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VisActor

vchart-mcp-server

Official
by VisActor

generate_progress_chart

Create progress charts to visualize completion rates, proportional metrics, and normalized quantitative values between 0 and 1 using gauge, liquid, linear, or circular formats.

Instructions

Generates a progress chart for visualizing quantitative values normalized between 0 and 1. Ideal for representing progress, completion rates, or proportional metrics. The gauge chart and liquid chart currently only supports displaying data for a single dimension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNoChart output type. Defaults to 'image'.image
widthNoChart width. Optional, defaults to 500.
heightNoChart height. Optional, defaults to 500.
dataTableYesData for the progress chart, e.g., [{ category: 'category 01', value: 0.5 }].
chartTypeYes
colorFieldNoDimension field, Must exist in the data, required in linear_progress, circular_progress and gauge
valueFieldYesMeasure field with values in [0, 1]. Must exist in the data.
chartThemeNoChart theme. Optional, defaults to 'light'.
titleNoChart title text.
subTitleNoChart subtitle text.
titleOrientNoTitle position in the chart.
backgroundNoChart background color (hex). Optional, defaults to white.
colorsNoColor palette for chart elements.

Implementation Reference

  • The MCP CallToolRequest handler that executes 'generate_progress_chart' by identifying the 'progress' chart type from the tool name, validating arguments with the progress schema, invoking generateChartByType('progress', args), and formatting the response as text content (spec, image URL, or HTML URL).
    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 for generate_progress_chart, including output format, dimensions, dataTable, chartType (linear_progress, circular_progress, gauge, liquid), valueField, styling options like theme, title, background, and colors.
    const schema = z.object({
      output: ChartOutputSchema,
      width: WidthSchema,
      height: HeightSchema,
      dataTable: z
        .array(z.any())
        .describe(
          "Data for the progress chart, e.g., [{ category: 'category 01', value: 0.5 }]."
        )
        .nonempty({
          message: "Data for the progress chart must not be empty.",
        }),
      chartType: z.enum([
        "linear_progress",
        "circular_progress",
        "gauge",
        "liquid",
      ]),
    
      colorField: z
        .string()
        .optional()
        .describe(
          "Dimension field, Must exist in the data, required in linear_progress, circular_progress and gauge"
        ),
      valueField: ProgressFieldSchema,
    
      chartTheme: ThemeSchema,
      title: TitleTextSchema,
      subTitle: TitleSubTextSchema,
      titleOrient: TitleOrientSchema,
    
      background: BackgroundSchema,
      colors: ColorsSchema,
    });
  • Defines and exports the tool metadata for 'generate_progress_chart', including name, description, and JSON schema derived from Zod for MCP tool registration.
    const tool = {
      name: "generate_progress_chart",
      description:
        "Generates a progress chart for visualizing quantitative values normalized between 0 and 1. Ideal for representing progress, completion rates, or proportional metrics. The gauge chart and liquid chart currently only supports displaying data for a single dimension.",
      inputSchema: convertZodToJsonSchema(schema),
    };
    
    export const progress = {
      schema,
      tool,
    };
  • src/server.ts:34-38 (registration)
    MCP ListToolsRequest handler that dynamically registers all chart tools, including generate_progress_chart, by collecting .tool objects from imported charts modules.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: Object.values(Charts).map(chart => (chart as any).tool),
      };
    });
  • Primary helper function invoked by the handler for 'progress' chartType; normalizes options, extracts fields/axes/title, generates VChart spec using generateChart from @visactor/generate-vchart (with sub chartType), and renders to image URL, HTML URL, or spec via external service.
    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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool generates charts and specifies constraints for gauge/liquid charts (single dimension only), but fails to describe critical behaviors like whether this is a read-only operation, what permissions might be needed, how errors are handled, or what the output looks like (beyond implied visual formats). For a complex 13-parameter tool with no annotations, this is a significant gap.

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 directly address the tool's purpose and key constraints. It's front-loaded with the main functionality and avoids unnecessary elaboration. However, the second sentence could be slightly clearer in structure ('The gauge chart and liquid chart currently only supports' has minor grammatical issues).

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 (13 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain what the tool returns (e.g., image data, HTML code, or specification object), doesn't cover error conditions or performance characteristics, and provides minimal guidance on parameter interactions. For a chart generation tool with multiple output types and chart variants, more contextual information would be helpful.

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?

The schema description coverage is high at 92%, so most parameters are documented in the schema itself. The description adds minimal parameter semantics beyond the schema—it mentions 'quantitative values normalized between 0 and 1' (relevant to valueField) and 'single dimension' constraint (relevant to dataTable structure for certain chart types). This meets the baseline expectation when schema coverage is high but doesn't provide substantial additional value.

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: 'Generates a progress chart for visualizing quantitative values normalized between 0 and 1.' It specifies the resource (progress chart) and verb (generates), and mentions specific use cases like progress, completion rates, or proportional metrics. However, it doesn't explicitly differentiate from sibling tools like generate_cartesian_chart or generate_scatter_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 some implied usage guidance by stating it's 'ideal for representing progress, completion rates, or proportional metrics' and noting that 'gauge chart and liquid chart currently only supports displaying data for a single dimension.' However, it lacks explicit when-to-use vs. when-not-to-use instructions or named alternatives among sibling tools, leaving the agent to infer appropriate contexts.

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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