GoodData has launched its MCP Server — a system that lets AI agents build, run and manage analytics autonomously under full governance, aiming to deliver up to 50x faster time to value.
San Francisco-based analytics company GoodData has announced the public release of its Model Context Protocol (MCP) Server, designed to enable AI and data teams to automate the full analytics lifecycle.
Unlike most AI tools that stop at query generation, the MCP Server moves into full execution, allowing AI agents to create, update, and operate analytics infrastructure directly — including dashboards, metrics, semantic models, and alerts — all within a governed framework.
“The analytics challenge has never been about asking questions, it’s been about execution,” said Roman Stanek, Founder and CEO of GoodData. “With MCP Server, we’re turning analytics into an executable system that AI can safely operate under governance. This fundamentally changes how fast organisations can build, adapt and scale AI analytics.”
The system leverages the Model Context Protocol, a standard that allows large language models and AI agents to interface with analytics assets through governed APIs. That means AI can manage analytics processes without relying on manual SQL workflows or visual interfaces.
GoodData says the combination of MCP, analytics-as-code and LLM integration allows analytics to be treated like programmable software resources. Teams can automate asset creation, run continuous analysis, and synchronise business logic safely across systems.
“Any AI agent can work with analytics assets such as semantic models and dashboards using the same APIs, permissions and governance controls as engineering teams,” said Peter Fedorocko, Field CTO at GoodData. “This approach delivers 10–50x faster time to value.”
The company positions MCP Server as a step beyond AI-assisted analytics — towards AI-executed analytics. All activity operates within the same permissions and compliance rules that govern human users, reducing operational risk while accelerating delivery.
GoodData believes this shift is made possible by three converging advances: the emergence of MCP as an execution layer for AI, analytics-as-code frameworks that make analytics programmable, and increasingly capable LLMs that can operate within defined governance. Together, these enable analytics to evolve from manual processes into scalable, automated systems.
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