Excel MCP Server - Model Context Protocol for Excel without Microsoft Excel

A Model Context Protocol (MCP) server that lets you manipulate Excel files without needing Microsoft Excel installed. Create, read, write, and analyze Excel workbooks (.xlsx, .xlsm) with AI assistants like Claude. Complete Excel automation through LLM integration.

Key Features:

• ✅ Read and write Excel files without Microsoft Excel
• ✅ Full support for XLSX, XLSM, XLTX, XLTM formats
• ✅ Create charts, pivot tables, and dashboards
• ✅ Import/export CSV, JSON, SQL, PDF
• ✅ Works with Claude AI and other LLM assistants
• ✅ Cross-platform: Windows, macOS, Linux
• ✅ Easy installation via npm/npx

🌟 Features - Excel MCP Server

Complete Excel Manipulation without Microsoft Excel

• 📊 Excel file operations: Read and write XLSX, XLSM, XLTX, XLTM files
• 📖 Data extraction: Read data from Excel sheets with pagination support
• ✍️ Write operations: Write data and formulas to Excel workbooks
• 📋 Sheet management: Create, delete, rename, and copy worksheets
• 📈 Charts and visualizations: Create charts, pivot tables, and dashboards
• 🔄 Data import/export: Import from CSV, JSON, SQL and export to multiple formats
• 🎨 Professional formatting: Automatic styling and formatting for Excel documents

Key Capabilities

📊 Data Operations

• Read and write Excel files with full formatting support
• Create professional tables with automatic styling
• Generate charts and visualizations
• Import from CSV, JSON, and SQL sources
• Export to multiple formats (CSV, JSON, PDF)

🎨 Professional Formatting

• Automatic column width adjustment
• Rich text formatting and styling
• Professional color schemes and themes
• Publication-ready document generation

🏗️ Advanced Features

• Dynamic dashboards with multiple visualizations
• Template-based report generation
• Data filtering and analysis
• Pivot tables and advanced calculations
• Batch processing and automation

🔐 Security & Trust

Security Score: 100/100 | Risk Level: Low

This project has been independently audited by MseeP.ai, providing ongoing security validation and trust assessment for the MCP ecosystem.

🚀 Quick Start - Excel MCP Server Installation

Installation

The easiest way to use Excel MCP Server is with npx (no installation required):

npx @guillehr2/excel-mcp-server@latest

Or install globally:

npm install -g @guillehr2/excel-mcp-server

Configuration

Add to your MCP client configuration (e.g., Claude Desktop):

Using npx (Recommended)

{
  "mcpServers": {
    "excel-master": {
      "command": "npx",
      "args": [
        "-y",
        "@guillehr2/excel-mcp-server@latest"
      ]
    }
  }
}

Using specific version

{
  "mcpServers": {
    "excel-master": {
      "command": "npx",
      "args": [
        "-y",
        "@guillehr2/excel-mcp-server@1.0.7"
      ]
    }
  }
}

Using global installation

{
  "mcpServers": {
    "excel-master": {
      "command": "excel-mcp-server"
    }
  }
}

Development mode

If you're developing or want to run from source:

{
  "mcpServers": {
    "excel-master": {
      "command": "node",
      "args": ["path/to/Excel-MCP-Server-Master/index.js"]
    }
  }
}

🛠️ Excel MCP Server Tools - Complete Excel Automation

Excel File Operations without Microsoft Excel

• Create Excel workbooks - create_workbook_tool
• Open Excel files - open_workbook_tool (XLSX, XLSM, XLTX, XLTM)
• Save Excel files - save_workbook_tool
• List Excel sheets - list_sheets_tool
• Manage worksheets - add_sheet_tool, delete_sheet_tool, rename_sheet_tool

Excel Data Manipulation

• Write to Excel - write_sheet_data_tool, update_cell_tool
• Read from Excel - Built-in data extraction with pagination
• Excel tables - add_table_tool, create_formatted_table_tool
• Excel formulas - Full formula support in all write operations

Excel Charts and Analysis

• Create Excel charts - add_chart_tool (column, bar, line, pie, scatter)
• Excel dashboards - create_dashboard_tool
• Pivot tables - Advanced data analysis
• Data filtering - filter_data_tool

Import/Export Excel Data

• Import to Excel - import_data_tool (CSV, JSON, SQL)
• Export from Excel - export_data_tool (CSV, JSON, PDF)
• PDF export - export_single_sheet_pdf_tool, export_sheets_pdf_tool

💡 Usage Examples

Creating a Professional Report

# Create a new workbook with formatted data
result = create_formatted_table_tool(
    file_path="sales_report.xlsx",
    sheet_name="Q4 Sales",
    start_cell="A1",
    data=[
        ["Region", "Q4 Sales", "Growth %"],
        ["North", 125000, 15.2],
        ["South", 98000, 8.7],
        ["East", 156000, 22.1],
        ["West", 89000, -3.2]
    ],
    table_name="Q4SalesData",
    table_style="TableStyleMedium9",
    formats={
        "B2:B5": "#,##0",  # Number format for sales
        "C2:C5": "0.0%",   # Percentage format
        "A1:C1": {"bold": True, "fill_color": "366092"}  # Header styling
    }
)

# Add a chart based on the table data
chart_result = add_chart_tool(
    file_path="sales_report.xlsx",
    sheet_name="Q4 Sales",
    chart_type="column",
    data_range="A1:B5",
    title="Q4 Sales by Region",
    position="E2",
    style="colorful-1"
)

Building a Dynamic Dashboard

# Create a comprehensive dashboard
dashboard_result = create_dashboard_tool(
    file_path="executive_dashboard.xlsx",
    data={
        "Data": [
            ["Month", "Revenue", "Expenses", "Profit"],
            ["Jan", 50000, 30000, 20000],
            ["Feb", 55000, 32000, 23000],
            ["Mar", 48000, 29000, 19000]
        ]
    },
    dashboard_config={
        "tables": [
            {
                "sheet": "Dashboard",
                "name": "MonthlyData",
                "range": "Data!A1:D4",
                "style": "TableStyleMedium9"
            }
        ],
        "charts": [
            {
                "sheet": "Dashboard",
                "type": "line",
                "data_range": "Data!A1:B4",
                "title": "Revenue Trend",
                "position": "E1",
                "style": "dark-blue"
            },
            {
                "sheet": "Dashboard",
                "type": "column",
                "data_range": "Data!A1:D4",
                "title": "Monthly Comparison",
                "position": "E15",
                "style": "colorful-2"
            }
        ]
    }
)

Data Import and Analysis

# Import data from multiple sources
import_result = import_data_tool(
    excel_file="analysis.xlsx",
    import_config={
        "csv": [
            {
                "file_path": "sales_data.csv",
                "sheet_name": "Sales",
                "delimiter": ",",
                "encoding": "utf-8"
            }
        ],
        "json": [
            {
                "file_path": "customer_data.json",
                "sheet_name": "Customers",
                "format": "records"
            }
        ]
    },
    create_tables=True
)

# Filter and analyze the imported data
filtered_data = filter_data_tool(
    file_path="analysis.xlsx",
    sheet_name="Sales",
    table_name="Table_Sales_1",
    filters={
        "Region": ["North", "South"],
        "Sales": {"gt": 10000}
    }
)

🎨 Professional Features

Automatic Formatting

The server automatically applies professional formatting:

• Column width adjustment based on content length
• Row height optimization for wrapped text
• Professional color schemes for charts and tables
• Consistent styling throughout documents

Chart Styling

Extensive chart customization options:

• 50+ predefined styles (light, dark, colorful themes)
• Custom color palettes for brand consistency
• Professional layouts with proper spacing
• Multiple chart types: column, bar, line, pie, scatter, area

Template System

Create reports from templates:

• Reusable templates for consistent reporting
• Dynamic data substitution
• Automatic chart updates
• Format preservation

📋 Requirements

• Node.js 14.0 or higher
• Python 3.8 or higher
• Operating System: Windows, macOS, or Linux

Python dependencies are automatically installed on first run:

• fastmcp
• openpyxl
• pandas
• numpy
• matplotlib
• xlsxwriter
• xlrd
• xlwt

📚 Documentation

For detailed documentation, see:

• 📖 Quick Start Guide
• 🔧 API Reference
• 💡 Examples
• 📝 Changelog

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

# Clone the repository
git clone https://github.com/guillehr2/Excel-MCP-Server-Master.git
cd Excel-MCP-Server-Master

# Install dependencies
npm install
pip install -r requirements.txt

# Run in development mode
node index.js

🐛 Troubleshooting

Common Issues

1. Python not found: Ensure Python 3.8+ is installed and in your PATH
2. Dependencies fail to install: Try running with administrator privileges
3. MCP client doesn't recognize the server: Restart your MCP client after configuration

For more help, see our troubleshooting guide or open an issue.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with FastMCP
• Excel manipulation powered by openpyxl
• Data processing with pandas
• Published on npm for easy distribution
• Special thanks to lwsinclair for the independent security audit and MseeP.ai integration

📊 Stats

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Made with ❤️ for the MCP ecosystem

If you find this Excel MCP Server useful, please consider giving it a ⭐ on GitHub!

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Excel MCP Server by Guillem Hermida | GitHub | NPM | Contact: qtmsuite@gmail.com

Excel manipulation without Microsoft Excel - Model Context Protocol server for Claude AI and LLM integration