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vizro-mcp

Official

Apache 2.0

2,921

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Server Configuration

Describes the environment variables required to run the server.

Name	Required	Description	Default
No arguments

Schema

Prompts

Interactive templates invoked by user choice

Name	Description
`create_starter_dashboard`	Prompt template for getting started with Vizro.
`create_eda_dashboard`	Prompt template for creating an EDA dashboard based on one dataset.
`create_vizro_chart`	Prompt template for creating a Vizro chart.

Resources

Contextual data attached and managed by the client

Name	Description
No resources

Tools

Functions exposed to the LLM to take actions

Name	Description
get_sample_data_info	If user provides no data, use this tool to get sample data information. Use the following data for the below purposes: - iris: mostly numerical with one categorical column, good for scatter, histogram, boxplot, etc. - tips: contains mix of numerical and categorical columns, good for bar, pie, etc. - stocks: stock prices, good for line, scatter, generally things that change over time - gapminder: demographic data, good for line, scatter, generally things with maps or many categories Args: data_name: Name of the dataset to get sample data for Returns: Data info object containing information about the dataset.
validate_model_config	Validate Vizro model configuration. Run ALWAYS when you have a complete dashboard configuration. If successful, the tool will return the python code and, if it is a remote file, the py.cafe link to the chart. The PyCafe link will be automatically opened in your default browser if auto_open is True. Args: config: Either a JSON string or a dictionary representing a Vizro model configuration data_infos: List of DFMetaData objects containing information about the data files auto_open: Whether to automatically open the PyCafe link in a browser Returns: ValidationResults object with status and dashboard details
get_model_json_schema	Get the JSON schema for the specified Vizro model. Args: model_name: Name of the Vizro model to get schema for (e.g., 'Card', 'Dashboard', 'Page') Returns: JSON schema of the requested Vizro model
get_vizro_chart_or_dashboard_plan	Get instructions for creating a Vizro chart or dashboard. Call FIRST when asked to create Vizro things.
load_and_analyze_data	Load data from various file formats into a pandas DataFrame and analyze its structure. Supported formats: - CSV (.csv) - JSON (.json) - HTML (.html, .htm) - Excel (.xls, .xlsx) - OpenDocument Spreadsheet (.ods) - Parquet (.parquet) Args: path_or_url: Local file path or URL to a data file Returns: DataAnalysisResults object containing DataFrame information and metadata
validate_chart_code	Validate the chart code created by the user and optionally open the PyCafe link in a browser. Args: config: A ChartPlan object with the chart configuration data_info: Metadata for the dataset to be used in the chart auto_open: Whether to automatically open the PyCafe link in a browser Returns: ValidationResults object with status and dashboard details

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