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‍After 10 days since launching the Keboola MCP (Model Context Protocol) Server, we've gathered the most common questions from our data community. This article combines practical answers with best practices inspired by successful AI-assisted development patterns, helping you get the most out of your AI-powered data workflows.

Keboola Data Templates are AI‑enhanced, reusable pipelines you launch with one click or API call. They eliminate the need to rebuild data workflows from scratch—so every use case is a fast-track to insights and impact. No more reinventing the wheel: once a template exists, it can be shared and adapted across departments—marketing, finance, ops—saving weeks of build time and hundreds of engineer-hours.

The biggest issue with chatbot implementations powered by generative AI is the accuracy and reliability of the output. Models can give erroneous or inaccurate answers due to hallucinations or simply because they lack information specific to a given business case, as many of them don’t have access to new data outside of pretraining. Retrieval-Augmented Generation (RAG) is a technique designed to address this limitation by integrating an external retrieval mechanism with a generative model.

The global financial services industry is a complex landscape: a patchwork quilt of regulatory frameworks, technologies, and markets with very different customer needs. To be the most profitable, the most competitive, and the most efficient it can be, a financial services provider must find a way to navigate that complexity, and sales and finance teams hold pieces of the puzzle. And putting the pieces together isn’t as easy as it may look at first glance.

The e-commerce landscape is passionately competitive. Today is a prime example as consumers rush to secure the perfect Valentine’s Day gift before it's slim pickings on the chocolates and the sad looking roses! How do you meet the demand and keep those last minute bouquet hunters happy?

We at Keboola believe that there can’t be too much efficiency in data engineering. Any data professional would surely agree, there is no such thing as good enough. And while better tools sometimes offer incremental steps, pushing the needle a little step at a time, a combination of tools can lead to impressive synergies. Keboola CLI and Cursor AI are exactly that—a combination that’s more than a sum of its parts.

Environmental, Social, and Governance (ESG) reporting is no longer a forward-thinking corporate initiative—it’s an immediate business imperative. With regulatory deadlines fast approaching, stakeholders demanding transparency, and the financial risks of inaction rising, companies must move beyond reactive reporting to proactive ESG data management.

Organizations currently face a fragmented ecosystem of data sources, collection methods, and reporting requirements. Many rely on manual processes and disconnected systems, leading to inefficiencies and increased risk of errors—approximately 70% of organizations struggle with data consistency and validation. The financial sector has emerged as a primary driver of ESG data management evolution, with investment decisions increasingly tied to sustainability performance.

Managing ESG data is complex but essential. Gartner’s Market Guide for ESG Reporting and Management Software states, "Without integrated ESG reporting, companies risk compliance breaches and reputational harm." This guide provides a roadmap to tackle ESG challenges and build a robust reporting strategy.

The European Union is transforming the landscape of ESG reporting with the Corporate Sustainability Reporting Directive (CSRD). This groundbreaking legislation, approved in November 2022, sets new standards for transparency and accountability in sustainability reporting.