MCP Excel Server for Excel operations through the Model Context Protocol
Project description
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
- 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
- Install dependencies:
# Using uv
uv pip install -r requirements.txt
# Or using pip
pip install -r requirements.txt
Integration with Claude Desktop
- Install Claude Desktop
- Open Settings and go to the Developer tab
- 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 filesget_excel_info: Get file detailsget_sheet_names: List worksheet names
Data Analysis
analyze_excel: Perform statistical analysisfilter_excel: Filter data by conditionspivot_table: Create pivot tablesdata_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 filesupdate_excel: Update existing Excel files
Available Resources
excel://{file_path}: Get file contentexcel://{file_path}/info: Get file structure informationexcel://{file_path}/preview: Generate data preview image
Prompt Templates
analyze_excel_data: Guided template for Excel data analysiscreate_chart: Help create data visualizationsdata_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
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