box_plot
Create box plots from SQL query results on CSV or Parquet data sources to visualize statistical distributions and identify outliers in your data.
Instructions
Run query against specified source and make a box plot using result For both csv and parquet sources, use DuckDB SQL syntax Use 'CSV' as the table name in the SQL query for csv sources. Use 'PARQUET' as the table name in the SQL query for parquet sources.
This will return an image of the plot
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | The data source to run the query on | |
| query | Yes | SQL query to run on the data source | |
| x | Yes | Column name from SQL result to use for x-axis | |
| y | Yes | Column name from SQL result to use for y-axis | |
| color | No | Optional column name from SQL result to show multiple colored bars representing another dimension |
Implementation Reference
- zaturn/tools/visualizations.py:195-229 (handler)Core handler function for the 'box_plot' MCP tool. Executes SQL query on specified data source, generates box plot using plotly.express.px.box with x, y, optional color grouping, converts to PNG base64 ImageContent, or returns error string.def box_plot(self, source_id: Annotated[ str, Field(description='The data source to run the query on') ], query: Annotated[ str, Field(description='SQL query to run on the data source') ], x: Annotated[ str, Field(description='Column name from SQL result to use for x-axis') ], y: Annotated[ str, Field(description='Column name from SQL result to use for y-axis') ], color: Annotated[ str | None, Field(description='Optional column name from SQL result to show multiple colored bars representing another dimension') ] = None, ) -> str | ImageContent: """ Run query against specified source and make a box plot using result For both csv and parquet sources, use DuckDB SQL syntax Use 'CSV' as the table name in the SQL query for csv sources. Use 'PARQUET' as the table name in the SQL query for parquet sources. This will return an image of the plot """ try: df = self._get_df_from_source(source_id, query) fig = px.box(df, x=x, y=y, color=color) fig.update_xaxes(autotickangles=[0, 45, 60, 90]) return _fig_to_image(fig) except Exception as e: return str(e)
- zaturn/tools/visualizations.py:29-40 (registration)Registration of the box_plot tool (along with other visualization tools) in the Visualizations class's self.tools list, used for MCP tool server registration.self.tools = [ self.scatter_plot, self.line_plot, self.histogram, self.strip_plot, self.box_plot, self.bar_plot, self.density_heatmap, self.polar_scatter, self.polar_line, ]
- zaturn/tools/visualizations.py:13-22 (helper)Helper function shared across all plot tools to convert Plotly figure to MCP ImageContent (base64 PNG).def _fig_to_image(fig): fig_encoded = b64encode(fig.to_image(format='png')).decode() img_b64 = "data:image/png;base64," + fig_encoded return ImageContent( type = 'image', data = fig_encoded, mimeType = 'image/png', annotations = None, )
- zaturn/tools/visualizations.py:43-49 (helper)Helper method to fetch and execute SQL query on the specified data source, returning a Pandas DataFrame for plotting.def _get_df_from_source(self, source_id, query): source = self.data_sources.get(source_id) if not source: raise Exception(f"Source {source_id} Not Found") return query_utils.execute_query(source, query)