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VisActor

vchart-mcp-server

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by VisActor

generate_scatter_chart

Create scatter charts to visualize data distributions, correlations, and trends between variables for analysis and insight discovery.

Instructions

Generate a scatter chart to visually display the distribution, clustering trends, and correlations of data points in two-dimensional or multi-dimensional space. Suitable for analyzing relationships between variables, outlier detection, and similar scenarios.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNoChart output type. Defaults to 'image'.image
widthNoChart width. Optional, defaults to 500.
heightNoChart height. Optional, defaults to 500.
dataTableYesScatter chart data, e.g., [{ x: 34, y: 10, category: 'A' }].
xFieldYesMeasure field. Must be numeric and exist in the data.
yFieldYes
sizeFieldNoNumeric field for bubble size.
colorFieldNoColor grouping field. Should not duplicate the dimension field.
chartThemeNoChart theme. Optional, defaults to 'light'.
titleNoChart title text.
subTitleNoChart subtitle text.
titleOrientNoTitle position in the chart.
xAxisTypeNoX-axis type: categorical ('band') or continuous ('linear').
xAxisOrientNoX-axis position in the chart.
xAxisTitleNoX-axis title.
xAxisHasGridNoShow vertical grid lines for the X-axis.
xAxisHasLabelNoShow X-axis labels.
xAxisHasTickNoShow X-axis ticks.
yAxisTypeNoY-axis type: categorical ('band') or continuous ('linear').
yAxisOrientNoY-axis position in the chart.
yAxisTitleNoY-axis title.
yAxisHasGridNoShow horizontal grid lines for the Y-axis.
yAxisHasLabelNoShow Y-axis labels.
yAxisHasTickNoShow Y-axis ticks.
backgroundNoChart background color (hex). Optional, defaults to white.
colorsNoColor palette for chart elements.

Implementation Reference

  • Generic MCP CallTool handler that dispatches to generateChartByType based on tool name matching 'generate_scatter_chart' to chartType 'scatter'. Validates input with scatter schema and returns image/html/spec.
    server.setRequestHandler(CallToolRequestSchema, async request => {
      const toolName = request.params.name;
      const chartType = Object.keys(Charts).find(
        key => (Charts as any)[key].tool.name === toolName
      );
    
      if (!chartType) {
        throw new McpError(
          ErrorCode.MethodNotFound,
          `Unknown tool: ${request.params.name}.`
        );
      }
    
      try {
        // Validate input using Zod before generating chart
        const args = request.params.arguments || {};
    
        // Select the appropriate schema based on the chart type
        const schema = Charts[chartType as keyof typeof Charts].schema;
    
        if (schema) {
          const result = schema.safeParse(args);
          if (!result.success) {
            throw new McpError(
              ErrorCode.InvalidParams,
              `Invalid parameters: ${result.error.message}`
            );
          }
        }
    
        const res = await generateChartByType(chartType, args);
    
        if (res && (res as any).spec) {
          return {
            content: [
              {
                type: 'text',
                text: JSON.stringify((res as any).spec, null, 2),
              },
            ],
          };
        }
    
        if (res && (res as any).image) {
          return {
            content: [
              {
                type: 'text',
                text: (res as any).image,
              },
            ],
          };
        }
    
        if (res && (res as any).html) {
          return {
            content: [
              {
                type: 'text',
                text: (res as any).html,
              },
            ],
          };
        }
    
        return {
          content: [
            {
              type: 'text',
              text: 'Failed to generate chart',
            },
          ],
        };
      } catch (error: any) {
        if (error instanceof McpError) {
          throw error;
        }
        throw new McpError(
          ErrorCode.InternalError,
          `Failed to generate chart: ${error?.message || 'Unknown error.'}`
        );
      }
    });
  • Zod schema defining the input parameters and validation for the generate_scatter_chart tool, including dataTable, xField, yField, etc.
    const schema = z.object({
      output: ChartOutputSchema,
      width: WidthSchema,
      height: HeightSchema,
      dataTable: z
        .array(z.any())
        .describe("Scatter chart data, e.g., [{ x: 34, y: 10, category: 'A' }].")
        .nonempty({ message: 'Scatter chart data cannot be empty.' }),
    
      xField: YFieldSchema,
      yField: YFieldSchema,
      sizeField: z.string().optional().describe('Numeric field for bubble size.'),
      colorField: ColorFieldSchema,
    
      chartTheme: ThemeSchema,
      title: TitleTextSchema,
      subTitle: TitleSubTextSchema,
      titleOrient: TitleOrientSchema,
      xAxisType: XAxisTypeSchema,
      xAxisOrient: XAxisOrientSchema,
      xAxisTitle: XAxisTitleSchema,
      xAxisHasGrid: XAxisHasGridSchema,
      xAxisHasLabel: XAxisHasLabelSchema,
      xAxisHasTick: XAxisHasTickSchema,
    
      yAxisType: YAxisTypeSchema,
      yAxisOrient: YAxisOrientSchema,
      yAxisTitle: YAxisTitleSchema,
      yAxisHasGrid: YAxisHasGridSchema,
      yAxisHasLabel: YAxisHasLabelSchema,
      yAxisHasTick: YAxisHasTickSchema,
    
      background: BackgroundSchema,
      colors: ColorsSchema,
    });
  • src/server.ts:34-38 (registration)
    Registers the generate_scatter_chart tool by including it in the list of tools returned for ListToolsRequest, sourced from Charts.scatter.tool.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: Object.values(Charts).map(chart => (chart as any).tool),
      };
    });
  • Defines the tool metadata (name, description, schema) exported as scatter.tool, which is imported and listed in the MCP server.
    const tool = {
      name: 'generate_scatter_chart',
      description:
        'Generate a scatter chart to visually display the distribution, clustering trends, and correlations of data points in two-dimensional or multi-dimensional space. Suitable for analyzing relationships between variables, outlier detection, and similar scenarios.',
      inputSchema: convertZodToJsonSchema(schema),
    };
    
    export const scatter = {
      schema,
      tool,
    };
  • Helper function that implements the chart generation logic for 'scatter' type: normalizes options, extracts fields (xField, yField, sizeField, colorField), generates VChart spec, and produces image/html/spec output.
    export async function generateChartByType(chartType: string, options: any) {
      const {
        title,
        subTitle,
        titleOrient,
        xAxisType,
        xAxisOrient,
        xAxisTitle,
        xAxisHasGrid,
        xAxisHasLabel,
        xAxisHasTick,
    
        yAxisType,
        yAxisOrient,
        yAxisTitle,
        yAxisHasGrid,
        yAxisHasLabel,
        yAxisHasTick,
    
        leftYAxisTitle,
        leftYAxisHasGrid,
        leftYAxisHasLabel,
        leftYAxisHasTick,
    
        rightYAxisTitle,
        rightYAxisHasGrid,
        rightYAxisHasLabel,
        rightYAxisHasTick,
    
        angleAxisTitle,
        angleAxisHasGrid,
        angleAxisHasLabel,
        angleAxisHasTick,
        angleAxisType,
    
        radiusAxisHasGrid,
        radiusAxisHasLabel,
        radiusAxisHasTick,
        radiusAxisType,
        radiusAxisTitle,
    
        output,
        width,
        height,
        ...res
      } = options;
    
      const opts = { ...res };
      const titleObj = filterValidAttributes({
        text: title,
        subText: subTitle,
        orient: titleOrient,
      });
      const xAxisObj = filterValidAttributes({
        type: xAxisType,
        orient: xAxisOrient,
        title: xAxisTitle,
        hasGrid: xAxisHasGrid,
        hasLabel: xAxisHasLabel,
        hasTick: xAxisHasTick,
      });
      const yAxisObj = filterValidAttributes({
        type: yAxisType,
        orient: yAxisOrient,
        title: yAxisTitle,
        hasGrid: yAxisHasGrid,
        hasLabel: yAxisHasLabel,
        hasTick: yAxisHasTick,
      });
      const leftYAxisObj = filterValidAttributes({
        title: leftYAxisTitle,
        hasGrid: leftYAxisHasGrid,
        hasLabel: leftYAxisHasLabel,
        hasTick: leftYAxisHasTick,
      });
      const rightYAxisObj = filterValidAttributes({
        title: rightYAxisTitle,
        hasGrid: rightYAxisHasGrid,
        hasLabel: rightYAxisHasLabel,
        hasTick: rightYAxisHasTick,
      });
      const angleAxisObj = filterValidAttributes({
        title: angleAxisTitle,
        hasGrid: angleAxisHasGrid,
        hasLabel: angleAxisHasLabel,
        hasTick: angleAxisHasTick,
        type: angleAxisType,
      });
      const radiusAxisObj = filterValidAttributes({
        hasGrid: radiusAxisHasGrid,
        hasLabel: radiusAxisHasLabel,
        hasTick: radiusAxisHasTick,
        type: radiusAxisType,
        title: radiusAxisTitle,
      });
    
      const cell: Record<string, string> = {};
    
      [
        "xField",
        "yField",
        "colorField",
        "categoryField",
        "valueField",
        "wordField",
        "sizeField",
        "timeField",
        "sourceField",
        "targetField",
        "setsField",
        "radiusField",
      ].forEach((fieldName) => {
        if (isValid(options[fieldName])) {
          cell[fieldName.replace("Field", "")] = options[fieldName];
          delete opts[fieldName];
        }
      });
    
      opts.cell = cell;
    
      if (!isEmpty(titleObj)) {
        opts.title = titleObj;
      }
    
      const axes = [
        xAxisObj,
        yAxisObj,
        leftYAxisObj,
        rightYAxisObj,
        angleAxisObj,
        radiusAxisObj,
      ];
    
      if (axes.some((axis) => !isEmpty(axis))) {
        opts.axes = axes.filter((axis) => !isEmpty(axis));
      }
    
      const { spec } = generateChart(options.chartType ?? chartType, opts);
    
      if (!spec) {
        return null;
      }
    
      if (output === "spec") {
        if (isValid(width)) {
          spec.width = width;
        }
        if (isValid(height)) {
          spec.height = height;
        }
    
        return {
          spec: spec,
        };
      }
    
      return gentrateChartImageOrHtml(output, spec, {
        width: `${width ?? 500}px`,
        height: `${height ?? 500}px`,
      });
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions what the tool does (generates charts for specific analyses), it lacks critical behavioral details: it doesn't specify output format details (though the schema covers this), potential side effects, performance characteristics, error conditions, or any limitations. For a complex 26-parameter tool with no annotations, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences that efficiently state the tool's purpose and suitable use cases. It's front-loaded with the core functionality and avoids unnecessary elaboration. However, it could be slightly more structured by explicitly separating purpose from usage guidelines, and it doesn't waste words on redundant information already in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (26 parameters, no annotations, no output schema), the description is incomplete. It adequately explains the high-level purpose but fails to address behavioral aspects, output expectations, or integration context that would help an agent use it effectively. For a sophisticated chart generation tool with many configuration options, more comprehensive guidance is needed beyond the basic purpose statement.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 96%, meaning the schema already documents most parameters thoroughly. The description adds minimal parameter semantics beyond the schema—it mentions 'two-dimensional or multi-dimensional space' which hints at the data structure, but doesn't explain parameter relationships or provide additional context about how parameters interact. With high schema coverage, the baseline is 3, and the description doesn't significantly compensate beyond this.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate a scatter chart to visually display the distribution, clustering trends, and correlations of data points in two-dimensional or multi-dimensional space.' It specifies the verb ('Generate') and resource ('scatter chart'), and mentions key use cases like analyzing relationships and outlier detection. However, it doesn't explicitly differentiate from sibling tools like 'generate_cartesian_chart' or 'generate_heatmap_chart', which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage guidance by stating the tool is 'Suitable for analyzing relationships between variables, outlier detection, and similar scenarios.' This gives some context about when to use it, but it doesn't explicitly mention when NOT to use it or suggest alternatives among the many sibling chart tools. No explicit comparisons or exclusions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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