Oracle Analytics

The Oracle Analytics AI Assistant delivers strong natural-language querying—even in unsupported languages—but falls short when handling advanced analytics functions. With the introduction of the Oracle Analytics Cloud MCP Server, these limitations are removed, enabling AI-driven access to advanced features like trendlines and clustering that the built-in assistant could not handle.

Business analytics is shifting from static dashboards to interactive, narrative-driven experiences where users ask natural-language questions and engage in an ongoing analytical dialogue. This paradigm is enabled by LLMs as the new interface, RAG as the foundation for trusted, governed insights, and MCP servers as the integration layer. Together, they allow AI agents to securely operate analytics systems, delivering dynamic explanations, visuals, and insights on demand—without relying on constantly redesigned dashboards.

Enterprise analytics is evolving rapidly as BI platforms and AI models mature, raising expectations for faster, more intuitive, and proactive insights. While Oracle Analytics has already advanced with AI-driven features like Insights and the AI Assistant, a key limitation remained: powerful external AI tools couldn’t directly access enterprise analytics data. The MCP Server for Oracle Analytics removes this barrier by enabling secure, direct interaction between AI assistants and OAC, fundamentally changing how analytics and AI work together.

Between 15th and 18th October 2025, we had the opportunity to speak at the HROUG 2025 conference, held on the beautiful island of Crveni otok (Red Island) near Rovinj, Croatia.