget to star it!)

What Can You Do With It?

Instead of clicking through the UI, you can now simply ask Claude questions like:

"Show me the top 10 pages by visits this week, broken down by device type."

mcp-matomo connects to your instance, introspects the API, executes the necessary calls, and presents the answer. It covers almost everything Matomo tracks:

  • Traffic: Visits, unique visitors, bounce rates.
  • Acquisition: Referrers, search engines, campaigns.
  • Behavior: Entry pages, downloads, outlinks.
  • Tech & Geo: Devices, screens, countries.

What's Next?

Now that the tool is live, my next step is to deploy this across the ecosystem of companies I've created or co-founded. We need to democratize access to data for our teams without forcing them to become analytics experts.

I'll be rolling this out at:

  • Cloud-IAM: To track adoption of our managed Keycloak solution (ISO 27001 certified).
  • Netir: To better understand how freelancers, companies and mentors interact on our marketplace.
  • Natalia: To analyze how users engage with our unified AI ecosystem across Voice, WhatsApp, and Transcripts.

If you share the value of autonomy and want to talk to your data without a middleman, give it a try.

Feedback and PRs are welcome on GitHub!

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Made with on a hot august night from an airplane the 19th of March 2017.