excel-mcp-server
Enables AI assistants to perform Excel file operations such as reading, writing, formatting, and chart creation through the Model Context Protocol.
README
Excel MCP Server
A comprehensive Model Context Protocol (MCP) server that provides Excel file manipulation capabilities. This project includes both a standalone Excel library and an MCP server that exposes Excel operations as tools for AI assistants like Claude.
โจ Features
๐ Excel Operations
- Read Excel Files: Extract data from .xlsx and .xls files with range and sheet selection
- Write Excel Files: Create new Excel files with structured data and headers
- Worksheet Management: Add, remove, and manage multiple worksheets
- Cell Operations: Update individual cells and ranges with values or formulas
- Formula Support: Apply and calculate Excel formulas including cross-sheet references
- Formatting: Apply styling, fonts, colors, and advanced formatting options
- Charts: Create various chart types (line, bar, pie, scatter) with customization
๐ง MCP Integration
- FastMCP Server: High-performance MCP server implementation using the official MCP SDK
- Resource Endpoints: Built-in help documentation and usage examples
- Tool Definitions: All Excel operations exposed as MCP tools with full type hints
- Error Handling: Comprehensive error reporting and logging throughout
๐ Quick Start
Prerequisites
- Python 3.8 or higher
- pip package manager
Installation
-
Clone the repository:
git clone https://github.com/amanarneja/XSpreadsheet.git cd XSpreadsheet -
Create a virtual environment:
python -m venv venv -
Activate the virtual environment:
# Windows venv\Scripts\activate # macOS/Linux source venv/bin/activate -
Install dependencies:
pip install -r requirements.txt
Usage
Running the MCP Server
cd src/excel_mcp_server
python server.py
The server will start and listen for MCP protocol messages on standard input/output.
Using the Excel Library
from src.excel_mcp_server.excel_library import ExcelLibrary
# Initialize the library
excel_lib = ExcelLibrary()
# Read an Excel file
data = excel_lib.read_excel_file("example.xlsx", "Sheet1")
# Write data to Excel
excel_lib.write_excel_file("output.xlsx", [
["Name", "Age", "City"],
["John", 30, "New York"],
["Jane", 25, "Boston"]
], headers=["Name", "Age", "City"])
Available MCP Tools
Core Operations
-
read_excel_file- Read data from Excel files
- Parameters:
file_path,sheet_name(optional),range(optional)
-
write_excel_file- Write data to Excel files
- Parameters:
file_path,data,sheet_name(optional),headers(optional)
-
get_worksheet_info- Get information about worksheets
- Parameters:
file_path
Worksheet Management
add_worksheet- Add new worksheets
- Parameters:
file_path,sheet_name
Cell Operations
-
update_cell- Update specific cells
- Parameters:
file_path,sheet_name,cell,value
-
apply_formula- Apply Excel formulas
- Parameters:
file_path,sheet_name,cell,formula
Formatting and Charts
-
format_cells- Apply cell formatting
- Parameters:
file_path,sheet_name,range,format_options
-
create_chart- Create charts and graphs
- Parameters:
file_path,sheet_name,data_range,chart_type,title(optional),position(optional)
MCP Resources
excel://help- Comprehensive help documentationexcel://examples- Usage examples and code snippets
Configuration
VS Code Integration
The project includes VS Code configuration for MCP debugging:
{
"servers": {
"excel-mcp-server": {
"type": "stdio",
"command": "python",
"args": ["src/excel_mcp_server/server.py"]
}
}
}
Claude Desktop Integration
To use with Claude Desktop, add this to your claude_desktop_config.json:
{
"mcpServers": {
"excel-mcp-server": {
"command": "python",
"args": ["path/to/XSpreadsheet/src/excel_mcp_server/server.py"],
"cwd": "path/to/XSpreadsheet"
}
}
}
Windows example:
{
"mcpServers": {
"excel-mcp-server": {
"command": "python",
"args": ["C:\\projects\\XSpreadsheet\\src\\excel_mcp_server\\server.py"],
"cwd": "C:\\projects\\XSpreadsheet"
}
}
}
Alternative: Module Execution
{
"mcpServers": {
"excel-mcp-server": {
"command": "python",
"args": ["-m", "src.excel_mcp_server.server"],
"cwd": "path/to/XSpreadsheet"
}
}
}
Project Structure
Xpreadsheet/
โโโ src/
โ โโโ excel_mcp_server/
โ โโโ __init__.py
โ โโโ server.py # MCP Server implementation
โ โโโ excel_library.py # Core Excel functionality
โโโ .vscode/
โ โโโ mcp.json # VS Code MCP configuration
โโโ .github/
โ โโโ copilot-instructions.md # Copilot development guidelines
โโโ requirements.txt # Python dependencies
โโโ README.md # This file
Dependencies
- mcp: Model Context Protocol SDK
- openpyxl: Excel file manipulation
- pandas: Data processing and analysis
- anyio: Async I/O support
Development
Adding New Features
- Excel Library: Add new methods to
excel_library.py - MCP Tools: Expose new methods as MCP tools in
server.py - Documentation: Update help resources and README
๐งช Testing & Demo
Run the Demo
python demo.py
This creates sample Excel files demonstrating all features.
Verify Installation
python verify.py
Test Individual Components
# Test the Excel library
python -c "from src.excel_mcp_server.excel_library import ExcelLibrary; print('โ
Library works!')"
# Test the MCP server (press Ctrl+C to stop)
python src/excel_mcp_server/server.py
๐ Usage Examples
Reading Excel Data with Claude
Once configured, you can ask Claude:
"Read the data from my sales.xlsx file, sheet called 'Q1 Data', range A1:D10"
Claude will use the read_excel_file tool:
{
"file_path": "sales.xlsx",
"sheet_name": "Q1 Data",
"range": "A1:D10"
}
Creating Charts with Claude
"Create a line chart from my data.xlsx file showing the sales trend. Use data from A1:B12 on the 'Sales' sheet"
Claude will use the create_chart tool:
{
"file_path": "data.xlsx",
"sheet_name": "Sales",
"data_range": "A1:B12",
"chart_type": "line",
"title": "Sales Trend"
}
Writing Excel Files
"Create a new Excel file called 'report.xlsx' with this data: [['Name', 'Score'], ['Alice', 95], ['Bob', 87]]"
Claude will use the write_excel_file tool:
{
"file_path": "report.xlsx",
"data": [["Alice", 95], ["Bob", 87]],
"headers": ["Name", "Score"]
}
๐ค Contributing
We welcome contributions! Here's how to get started:
- Fork the repository on GitHub
- Clone your fork locally:
git clone https://github.com/amanarneja/XSpreadsheet.git - Create a feature branch:
git checkout -b feature/amazing-feature - Make your changes and add tests
- Run the verification:
python verify.py python demo.py - Commit your changes:
git commit -m "Add amazing feature" - Push to your branch:
git push origin feature/amazing-feature - Open a Pull Request on GitHub
Development Guidelines
- Follow the existing code style and patterns
- Add type hints to all functions
- Include docstrings for new methods
- Update tests and documentation
- Ensure all demo scripts still work
๐ License
This project is licensed under the MIT License - see the LICENSE file for details.
๐ Support & Resources
- Issues: GitHub Issues
- MCP Documentation: Model Context Protocol
- Claude Desktop: Anthropic Claude
- Excel Library: Built with openpyxl
๐ Acknowledgments
- Built using the Model Context Protocol (MCP)
- Excel manipulation powered by openpyxl
- Data processing with pandas
๐ Ready to supercharge your Excel workflows with AI? Get started today!
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