SAN FRANCISCO, CALIFORNIA – 27/01/2026 – () – While companies expand AI adoption in analytics, they continue to face a common obstacle: although AI is capable of producing queries and insights, the actual implementation of analytics is still predominantly manual. Maintaining metrics, updating dashboards, and governing business logic require labor-intensive procedures that delay delivery and heighten operational risk.
GoodData has launched its MCP Server to the public, a new feature that transitions AI analytics from supportive analysis to controlled implementation. Designed to assist AI developers, business intelligence, and data teams, the MCP Server allows AI to create, oversee, and run analytics workflows within a managed setting, greatly speeding up the delivery of analytics results.
The MCP Server utilizes the Model Context Protocol (MCP) to enable AI agents and large language models to link directly to the GoodData platform. Via this link, AI can manage controlled analytics resources like semantic models, metrics, dashboards, and alerts across their entire lifecycle. This method removes the necessity for screenshots, manual SQL transfers, or fragile user-interface automation, enabling analytics processes to be constructed, modified, and run through code.
Initial applications show that this implementation-centric approach can decrease time-to-value tenfold, allowing companies to transition from testing to operational analytics much faster. By handling analytics resources as executable infrastructure, teams can automate modifications, perform ongoing analysis, and distribute updates securely across systems without continual manual involvement.
In contrast to conventional AI-powered BI tools that function above dashboards, GoodData’s MCP Server integrates AI directly into the analytics core. Analytics-as-code, controlled APIs, and LLM-powered logic collaborate to guarantee consistent definitions, ongoing validation, and compliance with enterprise governance standards.
Every action carried out by AI agents follows the identical security, permission, and governance rules that apply to human users. This guarantees that the system enforces business rules automatically, decreasing reliance on individual knowledge while enhancing reliability and compliance.
Using MCP Server, analytics teams can speed up BI development by letting AI generate and manage analytics resources, cutting down backlogs and removing manual setup tasks. Once established, analytics can operate continuously, automatically running queries, refreshing dashboards, scheduling alerts, and synchronizing logic. Furthermore, any MCP-compatible AI agent can securely utilize GoodData’s analytics features within a unified governance structure.
This launch indicates a wider analytics transition from human-driven implementation to platform-powered automation, enabled by the combination of standardized AI execution protocols, programmable analytics, and progressively advanced large language models. Collectively, these developments convert analytics into a scalable framework that companies can modify and expand as AI usage increases.
The MCP Server is currently accessible as a component of the GoodData platform.
About GoodData
GoodData is an AI-native decision intelligence platform created to assist enterprises in transforming reliable data into actionable insights. Designed for controlled and scalable analytics, the platform allows organizations to implement insights, automate decisions, and integrate intelligence directly into products and workflows. Featuring a composable architecture and a controlled semantic layer at its foundation, GoodData delivers transparent, auditable, and secure AI-driven analytics for global enterprises.