diff --git a/website/docs/docs/build/metricflow-commands.md b/website/docs/docs/build/metricflow-commands.md
index a0964269e68..b26b9c14139 100644
--- a/website/docs/docs/build/metricflow-commands.md
+++ b/website/docs/docs/build/metricflow-commands.md
@@ -25,7 +25,7 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash
 
 <TabItem value="cloudcli" label="dbt Cloud CLI">
 
-- MetricFlow commands are embedded in the dbt Cloud CLI. This means you can immediately run them once you install the dbt Cloud CLI and don't need to install MetricFlow separately.
+- MetricFlow [commands](#metricflow-commands) are embedded in the dbt Cloud CLI. This means you can immediately run them once you install the dbt Cloud CLI and don't need to install MetricFlow separately.
 - You don't need to manage versioning &mdash; your dbt Cloud account will automatically manage the versioning for you.
 
 </TabItem>
@@ -36,21 +36,17 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash
 You can create metrics using MetricFlow in the dbt Cloud IDE. However, support for running MetricFlow commands in the IDE will be available soon.
 :::
 
-
-
 </TabItem>
 
 <TabItem value="core" label="dbt Core">
 
+:::tip Use dbt Cloud CLI for semantic layer development
 
-:::info Use dbt Cloud CLI for semantic layer development
-
-Use the dbt Cloud CLI for the experience in defining and querying metrics in your dbt project on dbt Cloud or dbt Core with MetricFlow. 
+You can use the dbt Cloud CLI for the experience in defining and querying metrics in your dbt project.
 
 A benefit to using the dbt Cloud is that you won't need to manage versioning &mdash; your dbt Cloud account will automatically manage the versioning.
 :::
 
-
 You can install [MetricFlow](https://github.com/dbt-labs/metricflow#getting-started) from [PyPI](https://pypi.org/project/dbt-metricflow/). You need to use `pip` to install MetricFlow on Windows or Linux operating systems:
 
 1. Create or activate your virtual environment `python -m venv venv`
@@ -70,16 +66,16 @@ Something to note, MetricFlow `mf` commands return an error if you have a Metafo
 MetricFlow provides the following commands to retrieve metadata and query metrics. 
 
 <Tabs>
-<TabItem value="cloud" label="Commands for dbt Cloud">
+<TabItem value="cloud" label="Commands for dbt Cloud CLI">
 
-Use the `dbt sl` prefix before the command name to execute them in dbt Cloud. For example, to list all metrics, run `dbt sl list metrics`. 
+You can use the `dbt sl` prefix before the command name to execute them in the dbt Cloud CLI. For example, to list all metrics, run `dbt sl list metrics`.
 
 - [`list`](#list) &mdash; Retrieves metadata values.
 - [`list metrics`](#list-metrics) &mdash; Lists metrics with dimensions.
 - [`list dimensions`](#list) &mdash; Lists unique dimensions for metrics.
 - [`list dimension-values`](#list-dimension-values) &mdash; List dimensions with metrics.
 - [`list entities`](#list-entities) &mdash; Lists all unique entities.
-- [`query`](#query) &mdash; Query metrics and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
+- [`query`](#query) &mdash; Query metrics, saved queries, and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
 
 <!--below commands aren't supported in dbt cloud yet
 - [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
@@ -226,10 +222,11 @@ mf tutorial # In dbt Core
 
 ### Query
 
-Create a new query with MetricFlow, execute that query against the user's data platform, and return the result:
+Create a new query with MetricFlow and execute it against your data platform. The query returns the following result:
 
 ```bash
 dbt sl query --metrics <metric_name> --group-by <dimension_name> # In dbt Cloud 
+dbt sl query --saved-query <name> # In dbt Cloud CLI
 
 mf query --metrics <metric_name> --group-by <dimension_name> # In dbt Core
 
@@ -372,7 +369,6 @@ mf query --metrics order_total --group-by metric_time,is_food_order --limit 10 -
 You can further filter the data set by adding a `where` clause to your query.
 
 **Query**
-
 ```bash
 # In dbt Cloud 
 dbt sl query --metrics order_total --group-by metric_time --where "{{ Dimension('order_id__is_food_order') }} = True" 
@@ -406,7 +402,6 @@ To filter by time, there are dedicated start and end time options. Using these o
 
 **Query**
 ```bash
-
 # In dbt Cloud
 dbt sl query --metrics order_total --group-by metric_time,is_food_order --limit 10 --order -metric_time --where "is_food_order = True" --start-time '2017-08-22' --end-time '2017-08-27' 
 
@@ -429,9 +424,25 @@ mf query --metrics order_total --group-by metric_time,is_food_order --limit 10 -
 
 </TabItem>
 
+<TabItem value="eg6" label=" Saved queries">
 
-</Tabs>
+You can use this for frequently used queries. Replace `<name>` with the name of your [saved query](/docs/build/saved-queries). 
+
+**Query**
+```bash
+dbt sl query --saved-query <name> # In dbt Cloud
+
+mf query --saved-query <name> # In dbt Core
+```
+
+For example, if you use dbt Cloud and have a saved query named `new_customer_orders`, you would run `dbt sl query --saved-query new_customer_orders`.
 
+:::info A note on querying saved queries
+When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::
+
+</TabItem>
+</Tabs>
 
 ### Additional query examples
 
diff --git a/website/docs/docs/dbt-cloud-apis/sl-graphql.md b/website/docs/docs/dbt-cloud-apis/sl-graphql.md
index f26a19a1930..e2a473b23e9 100644
--- a/website/docs/docs/dbt-cloud-apis/sl-graphql.md
+++ b/website/docs/docs/dbt-cloud-apis/sl-graphql.md
@@ -217,6 +217,31 @@ Dimension {
 DimensionType = [CATEGORICAL, TIME]
 ```
 
+**List saved queries**
+  
+  ```graphql
+  {
+  savedQueries(environmentId: 200532) {
+    name
+    description
+    label
+    queryParams {
+      metrics {
+        name
+      }
+      groupBy {
+        name
+        grain
+        datePart
+      }
+      where {
+        whereSqlTemplate
+      }
+    }
+  }
+}
+```
+
 ### Querying
 
 When querying for data, _either_ a `groupBy` _or_ a `metrics` selection is required. 
@@ -576,3 +601,38 @@ mutation {
   }
 }
 ```
+
+**Querying compile SQL with saved queries** 
+
+This query includes the field `savedQuery` and generates the SQL based on a predefined [saved query](/docs/build/saved-queries),rather than dynamically building it from a list of metrics and groupings. You can use this for frequently used queries.
+
+```graphql
+mutation {
+  compileSql(
+    environmentId: 200532
+    savedQuery: "new_customer_orders" # new field
+  ) {
+    queryId
+    sql
+  }
+}
+```
+
+:::info A note on querying saved queries
+When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::
+
+**Create query with saved queries** 
+
+This takes the same inputs as the `createQuery` mutation, but includes the field `savedQuery`. You can use this for frequently used queries.
+
+```graphql
+mutation {
+  createQuery(
+    environmentId: 200532
+    savedQuery: "new_customer_orders"  # new field
+  ) {
+    queryId
+  }
+}
+```
diff --git a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
index 2e928db6af2..4727fcdbd21 100644
--- a/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
+++ b/website/docs/docs/dbt-cloud-apis/sl-jdbc.md
@@ -60,13 +60,125 @@ jdbc:arrow-flight-sql://semantic-layer.cloud.getdbt.com:443?&environmentId=20233
 
 ## Querying the API for metric metadata
 
-The Semantic Layer JDBC API has built-in metadata calls which can provide a user with information about their metrics and dimensions. 
+The Semantic Layer JDBC API has built-in metadata calls which can provide a user with information about their metrics and dimensions.
 
-Refer to the following tabs for metadata commands and examples:
+Expand the following toggles for examples and metadata commands:
 
+<detailsToggle alt_header="Fetch defined metrics">
+
+You can use this query to fetch all defined metrics in your dbt project:
+
+```bash
+select * from {{ 
+	semantic_layer.metrics() 
+}}
+```
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch dimension for a metric">
+
+You can use this query to fetch all dimensions for a metric.
+
+Note, metrics is a required argument that lists one or multiple metrics in it.
+
+```bash
+select * from {{ 
+    semantic_layer.dimensions(metrics=['food_order_amount'])}}
+```
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch dimension values">
+
+You can use this query to fetch dimension values for one or multiple metrics and a single dimension.
+
+Note, metrics is a required argument that lists one or multiple metrics, and a single dimension.
+
+```bash
+select * from {{ 
+semantic_layer.dimension_values(metrics=['food_order_amount'], group_by=['customer__customer_name'])}}
+```
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch granularities for metrics">
+
+You can use this query to fetch queryable granularities for a list of metrics. 
+
+This API request allows you to only show the time granularities that make sense for the primary time dimension of the metrics (such as metric_time), but if you want queryable granularities for other time dimensions, you can use the dimensions() call, and find the column queryable_granularities.
+
+Note, metrics is a required argument that lists one or multiple metrics.
+```bash
+select * from {{
+    semantic_layer.queryable_granularities(metrics=['food_order_amount', 'order_gross_profit'])}}
+```
+
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch available metrics given dimensions">
+
+You can use this query to fetch available metrics given dimensions. This command is essentially the opposite of getting dimensions given a list of metrics.
+
+Note, group_by is a required argument that lists one or multiple dimensions.
+
+```bash
+select * from {{
+    semantic_layer.metrics_for_dimensions(group_by=['customer__customer_type'])
+}}
+```
+
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch granularities for all time dimensions">
+
+You can use this example query to fetch available granularities for all time dimensions (the similar queryable granularities API call only returns granularities for the primary time dimensions for metrics).
+
+The following call is a derivative of the dimensions() call and specifically selects the granularity field.
+
+```bash
+select NAME, QUERYABLE_GRANULARITIES from {{
+    semantic_layer.dimensions(
+        metrics=["order_total"]
+    )
+}}
+```
+
+</detailsToggle>
+
+<detailsToggle alt_header="Fetch primary time dimension names">
+
+It may be useful in your application to expose the names of the time dimensions that represent metric_time or the common thread across all metrics.
+
+You can first query the metrics() argument to fetch a list of measures, then use the measures() call which will return the name(s) of the time dimensions that make up metric time.
+
+```bash
+select * from {{
+    semantic_layer.measures(metrics=['orders'])
+}}
+```
+
+</detailsToggle>
+
+<detailsToggle alt_header="List saved queries">
+
+You can use this example query to list all available saved queries in your dbt project.
+
+**Command**
+
+```bash
+select * from semantic_layer.saved_queries()
+```
+
+**Output**
+
+```bash
+| NAME | DESCRIPTION | LABEL | METRICS | GROUP_BY | WHERE_FILTER |
+```
+
+</detailsToggle>
+
+<!--
 <Tabs>
 
-<TabItem value="allmetrics" label="Fetch defined metrics">
+<TabItem value="allmetrics" label="Defined metrics">
 
 Use this query to fetch all defined metrics in your dbt project:
 
@@ -77,7 +189,7 @@ select * from {{
 ```
 </TabItem>
 
-<TabItem value="alldimensions" label="Fetch dimensions for a metric">
+<TabItem value="alldimensions" label="Dimensions for a metric">
 
 Use this query to fetch all dimensions for a metric. 
 
@@ -90,7 +202,7 @@ select * from {{
 
 </TabItem>
 
-<TabItem value="dimensionvalueformetrics" label="Fetch dimension values">
+<TabItem value="dimensionvalueformetrics" label="Dimension values">
 
 Use this query to fetch dimension values for one or multiple metrics and a single dimension. 
 
@@ -103,9 +215,11 @@ semantic_layer.dimension_values(metrics=['food_order_amount'], group_by=['custom
 
 </TabItem>
 
-<TabItem value="queryablegranularitiesformetrics" label="Fetch queryable granularities for metrics">
+<TabItem value="queryablegranularitiesformetrics" label="Granularities for metrics">
+
+You can use this query to fetch queryable granularities for a list of metrics. 
 
-You can use this query to fetch queryable granularities for a list of metrics. This API request allows you to only show the time granularities that make sense for the primary time dimension of the metrics (such as `metric_time`), but if you want queryable granularities for other time dimensions, you can use the `dimensions()` call, and find the column queryable_granularities.
+This API request allows you to only show the time granularities that make sense for the primary time dimension of the metrics (such as `metric_time`), but if you want queryable granularities for other time dimensions, you can use the `dimensions()` call, and find the column queryable_granularities.
 
 Note, `metrics` is a required argument that lists one or multiple metrics.
 
@@ -120,7 +234,7 @@ select * from {{
 
 <Tabs>
 
-<TabItem value="metricsfordimensions" label="Fetch available metrics given dimensions">
+<TabItem value="metricsfordimensions" label="Available metrics given dimensions">
 
 Use this query to fetch available metrics given dimensions. This command is essentially the opposite of getting dimensions given a list of metrics.
 
@@ -135,9 +249,11 @@ select * from {{
 
 </TabItem>
 
-<TabItem value="queryablegranularitiesalltimedimensions" label="Fetch queryable granularities for all time dimensions">
+<TabItem value="queryablegranularitiesalltimedimensions" label="Granularities for all time dimensions">
 
-You can use this example query to fetch available granularities for all time dimensions (the similar queryable granularities API call only returns granularities for the primary time dimensions for metrics). The following call is a derivative of the `dimensions()` call and specifically selects the granularity field.
+You can use this example query to fetch available granularities for all time dimensions (the similar queryable granularities API call only returns granularities for the primary time dimensions for metrics). 
+
+The following call is a derivative of the `dimensions()` call and specifically selects the granularity field.
 
 ```bash
 select NAME, QUERYABLE_GRANULARITIES from {{
@@ -150,7 +266,7 @@ select NAME, QUERYABLE_GRANULARITIES from {{
 
 </TabItem>
 
-<TabItem value="fetchprimarytimedimensionnames" label="Fetch primary time dimension names">
+<TabItem value="fetchprimarytimedimensionnames" label="Primary time dimension names">
 
 It may be useful in your application to expose the names of the time dimensions that represent `metric_time` or the common thread across all metrics.
 
@@ -162,14 +278,15 @@ select * from {{
 }}
 ```
 </TabItem>
-
 </Tabs>
 
+-->
+
 ## Querying the API for metric values
 
 To query metric values, here are the following parameters that are available. Your query must have _either_ a `metric` **or** a `group_by` parameter to be valid. 
 
-| Parameter | Description  | Example    | 
+| Parameter | <div style={{width:'400px'}}>Description</div>  | <div style={{width:'100px'}}>Example</div>  | 
 | --------- | -----------| ------------ |
 | `metrics`   | The metric name as defined in your dbt metric configuration   | `metrics=['revenue']` | 
 | `group_by`  | Dimension names or entities to group by. We require a reference to the entity of the dimension (other than for the primary time dimension), which is pre-appended to the front of the dimension name with a double underscore. | `group_by=['user__country', 'metric_time']`    |
@@ -177,7 +294,8 @@ To query metric values, here are the following parameters that are available. Yo
 | `where`     | A where clause that allows you to filter on dimensions and entities using parameters. This takes a filter list OR string. Inputs come with `Dimension`, and `Entity` objects. Granularity is required if the `Dimension` is a time dimension | `"{{ where=Dimension('customer__country') }} = 'US')"`   | 
 | `limit`   | Limit the data returned    | `limit=10` | 
 |`order`  | Order the data returned by a particular field     | `order_by=['order_gross_profit']`, use `-` for descending, or full object notation if the object is operated on: `order_by=[Metric('order_gross_profit').descending(True)`]   | 
-| `compile`   | If true, returns generated SQL for the data platform but does not execute | `compile=True`  | 
+| `compile`   | If true, returns generated SQL for the data platform but does not execute | `compile=True`  |
+| `saved_query` | A saved query you can use for frequently used queries. | `select * from {{ semantic_layer.query(saved_query="new_customer_orders"` |
 
 ## Note on time dimensions and `metric_time`
 
@@ -403,16 +521,35 @@ semantic_layer.query(metrics=['food_order_amount', 'order_gross_profit'],
 
 ### Query with compile keyword
 
-Use the following example to query using a `compile` keyword:
+- Use the following example to query using a `compile` keyword:
+  ```sql
+  select * from {{
+  semantic_layer.query(metrics=['food_order_amount', 'order_gross_profit'],
+      group_by=[Dimension('metric_time').grain('month'),'customer__customer_type'],
+      compile=True)
+      }}
+  ```
 
-```bash
-select * from {{
-semantic_layer.query(metrics=['food_order_amount', 'order_gross_profit'],
-		group_by=[Dimension('metric_time').grain('month'),'customer__customer_type'],
-		compile=True)
-		}}
+- Use the following example to compile SQL with a [saved query](/docs/build/saved-queries). You can use this for frequently used queries.
+
+  ```sql
+  select * from {{ semantic_layer.query(saved_query="new_customer_orders", limit=5, compile=True}}
+  ```
+
+:::info A note on querying saved queries
+When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::
+
+### Query a saved query
+
+Use the following example to query a [saved query](/docs/build/saved-queries):
+
+```sql
+select * from {{ semantic_layer.query(saved_query="new_customer_orders", limit=5}}
 ```
 
+The JDBC API will use the saved query (`new_customer_orders`) as defined and apply a limit of 5 records.
+
 ## FAQs
 
 <FAQ path="Troubleshooting/sl-alpn-error" />