Excel MCP Server

An MCP server that provides comprehensive Excel file management and data analysis capabilities.

Features

• Excel File Operations
• Read multiple Excel formats (XLSX, XLS, CSV, TSV, JSON)
• Write and update Excel files
• Get file information and sheet names

• Data Analysis
• Summary statistics and descriptive analysis
• Data quality assessment
• Pivot tables
• Filtering and querying data

• Visualization
• Generate charts and plots from Excel data
• Create data previews
• Export visualizations as images

Installation

1. Create a new Python environment (recommended):

# Using uv (recommended)
uv init excel-mcp-server
cd excel-mcp-server
uv venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Or using pip
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

2. Install dependencies:

# Using uv
uv pip install -e .

Integration with Claude Desktop

1. Install Claude Desktop

2. Open Settings and go to the Developer tab

3. Edit claude_desktop_config.json:

{
  "mcpServers": {
      "command": "uvx",
      "args": [
        "mcp-excel-server"
      ],
      "env": {
        "PYTHONPATH": "/path/to/your/python"
      }
  }
}

Available Tools

File Reading

• read_excel: Read Excel files
• get_excel_info: Get file details
• get_sheet_names: List worksheet names

Data Analysis

• analyze_excel: Perform statistical analysis
• filter_excel: Filter data by conditions
• pivot_table: Create pivot tables
• data_summary: Generate comprehensive data summary

Data Visualization

• export_chart: Generate charts
• Supports line charts, bar charts, scatter plots, histograms

File Operations

• write_excel: Write new Excel files
• update_excel: Update existing Excel files

Available Resources

• excel://{file_path}: Get file content
• excel://{file_path}/info: Get file structure information
• excel://{file_path}/preview: Generate data preview image

Prompt Templates

• analyze_excel_data: Guided template for Excel data analysis
• create_chart: Help create data visualizations
• data_cleaning: Assist with data cleaning

Usage Examples

• "Analyze my sales_data.xlsx file"
• "Create a bar chart for product_sales.csv"
• "Filter employees over 30 in employees.xlsx"
• "Generate a pivot table of department sales"

Security Considerations

• Read files only from specified paths
• Limit file size
• Prevent accidental file overwriting
• Strictly control data transformation operations

Dependencies

• pandas
• numpy
• matplotlib
• seaborn

License

MIT License