You spoke we listened: the Fabi MCP server is here, letting you chat with your data from Claude, Cursor, or any MCP-compatible tool. We're also sharing how customers like Aisle are achieving 92% faster analysis and eliminating hours of manual work each week. Here's what's new.

🚀 Fabi MCP server: Chat with your data from anywhere in minutes

Fabi's Model Context Protocol (MCP) server is now available. It’s the perfect solution to handle ad hoc requests from the team, empower the business to explore data on their own or bring text-to-SQL capabilities to any workflow without a fraction of the effort and maximum accuracy.

What you can do:

• Handle ad hoc requests: Embed Fabi wherever your team works to let AI handle ad hoc data requests from the team

• Stay in your flow: Chat with your data in plain English right from where you work in Claude, Cursor or any other IDE that support MCP tool calling

• Flexible authentication methods: Choose between token or OAuth depending on what you’re building

• Automate workflows: Bring AI data analysis to your workflows with n8n or AgentKit

The magic of Fabi’s MCP server is that you can connect any data source to Fabi and immediately start talking to it. We handle the connection and ensure responses are fast and accurate with our Analyst Agent technology. All you have to worry about is choosing where you want to talk with your data.

Read the full documentation to learn more and reach out to us ([email protected]) if you would like to join the beta testing program.

PS: If you’re building an MCP server, check out this article about lessons learned along our journey to build the Fabi MCP. 

🛠️ Other features and improvements 

• Improvement to the Workflow view with a better experience when you zoom in/out to help you understand what you’re looking at

• Workflow view magic layout: Re-arrange your blocks automatically to clean up your analysis in one click

• RDS and MS SQL Server integrations

• ChatGPT 5.1 model support

• You can now cancel your Smartbook run if it’s taking longer than expected to complete the job

🏬 Aisle case study: 92% faster analysis without a data team

Discover how Aisle, a fast-growing startup helping brands turn marketing channels into measurable retail growth, transformed its entire data operations with Fabi. Before Fabi, their product and engineering teams were drowning in 5-10 ad hoc data requests per week, each taking 30 minutes to 2 hours, for a total of 15 hours weekly spent on work that didn't align with their priorities.

Impact in numbers:

• 92% reduction in analysis time - Dashboards and reports that took hours are now done in 10-15 minutes

• 40-50 monthly data requests eliminated - Non-technical brand team answers their own questions using Fabi

• Weeks to hours - Pilot program evaluations that took 2-3 weeks now finish in hours

• 100% team adoption - All brand managers adopted Fabi for weekly reporting within the first month

Read the full case study to see how Aisle scaled insights without scaling headcount.

💌 The data scientist's evolution: Why AI is redefining, not replacing the role

Our CEO, Marc, recently shared insights on LinkedIn about a fundamental shift in data science that resonated with many readers. AI isn't eliminating data scientists, it's elevating them from code writers to strategic advisors. 

The value of data science is moving away from pure coding skills toward strategic data modeling, business communication, and translating complex insights into business impact. 

Check out Marc's LinkedIn post to understand how this transformation is already reshaping careers and creating more impactful, business-focused roles.

📷 New videos

Analyze Neon data with Fabi: Watch how Fabi integrates with Neon's serverless Postgres in under 5 minutes, connect your database and start AI-powered analysis instantly.

SuperDataScience podcast: Marc joins Jon Krohn to discuss AI-first product design, how AI elevates data scientists into strategic advisors, and building tools that democratize data insights.

📺 Inaugural live product walkthrough session with Marc

Join us on November 19th at 10 am PST for a hands-on tutorial on connecting Fabi to your data and shipping your first dashboard. In this session, we’ll cover:

• Connecting different sources of data, like a CSV file, Google Sheet, database, API, etc.

• Customizing AI Analyst Agent

• Building your first dashboard

Come with questions and be ready for an informative session with Marc and best practices for using Fabi to supercharge your analysis.