How MCP Turned AI Experiments into Real Product Ideas
At Diskover Data, we’re always exploring new ways to make unstructured data more accessible, more useful, and more actionable. For our VP of Product, Olivier Rivard, that journey recently took an exciting turn with the release of Anthropic’s Model Context Protocol (MCP).
Olivier has launched a new four-part blog series on Medium where he shares his personal experience using AI not just as a productivity tool, but as a true development partner. His goal: to explore how far AI can go in helping a product leader move from ideas to working prototypes.
The Spark: Why AI + MCP Changed Everything
Olivier had already been using tools like ChatGPT and Claude for writing and research. But with MCP, AI assistants could connect to real systems, pull live data, and take meaningful action.
That shift turned his experiments into product ideas. Instead of just brainstorming with AI, he was able to:
- Build a prototype connector that generated storage reports, usage trends, and file searches.
- Ask Claude to create tasks, analyze storage patterns, and even forecast growth.
- See the potential for customers to ask natural language questions like “How much cold data do we have in PowerScale?” and get actionable answers instantly.
Why This Matters
For IT teams managing billions of files across on-prem and cloud systems, the ability to combine AI with MCP opens new possibilities:
- Automating weekly health checks and cleanup tasks
- Surfacing insights across multiple systems
- Lowering the barrier for non-technical users to get meaningful answers
- Extending product capabilities without waiting for UI updates
As Olivier puts it: the real power of AI isn’t just answering questions — it’s in acting on the answers.
Read the Full Post
This is just the beginning of the series. In Part 1, Olivier shares:
- Why his work in unstructured data led him to explore MCP
- The first prototypes he built entirely with AI
- How these experiments are shaping the future of Diskover Data
Read Olivier’s full blog on Medium.
Stay tuned for Part 2, where he’ll dive into the origins of the CloudSoda AI Assistant, the technical decisions behind it, and lessons learned along the way.