diff --git a/docs/en/integrations/data-ingestion/etl-tools/dbt/index.md b/docs/en/integrations/data-ingestion/etl-tools/dbt/index.md
index b576972fb37..3663494869d 100644
--- a/docs/en/integrations/data-ingestion/etl-tools/dbt/index.md
+++ b/docs/en/integrations/data-ingestion/etl-tools/dbt/index.md
@@ -4,6 +4,7 @@ slug: /en/integrations/dbt
 sidebar_position: 1
 description: Users can transform and model their data in ClickHouse using dbt
 ---
+import TOCInline from '@theme/TOCInline';
 
 # Integrating dbt and ClickHouse
 
@@ -13,6 +14,8 @@ Within dbt, these models can be cross-referenced and layered to allow the constr
 
 Dbt is compatible with ClickHouse through a [ClickHouse-supported plugin](https://github.com/ClickHouse/dbt-clickhouse). We describe the process for connecting ClickHouse with a simple example based on a publicly available IMDB dataset. We additionally highlight some of the limitations of the current connector.
 
+<TOCInline toc={toc}  maxHeadingLevel={2} />
+
 ## Concepts
 
 dbt introduces the concept of a model. This is defined as a SQL statement, potentially joining many tables. A model can be “materialized” in a number of ways. A materialization represents a build strategy for the model’s select query. The code behind a materialization is boilerplate SQL that wraps your SELECT query in a statement in order to create a new or update an existing relation.