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Lightdash works with the tools your team already uses. Connect a dbt project to build your semantic layer from it, send chart results to Slack and Google Sheets, deliver alerts and scheduled reports, query your semantic layer from any SQL client, and operate Lightdash agentically from Snowflake Cortex. One closely related integration is documented in its own product area: the Lightdash MCP server, which lets AI assistants explore your data and run queries directly.

Slack integration

Unfurl chart links, deliver scheduled reports and alerts, and chat with your AI agents in Slack

Google Sheets

Sync chart results to a Google Sheet on a schedule, or query Lightdash from the sidebar add-on

Metrics SQL API

Query your Lightdash semantic layer over the Postgres wire protocol from any SQL client or BI tool

Snowflake Cortex

Operate your BI layer agentically by pairing Lightdash with Snowflake's Cortex Code agent

dbt

dbt Projects

Every way to sync your dbt project into Lightdash, and how to connect multiple dbt sources

dbt write-back

Develop models and metrics in Lightdash and open a pull request against your dbt project

dbt MetricFlow metrics

Connect Lightdash to your dbt MetricFlow semantic layer metrics

Upgrading dbt

What changes in your Lightdash setup when you move between dbt versions