AI Agents in DataGrip
Summary
The most recent DataGrip release is packed with goodies, but the headline feature is the ability to work with AI agents. Today, we dropped a new video showing you how to get the most out of this integration. Whether you prefer Claude Code, Codex, or Junie, DataGrip powers them up with database capabilities, thanks to […]
Original Text
The most recent DataGrip release is packed with goodies, but the headline feature is the ability to work with AI agents.
Today, we dropped a new video showing you how to get the most out of this integration. Whether you prefer Claude Code, Codex, or Junie, DataGrip powers them up with database capabilities, thanks to our built-in MCP tools and skills.
What’s covered in the video:
Connection Setup: Create data sources directly from a text description, a JDBC URL, or by importing connections from another tool.
Talk to Your Schema: Ask agents for insights into your database architecture using natural language.
Text-to-SQL: Query data using natural language requests. AI agents leverage your schema structure to deliver accurate results.
Schema Cleanup: Watch the AI auto-detect out-of-place tables and perform dependency safety checks before running cleanup operations.
Object Mentions: Learn how to target specific database objects using the @dbObject identifier or files using the @fileName identifier.
Watch the full video and let us know your thoughts! What scenarios would you love to see us support next?
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