We’re excited to introduce Hubble MCP, a new way to interact with your research.

For years, user research has been packaged into static outputs: reports, slide decks, highlight reels, and summaries. These outputs are valuable, but they come with a fundamental limitation which is that they are static. The moment a report is delivered, it begins to lose context. New questions emerge, stakeholders want to dig deeper, and teams are forced to either sift through hours of recordings or run additional studies just to uncover insights that likely already exist.

This is the gap Hubble MCP is designed to solve. With MCP, research is no longer something you simply consume; it’s something you can actively engage with. Instead of digging through past studies, you can ask questions directly across your entire body of research. Whether it’s interviews, usability tests, surveys, or product feedback, MCP allows you to query and synthesize insights instantly, surfacing relevant patterns, themes, and supporting evidence in real time.

At its core, MCP transforms research into a queryable system. You can ask things like:

• What are the most common pain points users mentioned during onboarding?
• How do enterprise users differ from SMB users in their workflows?
• What issues are repeatedly showing up across recent usability tests?

And instead of manually piecing this together, MCP returns structured answers grounded in your actual research with references back to source data like transcripts, clips, and notes.

What makes this especially powerful is the ability to connect insights across studies. Traditionally, research lives in silos—each study is analyzed independently, and cross-study synthesis is time-consuming and often inconsistent. MCP changes that by allowing teams to identify patterns across multiple studies automatically, giving a more holistic and reliable view of user behavior over time.

This shift has major implications for how teams operate.

First, it dramatically accelerates decision-making. Teams no longer need to wait on reports or dedicate hours to analysis—they can get answers on demand. Second, it increases the ROI of every study you run. Instead of insights being locked within a single project, they become part of a growing knowledge base that compounds in value over time.

But perhaps most importantly, MCP makes research truly cross-functional.

Historically, access to research insights has been bottlenecked by the research team itself. Stakeholders rely on researchers to interpret findings, generate reports, and answer follow-up questions. While this ensures rigor, it also limits speed and accessibility.

With MCP, anyone in the organization—product managers, designers, marketers, executives—can explore research directly. They can ask their own questions, follow their own curiosity, and get immediate answers without needing to go through a formal research request. This doesn’t replace researchers—it amplifies their impact by making their work more accessible and reusable across the organization.

MCP also fundamentally changes how research scales.

As your organization runs more studies, the volume of data grows rapidly. Without the right system in place, this data becomes increasingly difficult to manage and leverage. MCP turns that growing dataset into an asset rather than a burden. The more research you conduct, the more context MCP has to draw from—resulting in richer insights, stronger patterns, and more confident decision-making.

Under the hood, MCP is designed to work seamlessly with the rest of the Hubble platform. It builds on top of your existing workflows—AI-moderated interviews, usability tests, surveys, and moderated sessions—automatically structuring and indexing your research data so it’s ready to be queried at any time. There’s no additional setup required, and no need to change how your team runs studies today.

Importantly, MCP is grounded in transparency and control. Every insight is tied back to source data, allowing teams to validate findings and dig deeper when needed. AI is used to assist with synthesis and discovery, but humans remain in the loop—defining research goals, interpreting results, and making final decisions.

Ultimately, Hubble MCP represents a shift from research as deliverables to research as infrastructure.

Instead of producing static outputs that age over time, teams can now build a living system of insights—one that evolves continuously, adapts to new questions, and becomes more valuable with every study.

This is how research becomes faster, more scalable, and more impactful across the entire organization.

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