Skip to main content
Glama
guangxiangdebizi

XLSX Reader MCP

read_xlsx

Extract and convert data from Excel files by reading specific sheets, cell ranges, or searching for values in columns, with output in JSON, CSV, or table format.

Instructions

Read and extract data from Excel (xlsx) files. Supports reading specific sheets, cell ranges, and converting data to various formats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to the Excel file to read
sheetNameNoName of the specific sheet to read (optional, defaults to first sheet)
rangeNoCell range to read (e.g., 'A1:C10', optional, defaults to entire sheet)
formatNoOutput format for the data (default: table)
includeHeadersNoWhether to include headers in the output (default: true)
maxRowsNoMaximum number of rows to return (default: 100, max: 1000)
searchColumnNoColumn name or index to search in (e.g., 'A', '1', or 'Name')
searchValueNoValue to search for in the specified column
searchTypeNoType of search to perform (default: exact)

Implementation Reference

  • The async run() function that implements the core tool logic: input validation, file existence check, workbook reading with XLSX library, sheet/range selection, data filtering (empty rows, search), row limiting, output formatting (json/csv/table), and error handling with detailed summary.
    async run(args: { 
      filePath: string; 
      sheetName?: string; 
      range?: string; 
      format?: "json" | "csv" | "table";
      includeHeaders?: boolean;
      maxRows?: number;
      searchColumn?: string;
      searchValue?: string;
      searchType?: "exact" | "contains" | "startsWith" | "endsWith";
    }) {
      try {
        // Parameter validation
        if (!args.filePath) {
          throw new Error("File path is required");
        }
    
        // Check if file exists
        if (!fs.existsSync(args.filePath)) {
          throw new Error(`File not found: ${args.filePath}`);
        }
    
        // Check file extension
        const ext = path.extname(args.filePath).toLowerCase();
        if (!['.xlsx', '.xls', '.xlsm'].includes(ext)) {
          throw new Error("File must be an Excel file (.xlsx, .xls, or .xlsm)");
        }
    
        // Read the workbook
        const workbook = XLSX.readFile(args.filePath);
        
        // Get sheet names
        const sheetNames = workbook.SheetNames;
        if (sheetNames.length === 0) {
          throw new Error("No sheets found in the workbook");
        }
    
        // Determine which sheet to read
        let targetSheet: string;
        if (args.sheetName) {
          if (!sheetNames.includes(args.sheetName)) {
            throw new Error(`Sheet '${args.sheetName}' not found. Available sheets: ${sheetNames.join(', ')}`);
          }
          targetSheet = args.sheetName;
        } else {
          targetSheet = sheetNames[0];
        }
    
        // Get the worksheet
        const worksheet = workbook.Sheets[targetSheet];
        
        // Extract data based on format
        const format = args.format || "table";
        const includeHeaders = args.includeHeaders !== false;
        const maxRows = Math.min(args.maxRows || 100, 1000); // Default 100, max 1000
        const skipEmptyRows = true; // Always skip empty rows
        
        let data: any;
        let output: string;
        let originalTotalRows = 0;
        let nonEmptyDataRows = 0;
        let skippedEmptyRows = 0;
        let isDataTruncated = false;
        let filteredData: any[] = [];
        
        // Helper function to check if a row is empty
        const isEmptyRow = (row: any[]): boolean => {
          return row.every(cell => cell === '' || cell == null || cell === undefined);
        };
        
        // Helper function to perform search
        const performSearch = (data: any[][], searchColumn: string, searchValue: string, searchType: string) => {
          if (data.length === 0) return { filteredData: data, matchedRows: 0 };
          
          const headers = data[0];
          let columnIndex = -1;
          
          // Find column index
          if (/^\d+$/.test(searchColumn)) {
            // Numeric index (1-based)
            columnIndex = parseInt(searchColumn) - 1;
          } else if (/^[A-Z]+$/i.test(searchColumn)) {
            // Excel column letter (A, B, C, etc.)
            columnIndex = searchColumn.toUpperCase().charCodeAt(0) - 65;
          } else {
            // Column name
            columnIndex = headers.findIndex((header: any) => 
              String(header).toLowerCase() === searchColumn.toLowerCase()
            );
          }
          
          if (columnIndex === -1 || columnIndex >= headers.length) {
            throw new Error(`Column '${searchColumn}' not found. Available columns: ${headers.join(', ')}`);
          }
          
          // Filter rows based on search criteria
          const headerRow = [headers];
          const dataRows = data.slice(1);
          const matchedRows = dataRows.filter((row: any[]) => {
            const cellValue = String(row[columnIndex] || '').toLowerCase();
            const searchVal = searchValue.toLowerCase();
            
            switch (searchType) {
              case "contains":
                return cellValue.includes(searchVal);
              case "startsWith":
                return cellValue.startsWith(searchVal);
              case "endsWith":
                return cellValue.endsWith(searchVal);
              case "exact":
              default:
                return cellValue === searchVal;
            }
          });
          
          return {
            filteredData: [...headerRow, ...matchedRows],
            matchedRows: matchedRows.length
          };
        };
    
        if (args.range) {
          // Read specific range
          const range = XLSX.utils.decode_range(args.range);
          const rangeData: any[][] = [];
          
          for (let row = range.s.r; row <= range.e.r; row++) {
            const rowData: any[] = [];
            for (let col = range.s.c; col <= range.e.c; col++) {
              const cellAddress = XLSX.utils.encode_cell({ r: row, c: col });
              const cell = worksheet[cellAddress];
              rowData.push(cell ? cell.v : '');
            }
            rangeData.push(rowData);
          }
          data = rangeData;
        } else {
          // Read entire sheet
          let rawData = XLSX.utils.sheet_to_json(worksheet, { 
            header: 1,
            defval: ''
          }) as any[][];
          
          // Get sheet statistics before filtering
           originalTotalRows = rawData.length;
           
           // Always filter empty rows (except header)
           const headerRow = rawData.length > 0 ? [rawData[0]] : [];
           const dataRows = rawData.slice(1).filter(row => !isEmptyRow(row));
           filteredData = [...headerRow, ...dataRows];
           nonEmptyDataRows = dataRows.length;
           skippedEmptyRows = originalTotalRows - filteredData.length;
           
           // Apply search filter if specified
           if (args.searchColumn && args.searchValue) {
             const searchResults = performSearch(filteredData, args.searchColumn, args.searchValue, args.searchType || "exact");
             filteredData = searchResults.filteredData;
             nonEmptyDataRows = searchResults.matchedRows;
           }
           
           // Limit the number of rows for display
           const totalRowsToShow = includeHeaders ? maxRows + 1 : maxRows;
           data = filteredData.slice(0, totalRowsToShow);
           isDataTruncated = filteredData.length > totalRowsToShow;
        }
    
        // Format output
        switch (format) {
          case "json":
            if (includeHeaders && data.length > 0) {
              const headers = data[0];
              const rows = data.slice(1);
              const jsonData = rows.map((row: any[]) => {
                const obj: any = {};
                headers.forEach((header: string, index: number) => {
                  obj[header || `Column${index + 1}`] = row[index] || '';
                });
                return obj;
              });
              output = JSON.stringify(jsonData, null, 2);
            } else {
              output = JSON.stringify(data, null, 2);
            }
            break;
            
          case "csv":
            output = data.map((row: any[]) => 
              row.map((cell: any) => 
                typeof cell === 'string' && cell.includes(',') ? `"${cell}"` : cell
              ).join(',')
            ).join('\n');
            break;
            
          default: // table
            if (data.length === 0) {
              output = "No data found in the specified range.";
            } else {
              const maxCols = Math.max(...data.map((row: any[]) => row.length));
              const colWidths = Array(maxCols).fill(0);
              
              // Calculate column widths
              data.forEach((row: any[]) => {
                row.forEach((cell: any, index: number) => {
                  const cellStr = String(cell || '');
                  colWidths[index] = Math.max(colWidths[index], cellStr.length);
                });
              });
              
              // Format table
              const formatRow = (row: any[]) => {
                return '| ' + row.map((cell: any, index: number) => {
                  const cellStr = String(cell || '');
                  return cellStr.padEnd(colWidths[index]);
                }).join(' | ') + ' |';
              };
              
              const separator = '|' + colWidths.map(width => '-'.repeat(width + 2)).join('|') + '|';
              
              output = data.map((row: any[], index: number) => {
                const formattedRow = formatRow(row);
                if (index === 0 && includeHeaders) {
                  return formattedRow + '\n' + separator;
                }
                return formattedRow;
              }).join('\n');
            }
            break;
        }
    
        // Prepare summary with sheet statistics
        const summaryParts = [
          `πŸ“Š **Excel File Analysis**`,
          ``,
          `**File:** ${path.basename(args.filePath)}`,
          `**Sheet:** ${targetSheet}`,
          `**Available Sheets:** ${sheetNames.join(', ')}`,
          `**Format:** ${format}`,
          args.range ? `**Range:** ${args.range}` : `**Range:** Entire sheet`,
          ``,
          `## πŸ“Š Sheet Information`
        ];
        
        if (!args.range) {
            summaryParts.push(
              `- **Total Rows:** ${originalTotalRows} (including header)`,
              `- **Data Rows:** ${nonEmptyDataRows} (excluding header)`
            );
            if (skippedEmptyRows > 0) {
              summaryParts.push(`- **Empty Rows Filtered:** ${skippedEmptyRows}`);
            }
            if (args.searchColumn && args.searchValue) {
              summaryParts.push(
                `- **πŸ” Search Applied:** Column '${args.searchColumn}' ${args.searchType || 'exact'} '${args.searchValue}'`,
                `- **Search Results:** ${nonEmptyDataRows} matching rows found`
              );
            }
            if (isDataTruncated) {
              summaryParts.push(`- **⚠️ Display Limit:** Showing first ${maxRows} rows (${filteredData.length - (includeHeaders ? maxRows + 1 : maxRows)} more rows available)`);
            }
        } else {
          summaryParts.push(
            `- **Displayed Rows:** ${data.length}`,
            `- **Displayed Columns:** ${data.length > 0 ? Math.max(...data.map((row: any[]) => row.length)) : 0}`
          );
        }
        
        summaryParts.push(
          ``,
          `## Data Content`,
          ``,
          output
        );
        
        const summary = summaryParts.join('\n');
        
        return {
          content: [{
            type: "text",
            text: summary
          }]
        };
        
      } catch (error: any) {
        return {
          content: [{
            type: "text",
            text: `❌ **Error reading Excel file:** ${error.message}`
          }],
          isError: true
        };
      }
    }
  • JSON Schema defining the input parameters for the read_xlsx tool, including required filePath and optional parameters for sheet, range, output format, headers, row limit, and search criteria.
    parameters: {
      type: "object",
      properties: {
        filePath: {
          type: "string",
          description: "Path to the Excel file to read"
        },
        sheetName: {
          type: "string",
          description: "Name of the specific sheet to read (optional, defaults to first sheet)"
        },
        range: {
          type: "string",
          description: "Cell range to read (e.g., 'A1:C10', optional, defaults to entire sheet)"
        },
        format: {
          type: "string",
          enum: ["json", "csv", "table"],
          description: "Output format for the data (default: table)"
        },
        includeHeaders: {
          type: "boolean",
          description: "Whether to include headers in the output (default: true)"
        },
        maxRows: {
          type: "number",
          description: "Maximum number of rows to return (default: 100, max: 1000)"
        },
        searchColumn: {
          type: "string",
          description: "Column name or index to search in (e.g., 'A', '1', or 'Name')"
        },
        searchValue: {
          type: "string",
          description: "Value to search for in the specified column"
        },
        searchType: {
          type: "string",
          enum: ["exact", "contains", "startsWith", "endsWith"],
          description: "Type of search to perform (default: exact)"
        }
      },
      required: ["filePath"]
    },
  • src/index.ts:21-25 (registration)
    Registration of read_xlsx tool in the ListToolsRequestSchema handler, providing name, description, and inputSchema.
    {
      name: xlsxReader.name,
      description: xlsxReader.description,
      inputSchema: xlsxReader.parameters
    },
  • src/index.ts:38-39 (registration)
    Dispatch of read_xlsx tool calls to the xlsxReader.run() method in the CallToolRequestSchema handler.
    case "read_xlsx":
      return await xlsxReader.run(request.params.arguments as any);
  • src/index.ts:6-6 (registration)
    Import of the xlsxReader tool implementation.
    import { xlsxReader } from "./tools/xlsx-reader.js";
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/guangxiangdebizi/xlsx-mcp'

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