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/[email protected]"
      ]
    }
  }
}

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

Python not found: Ensure Python 3.8+ is installed and in your PATH
Dependencies fail to install: Try running with administrator privileges
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

GitHub last commit GitHub issues GitHub pull requests npm bundle size

Made with ❤️ for the MCP ecosystem

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

Excel MCP Server by Guillem Hermida | GitHub | NPM | Contact: [email protected]

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