What’s new with Flatfile

Use Flatfile's newly released MCP server with tools like Claude Code, Claude Desktop, and Cursor to interact directly with your Flatfile data. Ask questions, add sheets, create sample data, and more—all with whatever tool you’re most comfortable with.

Learn more about the server and how to get started in this guide.

We've improved our filtering experience within sheets to allow users more control over the data you see. You can now apply both basic and complex filters to view errors, missing values, specific records or values, and more.

We now retrieve 5MB of log records for each agent run (previously 4KB) and display an error icon in the Agents dashboard next to any runs with issues.

Edit field settings like name, type, description, and required or unique status from our new field context menu. From within Blueprint in Build Mode, click the three dots next to any field to access these options.

We’ve just rolled out personal access tokens for Flatfile API access. Unlike shared environment keys, these tokens will follow users across environments, are tied to that user’s permissions, and can be revoked at any time.

You can find the technical documentation here.

You can now hover in between row numbers and click "Insert row" to add a record anywhere in a table.

In response to customer feedback, we've released an “add a row” button. You’ll see it frozen at the bottom of any sheet you’re working on, allowing you to quickly click and add a new record without scrolling to the bottom of the dataset.

Our new Calculations feature provides deeper insight into your progress toward a complete dataset, displaying count empty, count filled, percent empty, and percent filled metrics by column. This feature requires activation—please contact your Customer Success Manager to enable it.

Read more on our Knowledge Base

Now you can copy multiple values or rows and paste them into a range to have them automatically repeat throughout. This speeds up the data preparation process while minimizing errors, allowing you to move efficiently through a large volume of data.

Read more on our Knowledge Base