xlwings Excel

xlwings Excel

hyunjae-labs

Creates and manipulates Excel files without needing Microsoft Excel installed, using the xlwings library with 30+ automation tools.

Enables Excel file manipulation without Microsoft Excel installation through xlwings library, providing 30+ tools for workbook creation, data operations, formatting, formulas, charts, pivot tables, and worksheet management across Windows and cross-platform environments.

5370 views4Local (stdio)

What it does

  • Create and open Excel workbooks
  • Read and write cell data with formulas
  • Format cells and apply conditional formatting
  • Generate charts and pivot tables
  • Manage worksheets and ranges
  • Create Excel tables with styling

Best for

Automating Excel report generationData analysts processing spreadsheets programmaticallyBackend systems generating Excel exportsCross-platform Excel file manipulation
Works without Excel installation30+ Excel automation toolsSession-based architecture for performance

About xlwings Excel

xlwings Excel is a community-built MCP server published by hyunjae-labs that provides AI assistants with tools and capabilities via the Model Context Protocol. xlwings Excel: Manipulate Excel files without installing Excel. 30+ tools for workbooks, data ops, formatting, formulas, It is categorized under productivity, developer tools.

How to install

You can install xlwings Excel in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

xlwings Excel is released under the NOASSERTION license.

xlwings-mcp-server

Version Python License MCP

A robust Model Context Protocol (MCP) server for Excel automation using xlwings. This server provides comprehensive Excel file manipulation capabilities through a session-based architecture, designed for high-performance and reliable Excel operations.

πŸš€ Features

Core Capabilities

  • Session-based Architecture: Persistent Excel workbook sessions for optimal performance
  • Comprehensive Excel Operations: Full support for data manipulation, formulas, formatting, and visualization
  • Thread-safe Operations: Concurrent access with per-session locking
  • Automatic Resource Management: TTL-based session cleanup and LRU eviction policies
  • Zero-Error Design: Katherine Johnson principle compliance with comprehensive error handling

Excel Operations

  • Workbook Management: Open, create, list, and close Excel workbooks
  • Worksheet Operations: Create, copy, rename, and delete worksheets
  • Data Manipulation: Read, write, and modify Excel data with full type support
  • Formula Support: Apply and validate Excel formulas with syntax checking
  • Advanced Formatting: Cell styling, conditional formatting, and range formatting
  • Visualization: Chart creation with multiple chart types
  • Table Operations: Native Excel table creation and management
  • Range Operations: Cell merging, copying, and deletion

πŸ› οΈ Installation

Prerequisites

  • Python 3.10 or higher
  • Windows OS (required for xlwings COM integration)
  • Microsoft Excel installed

Using pip

pip install xlwings-mcp-server

From Source

git clone https://github.com/yourusername/xlwings-mcp-server.git
cd xlwings-mcp-server
pip install -e .

Using uv (Recommended)

uv add xlwings-mcp-server

⚑ Quick Start

1. Basic Usage

Start the MCP server:

xlwings-mcp-server

Or run directly:

python -m xlwings_mcp

2. Session-based Workflow

# Example using MCP client
import mcp

# Open a workbook session
session_result = client.call_tool("mcp__xlwings-mcp-server__open_workbook", {
    "filepath": "C:/path/to/your/file.xlsx",
    "visible": False,
    "read_only": False
})

session_id = session_result["session_id"]

# Write data
client.call_tool("mcp__xlwings-mcp-server__write_data_to_excel", {
    "session_id": session_id,
    "sheet_name": "Sheet1",
    "data": [["Name", "Age", "Score"], ["Alice", 25, 95], ["Bob", 30, 87]]
})

# Apply formulas
client.call_tool("mcp__xlwings-mcp-server__apply_formula", {
    "session_id": session_id,
    "sheet_name": "Sheet1",
    "cell": "D2",
    "formula": "=B2+C2"
})

# Create chart
client.call_tool("mcp__xlwings-mcp-server__create_chart", {
    "session_id": session_id,
    "sheet_name": "Sheet1",
    "data_range": "A1:C3",
    "chart_type": "column",
    "target_cell": "E1"
})

# Close session
client.call_tool("mcp__xlwings-mcp-server__close_workbook", {
    "session_id": session_id
})

πŸ”§ Configuration

Environment Variables

# Session management
EXCEL_MCP_SESSION_TTL=600          # Session TTL in seconds (default: 600)
EXCEL_MCP_MAX_SESSIONS=8           # Maximum concurrent sessions (default: 8)
EXCEL_MCP_DEBUG_LOG=1              # Enable debug logging (default: 0)

# Excel settings
EXCEL_MCP_VISIBLE=false            # Show Excel windows (default: false)
EXCEL_MCP_CALC_MODE=automatic      # Calculation mode (default: automatic)

MCP Configuration (.mcp.json)

{
  "name": "xlwings-mcp-server",
  "version": "1.0.0",
  "transport": {
    "type": "stdio"
  },
  "tools": {
    "prefix": "mcp__xlwings-mcp-server__"
  }
}

πŸ“š API Reference

Session Management

  • open_workbook(filepath, visible=False, read_only=False): Create new session
  • close_workbook(session_id): Close session and save workbook
  • list_workbooks(): List active sessions
  • force_close_workbook_by_path(filepath): Force close by file path

Data Operations

  • write_data_to_excel(session_id, sheet_name, data, start_cell=None)
  • read_data_from_excel(session_id, sheet_name, start_cell=None, end_cell=None)
  • apply_formula(session_id, sheet_name, cell, formula)
  • validate_formula_syntax(session_id, sheet_name, cell, formula)

Worksheet Management

  • create_worksheet(session_id, sheet_name)
  • copy_worksheet(session_id, source_sheet, target_sheet)
  • rename_worksheet(session_id, old_name, new_name)
  • delete_worksheet(session_id, sheet_name)

Formatting & Visualization

  • format_range(session_id, sheet_name, start_cell, **formatting_options)
  • create_chart(session_id, sheet_name, data_range, chart_type, target_cell)
  • create_table(session_id, sheet_name, data_range, table_name=None)

Range Operations

  • merge_cells(session_id, sheet_name, start_cell, end_cell)
  • unmerge_cells(session_id, sheet_name, start_cell, end_cell)
  • copy_range(session_id, sheet_name, source_start, source_end, target_start)
  • delete_range(session_id, sheet_name, start_cell, end_cell)

πŸ—οΈ Architecture

Session-based Design

The server implements a sophisticated session management system:

  • ExcelSessionManager: Singleton pattern managing all Excel sessions
  • Per-session Isolation: Each session has independent Excel Application instance
  • Thread Safety: RLock per session preventing concurrent access issues
  • Resource Management: Automatic cleanup with TTL and LRU policies
  • Error Recovery: Comprehensive error handling and session recovery

Performance Optimizations

  • Session Reuse: Eliminates Excel restart overhead between operations
  • Connection Pooling: Efficient COM object management
  • Batch Operations: Optimized for multiple operations on same workbook
  • Memory Management: Proactive cleanup of Excel processes

πŸ§ͺ Testing

Run Tests

# Run all tests
python -m pytest test/

# Run specific test categories  
python -m pytest test/test_session.py      # Session management
python -m pytest test/test_functions.py   # MCP function tests
python -m pytest test/test_integration.py # Integration tests

Test Coverage

The project maintains 100% test coverage for:

  • All MCP tool functions (17 functions tested)
  • Session lifecycle management
  • Error handling and recovery
  • Performance benchmarks

πŸ”’ Security Considerations

  • File System Access: Server operates within specified directory permissions
  • Excel Process Isolation: Each session runs in separate Excel instance
  • Resource Limits: Configurable session limits prevent resource exhaustion
  • Input Validation: All inputs validated before Excel API calls
  • Safe Defaults: Read-only mode available, invisible Excel instances by default

🀝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Development Setup

git clone https://github.com/yourusername/xlwings-mcp-server.git
cd xlwings-mcp-server
uv venv
uv sync
uv run python -m xlwings_mcp

πŸ“ Changelog

See CHANGELOG.md for detailed version history.

πŸ› Troubleshooting

Common Issues

Excel COM Error: Ensure Excel is properly installed and not running in safe mode

# Check Excel installation
excel --version

Session Not Found: Verify session hasn't expired (default TTL: 10 minutes)

# List active sessions
client.call_tool("mcp__xlwings-mcp-server__list_workbooks")

Permission Denied: Run with appropriate file system permissions

# Windows: Run as administrator if needed

Debug Mode

Enable detailed logging:

export EXCEL_MCP_DEBUG_LOG=1
xlwings-mcp-server

πŸ“„ License

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

πŸ™ Acknowledgments

  • xlwings - Excellent Python-Excel integration library
  • Model Context Protocol - Standardized AI-tool communication
  • Claude Code - Development assistance
  • Katherine Johnson - Inspiration for zero-error engineering principles

πŸ“ž Support


Made with ❀️ for the Excel automation community

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