Real AI usages with MCP and Matomo
- Enregistrée le 26/11/2025
Artificial intelligence is reshaping the way organizations understand their users, optimize their digital platforms, and automate complex workflows. When combined with the Model Context Protocol (MCP) and privacy-focused analytics tools like Matomo, AI becomes more than a buzzword — it becomes a practical, operational asset. This video explores real, concrete use cases that demonstrate how AI can enhance data quality, improve decision-making, and streamline digital performance measurement in a GDPR-compliant environment.
Using MCP, AI gains secure and structured access to data sources, enabling it to generate insights without compromising governance or user privacy. MCP acts as a universal translator between AI models and tools such as Matomo, ensuring that every action is logged, controlled, and permission-based. This creates a safe environment for automating repetitive tasks: generating dashboards, detecting anomalies, or creating insights summaries that would normally demand hours of manual work.
Matomo brings the analytics foundation to the equation. Its self-hosted and privacy-first architecture ensures that data stays under full control — a critical requirement when integrating AI into measurement workflows. When AI is connected to Matomo through MCP, new scenarios become possible: automatic tagging audits, content performance reports written in natural language, real-time detection of tracking issues, and even predictive models for user behaviour, all without sending third-party data to external clouds.
The video also highlights practical demonstrations, showing how marketing teams, analysts, and developers can collaborate through AI to build cleaner data structures, enrich custom dimensions, and validate tracking configurations. Instead of replacing expertise, AI acts as a force multiplier, giving teams better visibility and freeing them from tedious, error-prone tasks.
Ultimately, the combination of MCP and Matomo opens the door to a new generation of analytics workflows — ones that are intelligent, transparent, secure, and designed for real-world use.