Skip to main content
Glama
idapixl

MCP Starter Kit

transform_data

Convert data between formats like JSON, CSV, TSV, Markdown tables, and text summaries to reformat API responses, prepare data for display, or normalize spreadsheet exports.

Instructions

Convert data between formats: JSON, CSV, TSV, Markdown table, and plain text summary. Useful for reformatting API responses, preparing data for display, or normalising spreadsheet exports.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesThe raw input data to transform
from_formatYesInput data format
to_formatYesDesired output format
optionsNo

Implementation Reference

  • The main handler function for the `transform_data` tool, which manages input parsing, normalization, and formatting.
    export async function transformData(
      input: TransformDataInput
    ): Promise<ToolResult<TransformDataResult>> {
      const { from_format, to_format } = input;
      const options = input.options ?? {};
      const pretty = options.pretty ?? true;
      const include_header = options.include_header ?? true;
      const delimiter = options.delimiter;
    
      if (input.input.length > config.transformerMaxInput) {
        return {
          ok: false,
          error: `Input exceeds maximum size of ${config.transformerMaxInput} characters`,
          code: "INPUT_TOO_LARGE",
        };
      }
    
      logger.debug("Transforming data", { from_format, to_format });
    
      // Determine actual delimiters
      const inputDelimiter = delimiter ?? (from_format === "tsv" ? "\t" : ",");
      const outputDelimiter = to_format === "tsv" ? "\t" : ",";
    
      let parsed: unknown;
      try {
        if (from_format === "json") {
          parsed = parseJson(input.input);
        } else if (from_format === "csv" || from_format === "tsv") {
          parsed = parseCsvOrTsv(input.input, inputDelimiter);
        } else {
          parsed = parseText(input.input);
        }
      } catch (err) {
        return {
          ok: false,
          error: `Failed to parse input as ${from_format}: ${(err as Error).message}`,
          code: "PARSE_ERROR",
        };
      }
    
      let normalised: { headers: string[]; rows: string[][] };
      try {
        normalised = normalise(parsed, from_format);
      } catch (err) {
        return {
          ok: false,
          error: `Failed to normalise data: ${(err as Error).message}`,
          code: "NORMALISE_ERROR",
        };
      }
    
      let output: string;
      try {
        switch (to_format) {
          case "json":
            output = toJson(normalised, pretty);
            break;
          case "csv":
            output = toCsvOrTsv(normalised, ",", include_header);
            break;
          case "tsv":
            output = toCsvOrTsv(normalised, outputDelimiter, include_header);
            break;
          case "markdown_table":
            output = toMarkdownTable(normalised);
            break;
          case "text_summary":
            output = toTextSummary(normalised);
            break;
          default:
            return {
              ok: false,
              error: `Unknown to_format: ${to_format as string}`,
              code: "UNKNOWN_FORMAT",
            };
        }
      } catch (err) {
        return {
          ok: false,
          error: `Failed to format output as ${to_format}: ${(err as Error).message}`,
          code: "FORMAT_ERROR",
        };
      }
    
      logger.info("Transform complete", {
        from_format,
        to_format,
        rows: normalised.rows.length,
      });
    
      return {
        ok: true,
        data: {
          input_format: from_format,
          output_format: to_format,
          output,
          rows_processed: normalised.rows.length,
          transformed_at: new Date().toISOString(),
        },
      };
    }

Tool Definition Quality

Score is being calculated. Check back soon.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/idapixl/mcp-starter-kit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server