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About Baserow MCP

Baserow's MCP server turns a no-code database workspace into both a data source and a write target for an AI client. The exposed tools cover what an agent needs to be useful against a table: list the databases in a workspace, list the tables inside them, fetch a table's schema so the model knows the field names and types it is working with, list rows, and then create, update or delete rows. Schema access is what makes the write path reliable. Because the agent reads field definitions before it writes, it maps a loose natural language instruction onto the correct columns instead of inventing them, which is the usual failure mode when an assistant is pointed at a spreadsheet. Typical uses are logging structured records out of a conversation, bulk updating a status column, pulling a filtered slice of a table into a summary, or cleaning up entries that were captured inconsistently by different people. Setup is per workspace: an admin generates an endpoint URL that carries its own access, so the URL should be treated like a password and revoked when a client no longer needs it. Each endpoint has independent access controls, which is the practical way to keep an agent scoped to one workspace rather than an entire account. It suits teams already running operations on Baserow who would rather have an assistant maintain the data than do manual entry.