SAN FRANCISCO, CALIFORNIA — January 21, 2026 — Leads & Copy — GoodData has launched its MCP Server, designed to automate analytics execution. The platform combines Model Context Protocol (MCP), analytics-as-code, and large language models (LLMs) to accelerate the process.
According to GoodData, most tools are limited to query generation, requiring teams to manually manage metrics, dashboards and business logic when organizations adopt AI in analytics. The MCP Server aims to move AI beyond analysis, enabling governed, end-to-end analytics execution.
The company says this delivers 10-50x faster time to value.
GoodData says the MCP Server is designed for AI developers, and BI and data teams who want to build and manage analytics faster with AI. It allows AI to build and operate analytics in the same way a skilled human team would, but faster and without operational bottlenecks.
AI agents and LLMs can connect directly to GoodData using the Model Context Protocol (MCP) and execute analytics across the full lifecycle, according to the company. They can work with governed analytics assets, including semantic models, metrics, dashboards and alerts, without relying on screenshots, SQL copy-and-paste or fragile UI workflows. GoodData says this means AI can build, update and run analytics processes and agentic workflows automatically, while respecting the same rules and controls as human users.
CEO and Founder of GoodData Roman Stanek said that analytics has been limited by execution, not questions. He said with MCP Server, the company is turning analytics into an executable system that AI can safely operate under governance, fundamentally changing how fast organizations can build, adapt and scale AI analytics.
GoodData’s MCP Server shifts AI from interacting with analytics to executing within it, the company said. Rather than layering AI on top of dashboards or query interfaces, MCP exposes analytics as executable infrastructure.
By combining analytics-as-code, governed APIs and LLM-based coding, MCP Server allows AI to create, modify and validate analytics assets directly. Definitions remain consistent as they evolve, analysis runs continuously and changes propagate safely, without requiring manual intervention at every step.
The company said all execution takes place under the same security, permissions and governance model used by human teams. Business rules are enforced by the system rather than relying on individual knowledge, reducing operational risk while increasing speed and reliability.
According to GoodData, with MCP Server, analytics and BI assets become programmatic resources that AI can work with directly:
Analytics-as-code allows AI to build and update analytics automatically, reducing BI backlogs and eliminating manual UI-driven work.
Once analytics are defined, execution is ongoing, data is queried, results are computed, dashboards are updated, alerts are scheduled and logic remains in sync.
Any MCP-compatible agent can safely use GoodData’s full analytics capabilities, modelling, metrics, queries, alerts and validations, under the same governance controls as human experts.
Field CTO at GoodData Peter Fedorocko said that GoodData’s MCP Server turns analytics assets, such as semantic models, metrics and dashboards, into software resources. He said any AI agent can work with them using the same APIs, permissions and governance controls as engineering teams, delivering 10-50x faster time to value.
GoodData believes this shift is possible because three advances have converged: MCP provides a standard execution layer for AI, analytics-as-code makes analytics programmable, and modern LLMs can reliably operate complex systems within defined constraints. Together, they transform analytics execution from a linear, people-bound process into a scalable platform capability.
GoodData is an AI-native decision intelligence platform designed to help enterprises turn trusted data into confident action. The company said that designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions, and embed intelligence directly into products and business workflows.
The company said that with a composable architecture and a governed semantic layer at its core, GoodData ensures AI-powered analytics are transparent, auditable, and aligned with how enterprises define and trust their data. Organizations use GoodData to move from insight to impact faster, while maintaining enterprise-grade security, governance, and performance.
GoodData serves over 140,000 of the world’s leading companies and 3.2 million users.
Contact:
+1 415-200-0186
press@gooddata.com
Source: GoodData
