Datawrapper MCP

Instructions

Implementation Reference

• handlers/update.py:12-59 (handler)

  The 'update_chart' handler function that processes data updates and configuration adjustments for a Datawrapper chart.

  async def update_chart(arguments: UpdateChartArgs) -> list[TextContent]:
      """Update an existing chart's data or configuration."""
      chart_id = arguments["chart_id"]
  
      # Get chart using factory function - returns correct Pydantic class instance
      chart = get_chart(chart_id)
  
      # Update data if provided
      if "data" in arguments:
          df = json_to_dataframe(arguments["data"])
          chart.data = df
  
      # Update config if provided
      if "chart_config" in arguments:
          # Directly set attributes on the chart instance
          # Pydantic will validate each assignment automatically due to validate_assignment=True
          try:
              # Build a mapping of aliases to field names
              alias_to_field = {}
              for field_name, field_info in chart.model_fields.items():
                  # Add the field name itself
                  alias_to_field[field_name] = field_name
                  # Add any aliases
                  if field_info.alias:
                      alias_to_field[field_info.alias] = field_name
  
              for key, value in arguments["chart_config"].items():
                  # Convert alias to field name if needed
                  field_name = alias_to_field.get(key, key)
                  setattr(chart, field_name, value)
  
          except Exception as e:
              raise ValueError(
                  f"Invalid chart configuration: {str(e)}\n\n"
                  f"Use get_chart_schema to see the valid schema for this chart type. "
                  f"Only high-level Pydantic fields are accepted."
              )
  
      # Update using Pydantic instance method
      chart.update()
  
      result = {
          "chart_id": chart.chart_id,
          "message": "Chart updated successfully!",
          "edit_url": chart.get_editor_url(),
      }
  
      return [TextContent(type="text", text=json.dumps(result, indent=2))]

• dw_types.py:20-26 (schema)

  The 'UpdateChartArgs' TypedDict defining the expected input structure for the 'update_chart' handler.

  class UpdateChartArgs(TypedDict):
      """Arguments for update_chart handler."""
  
      chart_id: str
      data: NotRequired[str | list[dict] | dict[str, list]]
      chart_config: NotRequired[dict[str, Any]]

• server.py:289-349 (registration)

  The 'update_chart' tool registration in the MCP server, which interfaces with the 'update_chart_handler'.

  async def update_chart(
      chart_id: str,
      data: str | list | dict | None = None,
      chart_config: dict | None = None,
  ) -> str:
      """⚠️ DATAWRAPPER MCP TOOL ⚠️
      This is part of the Datawrapper MCP server integration.
  
      ---
  
      Update an existing Datawrapper chart's data or configuration using Pydantic models.
  
      ⚠️ IMPORTANT LIMITATION: You CANNOT change the chart type with this tool.
      Chart types are immutable once created. To change from one chart type to another
      (e.g., column → stacked_bar, or line → area), you must create a new chart instead.
  
      WHAT YOU CAN UPDATE:
      • Chart data (add/modify/replace data points)
      • Title, intro, byline, source information
      • Colors, styling, axes configuration
      • Tooltips, annotations, labels
      • Any other configuration options for the existing chart type
  
      WHAT YOU CANNOT UPDATE:
      ✗ Chart type (bar, line, column, etc.) - this is permanent
  
      The chart_config must use high-level Pydantic fields only (title, intro,
      byline, source_name, source_url, etc.). Do NOT use low-level serialized structures
      like 'metadata', 'visualize', or other internal API fields.
  
      STYLING UPDATES:
      Use get_chart_schema to see available fields, then apply styling changes:
      - Colors: {"color_category": {"sales": "#ff0000"}}
      - Line properties: {"lines": [{"column": "sales", "width": "style2"}]}
      - Axis settings: {"custom_range_y": [0, 200], "y_grid_format": "0,0"}
      - Tooltips: {"tooltip_number_format": "0.0"}
  
      See https://datawrapper.readthedocs.io/en/latest/ for detailed examples.
      The provided config will be validated through Pydantic and merged with the existing
      chart configuration.
  
      Args:
          chart_id: ID of the chart to update
          data: New chart data (optional). Same formats as create_chart.
          chart_config: Updated chart configuration using high-level Pydantic fields (optional)
  
      Returns:
          Confirmation message with editor URL
      """
      arguments: dict[str, Any] = {"chart_id": chart_id}
      if data is not None:
          arguments["data"] = data
      if chart_config is not None:
          arguments["chart_config"] = chart_config
  
      try:
          result = await update_chart_handler(cast(UpdateChartArgs, arguments))
          return result[0].text
      except Exception as e:
          return f"Error updating chart with ID '{chart_id}': {str(e)}"