Excel MCP Server

Excel MCP Server

By yzfly GitHub

The Excel MCP Server is a powerful tool that enables natural language interaction with Excel files through the Model Context Protocol (MCP). It provides a comprehensive set of capabilities for reading, analyzing, visualizing, and writing Excel data.

data mcp
Overview

What is Excel MCP Server?

Excel MCP Server is a powerful tool that enables natural language interaction with Excel files through the Model Context Protocol (MCP), allowing users to read, analyze, visualize, and write Excel data seamlessly.

How to use Excel MCP Server?

To use the Excel MCP Server, set up a Python environment, install the necessary dependencies, and integrate it with Claude Desktop for natural language commands.

Key features of Excel MCP Server?

  • Excel File Operations: Read and write multiple Excel formats (XLSX, XLS, CSV, TSV, JSON), get file information, and sheet names.
  • Data Analysis: Perform summary statistics, data quality assessments, and create pivot tables.
  • Visualization: Generate charts and plots from Excel data and export visualizations as images.

Use cases of Excel MCP Server?

  1. Analyzing sales data from Excel files.
  2. Creating visual representations of data trends.
  3. Filtering and querying large datasets for insights.

FAQ from Excel MCP Server?

  • Can I use Excel MCP Server with any Excel file format?

Yes! It supports XLSX, XLS, CSV, TSV, and JSON formats.

  • Is there a limit on file size?

Yes, there are security considerations that limit file size to prevent performance issues.

  • How do I install the Excel MCP Server?

Follow the installation instructions provided in the documentation to set up the server in a Python environment.

Content

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
  1. Install dependencies:
# Using uv
uv pip install -r requirements.txt

# Or using pip
pip install -r requirements.txt

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

No tools information available.
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