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generate_scatter_chart

Read-only

Create scatter charts to visualize relationships between two variables, identify correlations, and reveal data distribution patterns for analysis.

Instructions

Generate a scatter chart to show the relationship between two variables, helps discover their relationship or trends, such as, the strength of correlation, data distribution patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesData for scatter chart, such as, [{ x: 10, y: 15 }], when the data is grouped, the group name can be specified in the `group` field, such as, [{ x: 10, y: 15, group: 'Group A' }].
styleNoStyle configuration for the chart with a JSON object, optional.
themeNoSet the theme for the chart, optional, default is 'default'.default
widthNoSet the width of chart, default is 600.
heightNoSet the height of chart, default is 400.
titleNoSet the title of chart.
axisXTitleNoSet the x-axis title of chart.
axisYTitleNoSet the y-axis title of chart.

Implementation Reference

  • Generic handler for all chart generation tools, including 'generate_scatter_chart'. Maps the tool name to chart type 'scatter', validates input using the schema, and calls generateChartUrl to produce the chart URL.
    export async function callTool(tool: string, args: object = {}) {
      logger.info(`Calling tool: ${tool}`);
      const chartType = CHART_TYPE_MAP[tool as keyof typeof CHART_TYPE_MAP];
    
      if (!chartType) {
        logger.error(`Unknown tool: ${tool}`);
        throw new McpError(ErrorCode.MethodNotFound, `Unknown tool: ${tool}.`);
      }
    
      try {
        // Validate input using Zod before sending to API.
        // Select the appropriate schema based on the chart type.
        const schema = Charts[chartType].schema;
    
        if (schema) {
          // Use safeParse instead of parse and try-catch.
          const result = z.object(schema).safeParse(args);
          if (!result.success) {
            logger.error(`Invalid parameters: ${result.error.message}`);
            throw new McpError(
              ErrorCode.InvalidParams,
              `Invalid parameters: ${result.error.message}`,
            );
          }
        }
    
        const isMapChartTool = [
          "generate_district_map",
          "generate_path_map",
          "generate_pin_map",
        ].includes(tool);
    
        if (isMapChartTool) {
          // For map charts, we use the generateMap function, and return the mcp result.
          const { metadata, ...result } = await generateMap(tool, args);
          return result;
        }
    
        const url = await generateChartUrl(chartType, args);
        logger.info(`Generated chart URL: ${url}`);
    
        return {
          content: [
            {
              type: "text",
              text: url,
            },
          ],
          _meta: {
            description:
              "This is the chart's spec and configuration, which can be renderred to corresponding chart by AntV GPT-Vis chart components.",
            spec: { type: chartType, ...args },
          },
        };
        // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      } catch (error: any) {
        logger.error(
          `Failed to generate chart: ${error.message || "Unknown error"}.`,
        );
        if (error instanceof McpError) throw error;
        if (error instanceof ValidateError)
          throw new McpError(ErrorCode.InvalidParams, error.message);
        throw new McpError(
          ErrorCode.InternalError,
          `Failed to generate chart: ${error?.message || "Unknown error."}`,
        );
      }
    }
  • Zod schema definition for input validation and tool descriptor (name, description, inputSchema) for the 'generate_scatter_chart' tool.
    const schema = {
      data: z
        .array(data)
        .describe(
          "Data for scatter chart, such as, [{ x: 10, y: 15 }], when the data is grouped, the group name can be specified in the `group` field, such as, [{ x: 10, y: 15, group: 'Group A' }].",
        )
        .nonempty({ message: "Scatter chart data cannot be empty." }),
      style: z
        .object({
          backgroundColor: BackgroundColorSchema,
          palette: PaletteSchema,
          texture: TextureSchema,
        })
        .optional()
        .describe(
          "Style configuration for the chart with a JSON object, optional.",
        ),
      theme: ThemeSchema,
      width: WidthSchema,
      height: HeightSchema,
      title: TitleSchema,
      axisXTitle: AxisXTitleSchema,
      axisYTitle: AxisYTitleSchema,
    };
    
    // Scatter chart tool descriptor
    const tool = {
      name: "generate_scatter_chart",
      description:
        "Generate a scatter chart to show the relationship between two variables, helps discover their relationship or trends, such as, the strength of correlation, data distribution patterns.",
      inputSchema: zodToJsonSchema(schema),
      annotations: {
        title: "Generate Scatter Chart",
        readOnlyHint: true,
      },
    };
  • src/server.ts:64-77 (registration)
    Registers the MCP tool handlers: ListTools returns tool descriptors including 'generate_scatter_chart', and CallToolRequest dispatches to the callTool handler.
    function setupToolHandlers(server: Server): void {
      logger.info("setting up tool handlers...");
      server.setRequestHandler(ListToolsRequestSchema, async () => ({
        tools: getEnabledTools().map((chart) => chart.tool),
      }));
    
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      server.setRequestHandler(CallToolRequestSchema, async (request: any) => {
        logger.info("calling tool", request.params.name, request.params.arguments);
    
        return await callTool(request.params.name, request.params.arguments);
      });
      logger.info("tool handlers set up");
    }
  • Mapping from tool names to internal chart types, mapping 'generate_scatter_chart' to 'scatter'.
    const CHART_TYPE_MAP = {
      generate_area_chart: "area",
      generate_bar_chart: "bar",
      generate_boxplot_chart: "boxplot",
      generate_column_chart: "column",
      generate_district_map: "district-map",
      generate_dual_axes_chart: "dual-axes",
      generate_fishbone_diagram: "fishbone-diagram",
      generate_flow_diagram: "flow-diagram",
      generate_funnel_chart: "funnel",
      generate_histogram_chart: "histogram",
      generate_line_chart: "line",
      generate_liquid_chart: "liquid",
      generate_mind_map: "mind-map",
      generate_network_graph: "network-graph",
      generate_organization_chart: "organization-chart",
      generate_path_map: "path-map",
      generate_pie_chart: "pie",
      generate_pin_map: "pin-map",
      generate_radar_chart: "radar",
      generate_sankey_chart: "sankey",
      generate_scatter_chart: "scatter",
      generate_treemap_chart: "treemap",
      generate_venn_chart: "venn",
      generate_violin_chart: "violin",
      generate_waterfall_chart: "waterfall",
      generate_word_cloud_chart: "word-cloud",
    } as const;
  • Core function called by the handler to generate the chart URL by sending the chart type and options to the external visualization service API.
    export async function generateChartUrl(
      type: string,
      // biome-ignore lint/suspicious/noExplicitAny: <explanation>
      options: Record<string, any>,
    ): Promise<string> {
      const url = getVisRequestServer();
    
      const response = await axios.post(
        url,
        {
          type,
          ...options,
          source: "mcp-server-chart",
        },
        {
          headers: {
            "Content-Type": "application/json",
          },
        },
      );
      const { success, errorMessage, resultObj } = response.data;
    
      if (!success) {
        throw new Error(errorMessage);
      }
    
      return resultObj;
    }
Behavior3/5

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

Annotations indicate readOnlyHint=true, suggesting this is a safe read operation (likely generating a chart without side effects). The description doesn't contradict this, as 'Generate' aligns with a read operation in this context. However, it adds minimal behavioral context beyond annotations—it mentions the chart's purpose but not details like output format (e.g., image URL, base64), performance considerations, or error handling. With annotations covering safety, a 3 is appropriate for limited added value.

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 a single, efficient sentence that front-loads the core purpose. It avoids redundancy and wastes no words. However, it could be slightly more structured by separating usage context from purpose, but it's still highly concise and clear.

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

Completeness3/5

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

Given the complexity (8 parameters, nested objects) and lack of output schema, the description is minimally adequate. It states what the tool does but doesn't cover output details (e.g., what is returned—a chart image, data, or error), performance limits, or advanced usage scenarios. With annotations providing safety info and schema covering parameters, it meets a basic threshold but leaves gaps for agent invocation.

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 100%, meaning all parameters are documented in the schema. The description adds no specific parameter information beyond the general purpose of showing relationships between variables. It doesn't explain parameter interactions, defaults, or usage examples. Given the high schema coverage, the baseline is 3, as the description doesn't compensate but also doesn't detract.

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 show the relationship between two variables.' It specifies the verb ('Generate') and resource ('scatter chart'), and mentions the goal of discovering relationships or trends. However, it doesn't explicitly differentiate this from sibling tools like 'generate_line_chart' or 'generate_bar_chart' beyond the scatter chart type, which keeps it from 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 Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions that scatter charts help discover relationships or trends, but doesn't specify scenarios where a scatter chart is preferred over other chart types (e.g., line charts for time series, bar charts for categorical comparisons). There's no mention of prerequisites, exclusions, or explicit alternatives among the sibling tools.

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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