Vizro
provides tools and templates to create a functioning Vizro chart or dashboard step by step.
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6 Tools
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About
Vizro MCP Server
provides tools and templates to create a functioning Vizro chart or dashboard step by step.
Characteristics
| Attribute | Details |
|---|---|
| Docker Image | mcp/vizro |
| Author | mckinsey |
| Repository | https://github.com/mckinsey/vizro |
| Dockerfile | https://github.com/mckinsey/vizro/blob/main/vizro-mcp/Dockerfile |
| Docker Image built by | Docker Inc. |
| Docker Scout Health Score | |
| Verify Signature | COSIGN_REPOSITORY=mcp/signatures cosign verify mcp/vizro --key https://raw.githubusercontent.com/docker/keyring/refs/heads/main/public/mcp/latest.pub |
| Licence | Apache License 2.0 |
Available Tools (6)
| Tools provided by this Server | Short Description |
|---|---|
get_model_json_schema | Get the JSON schema for the specified Vizro model. |
get_sample_data_info | If user provides no data, use this tool to get sample data information. |
get_vizro_chart_or_dashboard_plan | Get instructions for creating a Vizro chart or dashboard. |
load_and_analyze_data | Use to understand local or remote data files. |
validate_chart_code | Validate the chart code created by the user and optionally open the PyCafe link in a browser. |
validate_dashboard_config | Validate Vizro model configuration. |
Tools Details
Tool: get_model_json_schema
Get the JSON schema for the specified Vizro model.
| Parameters | Type | Description |
|---|---|---|
model_name | string | Name of the Vizro model to get schema for (e.g., 'Card', 'Dashboard', 'Page') |
Tool: 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
| Parameters | Type | Description |
|---|---|---|
data_name | string | Name of the dataset to get sample data for |
Tool: get_vizro_chart_or_dashboard_plan
Get instructions for creating a Vizro chart or dashboard. Call FIRST when asked to create Vizro things.
Must be ALWAYS called FIRST with advanced_mode=False, then call again with advanced_mode=True
if the JSON config does not suffice anymore.
| Parameters | Type | Description |
|---|---|---|
user_host | string | The host the user is using, if "ide" you can use the IDE/editor to run python code |
user_plan | string | The type of Vizro thing the user wants to create |
advanced_mode | booleanoptional | Only call if you need to use custom CSS, custom components or custom actions. |
Tool: load_and_analyze_data
Use to understand local or remote data files. Must be called with absolute paths or URLs.
Supported formats:
- CSV (.csv)
- JSON (.json)
- HTML (.html, .htm)
- Excel (.xls, .xlsx)
- OpenDocument Spreadsheet (.ods)
- Parquet (.parquet)
| Parameters | Type | Description |
|---|---|---|
path_or_url | string | Absolute (important!) local file path or URL to a data file |
Tool: validate_chart_code
Validate the chart code created by the user and optionally open the PyCafe link in a browser.
| Parameters | Type | Description |
|---|---|---|
chart_config | string | A ChartPlan object with the chart configuration |
data_info | string | Metadata for the dataset to be used in the chart |
auto_open | booleanoptional | Whether to automatically open the PyCafe link in a browser |
Tool: validate_dashboard_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.
| Parameters | Type | Description |
|---|---|---|
custom_charts | array | List of ChartPlan objects containing information about the custom charts in the dashboard |
dashboard_config | object | Either a JSON string or a dictionary representing a Vizro dashboard model configuration |
data_infos | array | List of DFMetaData objects containing information about the data files |
auto_open | booleanoptional | Whether to automatically open the PyCafe link in a browser |
Use this MCP Server
{
"mcpServers": {
"vizro": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"mcp/vizro"
]
}
}
}
Manual installation
You can install the MCP server using:
Installation for