SAN FRANCISCO, CALIFORNIA – 27/01/2026 – (SeaPRwire) – As enterprises scale their use of AI in analytics, many still encounter a familiar bottleneck: while AI can generate queries or insights, the execution of analytics remains largely manual. Metrics must be maintained, dashboards updated, and business logic governed through time-intensive processes that slow down delivery and increase operational risk.
GoodData has announced the public release of its MCP Server, a new capability designed to shift AI analytics from assisted analysis to governed execution. Built to support AI developers as well as business intelligence and data teams, the MCP Server enables artificial intelligence to design, manage, and operate analytics workflows in a controlled environment, significantly accelerating the delivery of analytics outcomes.
The MCP Server leverages the Model Context Protocol (MCP) to allow AI agents and large language models to connect directly with the GoodData platform. Through this connection, AI can work with governed analytics assets such as semantic models, metrics, dashboards, and alerts throughout their full lifecycle. This approach eliminates the need for screenshots, manual SQL transfers, or brittle user-interface automation, allowing analytics processes to be built, updated, and executed programmatically.
Early use cases demonstrate that this execution-focused model can reduce time to value by an order of magnitude, enabling organizations to move from experimentation to production analytics far more quickly. By treating analytics assets as executable infrastructure, teams can automate changes, run continuous analysis, and propagate updates safely across systems without repeated manual intervention.
Unlike traditional AI-enabled BI tools that operate on top of dashboards, GoodData’s MCP Server embeds AI directly into the analytics foundation. Analytics-as-code, governed APIs, and LLM-driven logic work together to ensure that definitions remain consistent, validation is continuous, and execution adheres to enterprise governance standards.
All actions performed by AI agents operate under the same security, permissions, and governance policies applied to human users. This ensures that business rules are enforced by the system itself, reducing dependency on individual expertise while improving reliability and compliance.
With MCP Server, analytics teams can accelerate BI development by allowing AI to create and maintain analytics assets, reducing backlogs and eliminating manual configuration work. Once defined, analytics can run continuously, with queries executed, dashboards refreshed, alerts scheduled, and logic kept in sync automatically. In addition, any MCP-compatible AI agent can safely leverage GoodData’s analytics capabilities under a unified governance framework.
The release reflects a broader shift in analytics from people-driven execution to platform-driven automation, made possible by the convergence of standardized AI execution protocols, programmable analytics, and increasingly capable large language models. Together, these advances transform analytics into a scalable system that organizations can adapt and extend as AI adoption grows.
The MCP Server is available now as part of the GoodData platform.
About GoodData
GoodData is an AI-native decision intelligence platform designed to help enterprises convert trusted data into informed action. Built for governed and scalable analytics, the platform enables organizations to operationalize insights, automate decision-making, and embed intelligence directly into products and workflows. With a composable architecture and a governed semantic layer at its core, GoodData supports transparent, auditable, and secure AI-powered analytics for enterprises worldwide.