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generate_line_chart

Read-only

Create line charts to visualize trends over time using time-series data, with customizable styling, themes, and dimensions for clear trend analysis.

Instructions

Generate a line chart to show trends over time, such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesData for line chart, it should be an array of objects, each object contains a `time` field and a `value` field, such as, [{ time: '2015', value: 23 }, { time: '2016', value: 32 }], when the data is grouped by time, the `group` field should be used to specify the group, such as, [{ time: '2015', value: 23, group: 'A' }, { time: '2015', value: 32, group: 'B' }].
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

  • MCP generic tool execution handler that handles calls to 'generate_line_chart' by delegating to the callTool utility function.
    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);
    });
  • src/server.ts:66-68 (registration)
    Registers 'generate_line_chart' tool in the MCP tools/list response via imported Charts.line.tool object.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: getEnabledTools().map((chart) => chart.tool),
    }));
  • Defines the tool descriptor for 'generate_line_chart' including name, description, input schema (derived from Zod schema above), and annotations.
    // Line chart tool descriptor
    const tool = {
      name: "generate_line_chart",
      description:
        "Generate a line chart to show trends over time, such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016.",
      inputSchema: zodToJsonSchema(schema),
      annotations: {
        title: "Generate Line Chart",
        readOnlyHint: true,
      },
    };
    
    export const line = {
      schema,
      tool,
    };
  • Dispatches 'generate_line_chart' to chartType 'line', validates args against line schema, generates and returns the chart URL for line charts.
    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."}`,
        );
      }
    }
  • Helper function that generates the chart URL for 'line' type by sending POST request to the visualization service with chart config.
    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 provide readOnlyHint=true, indicating this is a safe read operation. The description adds context by specifying the chart type (line chart) and its purpose (showing trends over time), which is useful beyond annotations. However, it doesn't disclose behavioral traits like output format (e.g., image URL, base64), error handling, or performance considerations. With annotations covering safety, the description adds some value but lacks rich behavioral details.

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 concise and front-loaded, stating the purpose in the first sentence. The example adds clarity without being verbose. However, it could be slightly more structured by explicitly mentioning key parameters or usage scenarios, but overall, it's efficient with minimal waste.

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 tool's complexity (8 parameters, nested objects) and lack of output schema, the description is moderately complete. It covers the core purpose and provides an example, but doesn't explain the output (e.g., what is returned, such as an image or chart object), which is a gap since there's no output schema. With good schema coverage and annotations, it's adequate but could better address missing elements like result format.

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%, so the schema fully documents all 8 parameters. The description doesn't add any parameter-specific semantics beyond what's in the schema; it only gives a high-level example without explaining individual parameters. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, 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 line chart to show trends over time.' It provides a specific verb ('Generate') and resource ('line chart'), with an example illustrating its use for time-series data. However, it doesn't explicitly differentiate from sibling tools like 'generate_area_chart' or 'generate_scatter_chart', which might also show trends over time, leaving some ambiguity about when to choose a line chart specifically.

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 minimal guidance on usage. It includes an example ('such as, the ratio of Apple computer sales to Apple's profits changed from 2000 to 2016'), which implies use for time-based trends, but lacks explicit when-to-use criteria, prerequisites, or alternatives. No mention is made of when to choose this over sibling tools like 'generate_area_chart' or 'generate_bar_chart', leaving the agent to infer based on the example alone.

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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