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Vizro

by docker ✓ verified ✓ Packaged by Docker

provides tools and templates to create a functioning Vizro chart or dashboard step by step.

MCP server installable network: on runtime: sysbox

Analytics MCP Servers

Vizro MCP Server

provides tools and templates to create a functioning Vizro chart or dashboard step by step.

What is an MCP Server?

MCP Info

Attribute Details
Docker Image mcp/vizro
Author mckinsey
Repository https://github.com/mckinsey/vizro

Image Building Info

Attribute Details
Dockerfile https://github.com/mckinsey/vizro/blob/c88f5e62478de3762402a759cec33e4e1f8d0ee0/vizro-mcp/Dockerfile
Commit c88f5e62478de3762402a759cec33e4e1f8d0ee0
Docker Image built by Docker Inc.
Docker Scout Health Score 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. Server Vizro version: 0.1.46

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

Returns:
    Data info object containing information about the dataset.
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.

Returns:
    Instructions for creating a Vizro chart or dashboard
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 boolean optional Only call if you need to use custom CSS, custom components or custom actions.
No need to call this with advanced_mode=True if you need advanced charts,
use custom_charts in the validate_dashboard_config tool instead.
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)

Returns:
    DataAnalysisResults object containing DataFrame information and metadata
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.

Returns:
    ValidationResults object with status and dashboard details
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 boolean optional 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.

Returns:
    ValidationResults object with status and dashboard details
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 boolean optional Whether to automatically open the PyCafe link in a browser

Use this MCP Server

{
  "mcpServers": {
    "vizro": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "mcp/vizro"
      ]
    }
  }
}

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