# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
sources:
looker-source:
kind: looker
base_url: ${LOOKER_BASE_URL}
client_id: ${LOOKER_CLIENT_ID:}
client_secret: ${LOOKER_CLIENT_SECRET:}
verify_ssl: ${LOOKER_VERIFY_SSL:true}
timeout: 600s
use_client_oauth: ${LOOKER_USE_CLIENT_OAUTH:false}
show_hidden_models: ${LOOKER_SHOW_HIDDEN_MODELS:true}
show_hidden_explores: ${LOOKER_SHOW_HIDDEN_EXPLORES:true}
show_hidden_fields: ${LOOKER_SHOW_HIDDEN_FIELDS:true}
tools:
get_models:
kind: looker-get-models
source: looker-source
description: |
This tool retrieves a list of available LookML models in the Looker instance.
LookML models define the data structure and relationships that users can query.
The output includes details like the model's `name` and `label`, which are
essential for subsequent calls to tools like `get_explores` or `query`.
This tool takes no parameters.
get_explores:
kind: looker-get-explores
source: looker-source
description: |
This tool retrieves a list of explores defined within a specific LookML model.
Explores represent a curated view of your data, typically joining several
tables together to allow for focused analysis on a particular subject area.
The output provides details like the explore's `name` and `label`.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
get_dimensions:
kind: looker-get-dimensions
source: looker-source
description: |
This tool retrieves a list of dimensions defined within a specific Looker explore.
Dimensions are non-aggregatable attributes or characteristics of your data
(e.g., product name, order date, customer city) that can be used for grouping,
filtering, or segmenting query results.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
Output Details:
- If a dimension includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that dimension.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
get_measures:
kind: looker-get-measures
source: looker-source
description: |
This tool retrieves a list of measures defined within a specific Looker explore.
Measures are aggregatable metrics (e.g., total sales, average price, count of users)
that are used for calculations and quantitative analysis in your queries.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
Output Details:
- If a measure includes a `suggestions` field, its contents are valid values
that can be used directly as filters for that measure.
- If a `suggest_explore` and `suggest_dimension` are provided, you can query
that specified explore and dimension to retrieve a list of valid filter values.
get_filters:
kind: looker-get-filters
source: looker-source
description: |
This tool retrieves a list of "filter-only fields" defined within a specific
Looker explore. These are special fields defined in LookML specifically to
create user-facing filter controls that do not directly affect the `GROUP BY`
clause of the SQL query. They are often used in conjunction with liquid templating
to create dynamic queries.
Note: Regular dimensions and measures can also be used as filters in a query.
This tool *only* returns fields explicitly defined as `filter:` in LookML.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
get_parameters:
kind: looker-get-parameters
source: looker-source
description: |
This tool retrieves a list of parameters defined within a specific Looker explore.
LookML parameters are dynamic input fields that allow users to influence query
behavior without directly modifying the underlying LookML. They are often used
with `liquid` templating to create flexible dashboards and reports, enabling
users to choose dimensions, measures, or other query components at runtime.
Parameters:
- model_name (required): The name of the LookML model, obtained from `get_models`.
- explore_name (required): The name of the explore within the model, obtained from `get_explores`.
query:
kind: looker-query
source: looker-source
description: |
This tool runs a query against a LookML model and returns the results in JSON format.
Required Parameters:
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
Optional Parameters:
- pivots: A list of fields to pivot the results by. These fields must also be included in the `fields` list.
- filters: A map of filter expressions, e.g., `{"view.field": "value", "view.date": "7 days"}`.
- Do not quote field names.
- Use `not null` instead of `-NULL`.
- If a value contains a comma, enclose it in single quotes (e.g., "'New York, NY'").
- sorts: A list of fields to sort by, optionally including direction (e.g., `["view.field desc"]`).
- limit: Row limit (default 500). Use "-1" for unlimited.
- query_timezone: specific timezone for the query (e.g. `America/Los_Angeles`).
Note: Use `get_dimensions`, `get_measures`, `get_filters`, and `get_parameters` to find valid fields.
query_sql:
kind: looker-query-sql
source: looker-source
description: |
This tool generates the underlying SQL query that Looker would execute
against the database for a given set of parameters. It is useful for
understanding how Looker translates a request into SQL.
Parameters:
All parameters for this tool are identical to those of the `query` tool.
This includes `model_name`, `explore_name`, `fields` (required),
and optional parameters like `pivots`, `filters`, `sorts`, `limit`, and `query_timezone`.
Output:
The result of this tool is the raw SQL text.
query_url:
kind: looker-query-url
source: looker-source
description: |
This tool generates a shareable URL for a Looker query, allowing users to
explore the query further within the Looker UI. It returns the generated URL,
along with the `query_id` and `slug`.
Parameters:
All query parameters (e.g., `model_name`, `explore_name`, `fields`, `pivots`,
`filters`, `sorts`, `limit`, `query_timezone`) are the same as the `query` tool.
Additionally, it accepts an optional `vis_config` parameter:
- vis_config (optional): A JSON object that controls the default visualization
settings for the generated query.
vis_config Details:
The `vis_config` object supports a wide range of properties for various chart types.
Here are some notes on making visualizations.
### Cartesian Charts (Area, Bar, Column, Line, Scatter)
These chart types share a large number of configuration options.
**General**
* `type`: The type of visualization (`looker_area`, `looker_bar`, `looker_column`, `looker_line`, `looker_scatter`).
* `series_types`: Override the chart type for individual series.
* `show_view_names`: Display view names in labels and tooltips (`true`/`false`).
* `series_labels`: Provide custom names for series.
**Styling & Colors**
* `colors`: An array of color values to be used for the chart series.
* `series_colors`: A mapping of series names to specific color values.
* `color_application`: Advanced controls for color palette application (collection, palette, reverse, etc.).
* `font_size`: Font size for labels (e.g., '12px').
**Legend**
* `hide_legend`: Show or hide the chart legend (`true`/`false`).
* `legend_position`: Placement of the legend (`'center'`, `'left'`, `'right'`).
**Axes**
* `swap_axes`: Swap the X and Y axes (`true`/`false`).
* `x_axis_scale`: Scale of the x-axis (`'auto'`, `'ordinal'`, `'linear'`, `'time'`).
* `x_axis_reversed`, `y_axis_reversed`: Reverse the direction of an axis (`true`/`false`).
* `x_axis_gridlines`, `y_axis_gridlines`: Display gridlines for an axis (`true`/`false`).
* `show_x_axis_label`, `show_y_axis_label`: Show or hide the axis title (`true`/`false`).
* `show_x_axis_ticks`, `show_y_axis_ticks`: Show or hide axis tick marks (`true`/`false`).
* `x_axis_label`, `y_axis_label`: Set a custom title for an axis.
* `x_axis_datetime_label`: A format string for datetime labels on the x-axis (e.g., `'%Y-%m'`).
* `x_padding_left`, `x_padding_right`: Adjust padding on the ends of the x-axis.
* `x_axis_label_rotation`, `x_axis_label_rotation_bar`: Set rotation for x-axis labels.
* `x_axis_zoom`, `y_axis_zoom`: Enable zooming on an axis (`true`/`false`).
* `y_axes`: An array of configuration objects for multiple y-axes.
**Data & Series**
* `stacking`: How to stack series (`''` for none, `'normal'`, `'percent'`).
* `ordering`: Order of series in a stack (`'none'`, etc.).
* `limit_displayed_rows`: Enable or disable limiting the number of rows displayed (`true`/`false`).
* `limit_displayed_rows_values`: Configuration for the row limit (e.g., `{ "first_last": "first", "show_hide": "show", "num_rows": 10 }`).
* `discontinuous_nulls`: How to render null values in line charts (`true`/`false`).
* `point_style`: Style for points on line and area charts (`'none'`, `'circle'`, `'circle_outline'`).
* `series_point_styles`: Override point styles for individual series.
* `interpolation`: Line interpolation style (`'linear'`, `'monotone'`, `'step'`, etc.).
* `show_value_labels`: Display values on data points (`true`/`false`).
* `label_value_format`: A format string for value labels.
* `show_totals_labels`: Display total labels on stacked charts (`true`/`false`).
* `totals_color`: Color for total labels.
* `show_silhouette`: Display a "silhouette" of hidden series in stacked charts (`true`/`false`).
* `hidden_series`: An array of series names to hide from the visualization.
**Scatter/Bubble Specific**
* `size_by_field`: The field used to determine the size of bubbles.
* `color_by_field`: The field used to determine the color of bubbles.
* `plot_size_by_field`: Whether to display the size-by field in the legend.
* `cluster_points`: Group nearby points into clusters (`true`/`false`).
* `quadrants_enabled`: Display quadrants on the chart (`true`/`false`).
* `quadrant_properties`: Configuration for quadrant labels and colors.
* `custom_quadrant_value_x`, `custom_quadrant_value_y`: Set quadrant boundaries as a percentage.
* `custom_quadrant_point_x`, `custom_quadrant_point_y`: Set quadrant boundaries to a specific value.
**Miscellaneous**
* `reference_lines`: Configuration for displaying reference lines.
* `trend_lines`: Configuration for displaying trend lines.
* `trellis`: Configuration for creating trellis (small multiple) charts.
* `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering interactions.
### Boxplot
* Inherits most of the Cartesian chart options.
* `type`: Must be `looker_boxplot`.
### Funnel
* `type`: Must be `looker_funnel`.
* `orientation`: How data is read (`'automatic'`, `'dataInRows'`, `'dataInColumns'`).
* `percentType`: How percentages are calculated (`'percentOfMaxValue'`, `'percentOfPriorRow'`).
* `labelPosition`, `valuePosition`, `percentPosition`: Placement of labels (`'left'`, `'right'`, `'inline'`, `'hidden'`).
* `labelColor`, `labelColorEnabled`: Set a custom color for labels.
* `labelOverlap`: Allow labels to overlap (`true`/`false`).
* `barColors`: An array of colors for the funnel steps.
* `color_application`: Advanced color palette controls.
* `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.
### Pie / Donut
* Pie charts must have exactly one dimension and one numerical measure.
* `type`: Must be `looker_pie`.
* `value_labels`: Where to display values (`'legend'`, `'labels'`).
* `label_type`: The format of data labels (`'labPer'`, `'labVal'`, `'lab'`, `'val'`, `'per'`).
* `start_angle`, `end_angle`: The start and end angles of the pie chart.
* `inner_radius`: The inner radius, used to create a donut chart.
* `series_colors`, `series_labels`: Override colors and labels for specific slices.
* `color_application`: Advanced color palette controls.
* `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.
* `advanced_vis_config`: A string containing JSON for advanced Highcharts configuration.
### Waterfall
* Inherits most of the Cartesian chart options.
* `type`: Must be `looker_waterfall`.
* `up_color`: Color for positive (increasing) values.
* `down_color`: Color for negative (decreasing) values.
* `total_color`: Color for the total bar.
### Word Cloud
* `type`: Must be `looker_wordcloud`.
* `rotation`: Enable random word rotation (`true`/`false`).
* `colors`: An array of colors for the words.
* `color_application`: Advanced color palette controls.
* `crossfilterEnabled`, `crossfilters`: Configuration for cross-filtering.
These are some sample vis_config settings.
A bar chart -
{{
"defaults_version": 1,
"label_density": 25,
"legend_position": "center",
"limit_displayed_rows": false,
"ordering": "none",
"plot_size_by_field": false,
"point_style": "none",
"show_null_labels": false,
"show_silhouette": false,
"show_totals_labels": false,
"show_value_labels": false,
"show_view_names": false,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"stacking": "normal",
"totals_color": "#808080",
"trellis": "",
"type": "looker_bar",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"x_axis_zoom": true,
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5,
"y_axis_zoom": true
}}
A column chart with an option advanced_vis_config -
{{
"advanced_vis_config": "{ chart: { type: 'pie', spacingBottom: 50, spacingLeft: 50, spacingRight: 50, spacingTop: 50, }, legend: { enabled: false, }, plotOptions: { pie: { dataLabels: { enabled: true, format: '\u003cb\u003e{key}\u003c/b\u003e\u003cspan style=\"font-weight: normal\"\u003e - {percentage:.2f}%\u003c/span\u003e', }, showInLegend: false, }, }, series: [], }",
"colors": [
"grey"
],
"defaults_version": 1,
"hidden_fields": [],
"label_density": 25,
"legend_position": "center",
"limit_displayed_rows": false,
"note_display": "below",
"note_state": "collapsed",
"note_text": "Unsold inventory only",
"ordering": "none",
"plot_size_by_field": false,
"point_style": "none",
"series_colors": {},
"show_null_labels": false,
"show_silhouette": false,
"show_totals_labels": false,
"show_value_labels": true,
"show_view_names": false,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"stacking": "normal",
"totals_color": "#808080",
"trellis": "",
"type": "looker_column",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"x_axis_zoom": true,
"y_axes": [],
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5,
"y_axis_zoom": true
}}
A line chart -
{{
"defaults_version": 1,
"hidden_pivots": {},
"hidden_series": [],
"interpolation": "linear",
"label_density": 25,
"legend_position": "center",
"limit_displayed_rows": false,
"plot_size_by_field": false,
"point_style": "none",
"series_types": {},
"show_null_points": true,
"show_value_labels": false,
"show_view_names": false,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"stacking": "",
"trellis": "",
"type": "looker_line",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5
}}
An area chart -
{{
"defaults_version": 1,
"interpolation": "linear",
"label_density": 25,
"legend_position": "center",
"limit_displayed_rows": false,
"plot_size_by_field": false,
"point_style": "none",
"series_types": {},
"show_null_points": true,
"show_silhouette": false,
"show_totals_labels": false,
"show_value_labels": false,
"show_view_names": false,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"stacking": "normal",
"totals_color": "#808080",
"trellis": "",
"type": "looker_area",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"x_axis_zoom": true,
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5,
"y_axis_zoom": true
}}
A scatter plot -
{{
"cluster_points": false,
"custom_quadrant_point_x": 5,
"custom_quadrant_point_y": 5,
"custom_value_label_column": "",
"custom_x_column": "",
"custom_y_column": "",
"defaults_version": 1,
"hidden_fields": [],
"hidden_pivots": {},
"hidden_points_if_no": [],
"hidden_series": [],
"interpolation": "linear",
"label_density": 25,
"legend_position": "center",
"limit_displayed_rows": false,
"limit_displayed_rows_values": {
"first_last": "first",
"num_rows": 0,
"show_hide": "hide"
},
"plot_size_by_field": false,
"point_style": "circle",
"quadrant_properties": {
"0": {
"color": "",
"label": "Quadrant 1"
},
"1": {
"color": "",
"label": "Quadrant 2"
},
"2": {
"color": "",
"label": "Quadrant 3"
},
"3": {
"color": "",
"label": "Quadrant 4"
}
},
"quadrants_enabled": false,
"series_labels": {},
"series_types": {},
"show_null_points": false,
"show_value_labels": false,
"show_view_names": true,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"size_by_field": "roi",
"stacking": "normal",
"swap_axes": true,
"trellis": "",
"type": "looker_scatter",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"x_axis_zoom": true,
"y_axes": [
{
"label": "",
"orientation": "bottom",
"series": [
{
"axisId": "Channel_0 - average_of_roi_first",
"id": "Channel_0 - average_of_roi_first",
"name": "Channel_0"
},
{
"axisId": "Channel_1 - average_of_roi_first",
"id": "Channel_1 - average_of_roi_first",
"name": "Channel_1"
},
{
"axisId": "Channel_2 - average_of_roi_first",
"id": "Channel_2 - average_of_roi_first",
"name": "Channel_2"
},
{
"axisId": "Channel_3 - average_of_roi_first",
"id": "Channel_3 - average_of_roi_first",
"name": "Channel_3"
},
{
"axisId": "Channel_4 - average_of_roi_first",
"id": "Channel_4 - average_of_roi_first",
"name": "Channel_4"
}
],
"showLabels": true,
"showValues": true,
"tickDensity": "custom",
"tickDensityCustom": 100,
"type": "linear",
"unpinAxis": false
}
],
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5,
"y_axis_zoom": true
}}
A single record visualization -
{{
"defaults_version": 1,
"show_view_names": false,
"type": "looker_single_record"
}}
A single value visualization -
{{
"comparison_reverse_colors": false,
"comparison_type": "value", "conditional_formatting_include_nulls": false, "conditional_formatting_include_totals": false,
"custom_color": "#1A73E8",
"custom_color_enabled": true,
"defaults_version": 1,
"enable_conditional_formatting": false,
"series_types": {},
"show_comparison": false,
"show_comparison_label": true,
"show_single_value_title": true,
"single_value_title": "Total Clicks",
"type": "single_value"
}}
A Pie chart -
{{
"defaults_version": 1,
"label_density": 25,
"label_type": "labPer",
"legend_position": "center",
"limit_displayed_rows": false,
"ordering": "none",
"plot_size_by_field": false,
"point_style": "none",
"series_types": {},
"show_null_labels": false,
"show_silhouette": false,
"show_totals_labels": false,
"show_value_labels": false,
"show_view_names": false,
"show_x_axis_label": true,
"show_x_axis_ticks": true,
"show_y_axis_labels": true,
"show_y_axis_ticks": true,
"stacking": "",
"totals_color": "#808080",
"trellis": "",
"type": "looker_pie",
"value_labels": "legend",
"x_axis_gridlines": false,
"x_axis_reversed": false,
"x_axis_scale": "auto",
"y_axis_combined": true,
"y_axis_gridlines": true,
"y_axis_reversed": false,
"y_axis_scale_mode": "linear",
"y_axis_tick_density": "default",
"y_axis_tick_density_custom": 5
}}
The result is a JSON object with the id, slug, the url, and
the long_url.
get_looks:
kind: looker-get-looks
source: looker-source
description: |
This tool searches for saved Looks (pre-defined queries and visualizations)
in a Looker instance. It returns a list of JSON objects, each representing a Look.
Search Parameters:
- title (optional): Filter by Look title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the Look is saved.
- user_id (optional): Filter by the ID of the user who created the Look.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific Look ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"dan%"` matches "danger", "Danzig")
- `_`: Matches any single character. (e.g., `"D_m%"` matches "Damage", "dump")
- Special expressions for null checks:
- `"IS NULL"`: Matches Looks where the field is null.
- `"NOT NULL"`: Excludes Looks where the field is null.
run_look:
kind: looker-run-look
source: looker-source
description: |
This tool executes the query associated with a saved Look and
returns the resulting data in a JSON structure.
Parameters:
- look_id (required): The unique identifier of the Look to run,
typically obtained from the `get_looks` tool.
Output:
The query results are returned as a JSON object.
make_look:
kind: looker-make-look
source: looker-source
description: |
This tool creates a new Look (saved query with visualization) in Looker.
The Look will be saved in the user's personal folder, and its name must be unique.
Required Parameters:
- title: A unique title for the new Look.
- description: A brief description of the Look's purpose.
- model_name: The name of the LookML model (from `get_models`).
- explore_name: The name of the explore (from `get_explores`).
- fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.
Optional Parameters:
- pivots, filters, sorts, limit, query_timezone: These parameters are identical
to those described for the `query` tool.
- vis_config: A JSON object defining the visualization settings for the Look.
The structure and options are the same as for the `query_url` tool's `vis_config`.
Output:
A JSON object containing a link (`url`) to the newly created Look, along with its `id` and `slug`.
get_dashboards:
kind: looker-get-dashboards
source: looker-source
description: |
This tool searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.
Search Parameters:
- title (optional): Filter by dashboard title (supports wildcards).
- folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
- user_id (optional): Filter by the ID of the user who created the dashboard.
- description (optional): Filter by description content (supports wildcards).
- id (optional): Filter by specific dashboard ID.
- limit (optional): Maximum number of results to return. Defaults to a system limit.
- offset (optional): Starting point for pagination.
String Search Behavior:
- Case-insensitive matching.
- Supports SQL LIKE pattern match wildcards:
- `%`: Matches any sequence of zero or more characters. (e.g., `"finan%"` matches "financial", "finance")
- `_`: Matches any single character. (e.g., `"s_les"` matches "sales")
- Special expressions for null checks:
- `"IS NULL"`: Matches dashboards where the field is null.
- `"NOT NULL"`: Excludes dashboards where the field is null.
run_dashboard:
kind: looker-run-dashboard
source: looker-source
description: |
This tool executes the queries associated with each tile in a specified dashboard
and returns the aggregated data in a JSON structure.
Parameters:
- dashboard_id (required): The unique identifier of the dashboard to run,
typically obtained from the `get_dashboards` tool.
Output:
The data from all dashboard tiles is returned as a JSON object.
make_dashboard:
kind: looker-make-dashboard
source: looker-source
description: |
This tool creates a new, empty dashboard in Looker. Dashboards are stored
in the user's personal folder, and the dashboard name must be unique.
After creation, use `add_dashboard_filter` to add filters and
`add_dashboard_element` to add content tiles.
Required Parameters:
- title (required): A unique title for the new dashboard.
- description (required): A brief description of the dashboard's purpose.
Output:
A JSON object containing a link (`url`) to the newly created dashboard and
its unique `id`. This `dashboard_id` is crucial for subsequent calls to
`add_dashboard_filter` and `add_dashboard_element`.
add_dashboard_element:
kind: looker-add-dashboard-element
source: looker-source
description: |
This tool creates a new tile (element) within an existing Looker dashboard.
Tiles are added in the order this tool is called for a given `dashboard_id`.
CRITICAL ORDER OF OPERATIONS:
1. Create the dashboard using `make_dashboard`.
2. Add any dashboard-level filters using `add_dashboard_filter`.
3. Then, add elements (tiles) using this tool.
Required Parameters:
- dashboard_id: The ID of the target dashboard, obtained from `make_dashboard`.
- model_name, explore_name, fields: These query parameters are inherited
from the `query` tool and are required to define the data for the tile.
Optional Parameters:
- title: An optional title for the dashboard tile.
- pivots, filters, sorts, limit, query_timezone: These query parameters are
inherited from the `query` tool and can be used to customize the tile's query.
- vis_config: A JSON object defining the visualization settings for this tile.
The structure and options are the same as for the `query_url` tool's `vis_config`.
Connecting to Dashboard Filters:
A dashboard element can be connected to one or more dashboard filters (created with
`add_dashboard_filter`). To do this, specify the `name` of the dashboard filter
and the `field` from the element's query that the filter should apply to.
The format for specifying the field is `view_name.field_name`.
add_dashboard_filter:
kind: looker-add-dashboard-filter
source: looker-source
description: |
This tool adds a filter to a Looker dashboard.
CRITICAL ORDER OF OPERATIONS:
1. Create a dashboard using `make_dashboard`.
2. Add all desired filters using this tool (`add_dashboard_filter`).
3. Finally, add dashboard elements (tiles) using `add_dashboard_element`.
Parameters:
- dashboard_id (required): The ID from `make_dashboard`.
- name (required): A unique internal identifier for the filter. You will use this `name` later in `add_dashboard_element` to bind tiles to this filter.
- title (required): The label displayed to users in the UI.
- flter_type (required): One of `date_filter`, `number_filter`, `string_filter`, or `field_filter`.
- default_value (optional): The initial value for the filter.
Field Filters (`flter_type: field_filter`):
If creating a field filter, you must also provide:
- model
- explore
- dimension
The filter will inherit suggestions and type information from this LookML field.
generate_embed_url:
kind: looker-generate-embed-url
source: looker-source
description: |
This tool generates a signed, private embed URL for specific Looker content,
allowing users to access it directly.
Parameters:
- type (required): The type of content to embed. Common values include:
- `dashboards`
- `looks`
- `explore`
- id (required): The unique identifier for the content.
- For dashboards and looks, use the numeric ID (e.g., "123").
- For explores, use the format "model_name/explore_name".
health_pulse:
kind: looker-health-pulse
source: looker-source
description: |
This tool performs various health checks on a Looker instance.
Parameters:
- action (required): Specifies the type of health check to perform.
Choose one of the following:
- `check_db_connections`: Verifies database connectivity.
- `check_dashboard_performance`: Assesses dashboard loading performance.
- `check_dashboard_errors`: Identifies errors within dashboards.
- `check_explore_performance`: Evaluates explore query performance.
- `check_schedule_failures`: Reports on failed scheduled deliveries.
- `check_legacy_features`: Checks for the usage of legacy features.
Note on `check_legacy_features`:
This action is exclusively available in Looker Core instances. If invoked
on a non-Looker Core instance, it will return a notice rather than an error.
This notice should be considered normal behavior and not an indication of an issue.
health_analyze:
kind: looker-health-analyze
source: looker-source
description: |
This tool calculates the usage statistics for Looker projects, models, and explores.
Parameters:
- action (required): The type of resource to analyze. Can be `"projects"`, `"models"`, or `"explores"`.
- project (optional): The specific project ID to analyze.
- model (optional): The specific model name to analyze. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to analyze. Requires `model` if used.
- timeframe (optional): The lookback period in days for usage data. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
Output:
The result is a JSON object containing usage metrics for the specified resources.
health_vacuum:
kind: looker-health-vacuum
source: looker-source
description: |
This tool identifies and suggests LookML models or explores that can be
safely removed due to inactivity or low usage.
Parameters:
- action (required): The type of resource to analyze for removal candidates. Can be `"models"` or `"explores"`.
- project (optional): The specific project ID to consider.
- model (optional): The specific model name to consider. Requires `project` if used without `explore`.
- explore (optional): The specific explore name to consider. Requires `model` if used.
- timeframe (optional): The lookback period in days to assess usage. Defaults to `90` days.
- min_queries (optional): The minimum number of queries for a resource to be considered active. Defaults to `1`.
Output:
A JSON array of objects, each representing a model or explore that is a candidate for deletion due to low usage.
dev_mode:
kind: looker-dev-mode
source: looker-source
description: |
This tool allows toggling the Looker IDE session between Development Mode and Production Mode.
Development Mode enables making and testing changes to LookML projects.
Parameters:
- enable (required): A boolean value.
- `true`: Switches the current session to Development Mode.
- `false`: Switches the current session to Production Mode.
get_projects:
kind: looker-get-projects
source: looker-source
description: |
This tool retrieves a list of all LookML projects available on the Looker instance.
It is useful for identifying projects before performing actions like retrieving
project files or making modifications.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each containing the `project_id` and `project_name`
for a LookML project.
get_project_files:
kind: looker-get-project-files
source: looker-source
description: |
This tool retrieves a list of all LookML files within a specified project,
providing details about each file.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
Output:
A JSON array of objects, each representing a LookML file and containing
details such as `path`, `id`, `type`, and `git_status`.
get_project_file:
kind: looker-get-project-file
source: looker-source
description: |
This tool retrieves the raw content of a specific LookML file from within a project.
Parameters:
- project_id (required): The unique ID of the LookML project, obtained from `get_projects`.
- file_path (required): The path to the LookML file within the project,
typically obtained from `get_project_files`.
Output:
The raw text content of the specified LookML file.
create_project_file:
kind: looker-create-project-file
source: looker-source
description: |
This tool creates a new LookML file within a specified project, populating
it with the provided content.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The desired path and filename for the new file within the project.
- content (required): The full LookML content to write into the new file.
Output:
A confirmation message upon successful file creation.
update_project_file:
kind: looker-update-project-file
source: looker-source
description: |
This tool modifies the content of an existing LookML file within a specified project.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to modify within the project.
- content (required): The new, complete LookML content to overwrite the existing file.
Output:
A confirmation message upon successful file modification.
delete_project_file:
kind: looker-delete-project-file
source: looker-source
description: |
This tool permanently deletes a specified LookML file from within a project.
Use with caution, as this action cannot be undone through the API.
Prerequisite: The Looker session must be in Development Mode. Use `dev_mode: true` first.
Parameters:
- project_id (required): The unique ID of the LookML project.
- file_path (required): The exact path to the LookML file to delete within the project.
Output:
A confirmation message upon successful file deletion.
get_connections:
kind: looker-get-connections
source: looker-source
description: |
This tool retrieves a list of all database connections configured in the Looker system.
Parameters:
This tool takes no parameters.
Output:
A JSON array of objects, each representing a database connection and including details such as:
- `name`: The connection's unique identifier.
- `dialect`: The database dialect (e.g., "mysql", "postgresql", "bigquery").
- `default_schema`: The default schema for the connection.
- `database`: The associated database name (if applicable).
- `supports_multiple_databases`: A boolean indicating if the connection can access multiple databases.
get_connection_schemas:
kind: looker-get-connection-schemas
source: looker-source
description: |
This tool retrieves a list of database schemas available through a specified
Looker connection.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- database (optional): An optional database name to filter the schemas.
Only applicable for connections that support multiple databases.
Output:
A JSON array of strings, where each string is the name of an available schema.
get_connection_databases:
kind: looker-get-connection-databases
source: looker-source
description: |
This tool retrieves a list of databases available through a specified Looker connection.
This is only applicable for connections that support multiple databases.
Use `get_connections` to check if a connection supports multiple databases.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
Output:
A JSON array of strings, where each string is the name of an available database.
If the connection does not support multiple databases, an empty list or an error will be returned.
get_connection_tables:
kind: looker-get-connection-tables
source: looker-source
description: |
This tool retrieves a list of tables available within a specified database schema
through a Looker connection.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema to list tables from, obtained from `get_connection_schemas`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of strings, where each string is the name of an available table.
get_connection_table_columns:
kind: looker-get-connection-table-columns
source: looker-source
description: |
This tool retrieves a list of columns for one or more specified tables within a
given database schema and connection.
Parameters:
- connection_name (required): The name of the database connection, obtained from `get_connections`.
- schema (required): The name of the schema where the tables reside, obtained from `get_connection_schemas`.
- tables (required): A comma-separated string of table names for which to retrieve columns
(e.g., "users,orders,products"), obtained from `get_connection_tables`.
- database (optional): The name of the database to filter by. Only applicable for connections
that support multiple databases (check with `get_connections`).
Output:
A JSON array of objects, where each object represents a column and contains details
such as `table_name`, `column_name`, `data_type`, and `is_nullable`.
toolsets:
looker_tools:
- get_models
- get_explores
- get_dimensions
- get_measures
- get_filters
- get_parameters
- query
- query_sql
- query_url
- get_looks
- run_look
- make_look
- get_dashboards
- run_dashboard
- make_dashboard
- add_dashboard_element
- add_dashboard_filter
- generate_embed_url
- health_pulse
- health_analyze
- health_vacuum
- dev_mode
- get_projects
- get_project_files
- get_project_file
- create_project_file
- update_project_file
- delete_project_file
- get_connections
- get_connection_schemas
- get_connection_databases
- get_connection_tables
- get_connection_table_columns