News
Key Takeawasys:
- End-to-end automation. GoodData's MCP Server enables AI to execute analytics processes fully.
- AI-driven governance. Analytics assets are managed by AI under enterprise governance controls.
- Impact for data teams. BI and AI developers gain faster analytics development and reduced manual workload.
GoodData believes that AI-powered analytics execution — not just insight — will define the next wave of enterprise BI.
The San Francisco-based vendor launched its MCP Server, a tool that enables AI agents and large language models (LLMs) to execute analytics workflows from start to finish, on Jan. 21. The server delivers 10x-50x faster time to value by allowing AI to build, update and run analytics processes automatically, according to the company.
Using the Model Context Protocol (MCP), AI agents can connect directly to GoodData and work with governed analytics assets, including semantic models, metrics, dashboards and alerts, under the same security and permissions as human users.
"Analytics has never been limited by questions, it's been limited by execution," said Roman Stanek, CEO and founder of GoodData. "With MCP Server, we're turning analytics into an executable system that AI can safely operate under governance."
GoodData MCP Server Capabilities
The server combines analytics-as-code, governed APIs and LLM-based coding to shift AI agents from interacting with analytics to executing within it, according to GoodData.
| Capability | Description |
|---|---|
| MCP Server | Enables AI agents to execute end-to-end analytics workflows |
| Model Context Protocol integration | Connects LLMs directly to governed analytics assets |
| Analytics-as-code | Allows AI to build and update analytics programmatically |
| Governed execution | Enforces enterprise security, permissions and business rules |
| LLM support | Enables large language models to operate within defined constraints |
Recent GoodData Developments
GoodData spent the past year repositioning itself from a cloud analytics provider to an AI-native decision-intelligence vendor. The company reported record Q1 growth in late April 2025, posting 41% annualized revenue growth and a Rule-of-40 score above 50.
Throughout 2025, GoodData maintained momentum with strategic launches and acquisitions. In June, the company launched AI Smart Search and earned Niche Player recognition in Gartner's 2025 Magic Quadrant for Analytics and BI Platforms. It then introduced self-hosted AI deployments in July. In September, the vendor acquired Understand Labs and unveiled a full-stack data intelligence platform. December brought the Intelligence Layer, a governed AI suite embedding semantic definitions directly into models.
GoodData opened 2026 by reporting a 50% year-on-year increase in Q4 product releases and a 296% surge in AI-focused development activity during the second half of 2025.
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.
— Peter Fedorocko, Field CTO at GoodData
Market Context
Enterprise AI adoption is no longer defined by ambition alone but by execution. Organizations are embedding AI into core workflows through standardized platforms and production-grade architectures.
AI budgets are increasing, often by more than 10%, as pilots transition into production. However, recent MIT research found that despite spending close to $40 billion on generative AI over the last two years, only 5% of enterprises could point to real business returns.
Analytical AI adoption shows clear momentum in sales, marketing and customer-facing functions. Yet strategic deployment remains below 10% in operations, finance and executive management.
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GoodData at a Glance
GoodData, founded in 2007 by Roman Stanek, is an AI-native decision intelligence platform built to help enterprises turn trusted data into confident action. Designed for governed, scalable analytics, GoodData enables organizations to operationalize insights, automate decisions and embed intelligence directly into products and business workflows.
