What is Mcp Excel Reader Server

mcp-excel-reader-server is a Model Context Protocol (MCP) server designed for reading Excel (xlsx) files efficiently.

Use cases

Use cases include extracting data for analysis, automating report generation, and integrating Excel data into web applications.

How to use

To use mcp-excel-reader-server, install it via pip or uv, and then utilize its three main functions: read_excel, read_excel_by_sheet_name, and read_excel_by_sheet_index to read data from Excel files.

Key features

Key features include reading content from all sheets, specific sheets by name or index, returning data in JSON format, handling empty cells, and converting data types.

Where to use

mcp-excel-reader-server can be used in data analysis, reporting, and any application that requires reading and processing Excel files.

Excel Reader Server

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files.

Features

• Read content from all sheets in an Excel file
• Read content from a specific sheet by name
• Read content from a specific sheet by index
• Returns data in JSON format
• Handles empty cells and data type conversions

Installation

Requires Python 3.10 or higher.

# Using pip
pip install excel-reader-server

# Using uv (recommended)
uv pip install excel-reader-server

Dependencies

• mcp >= 1.2.1
• openpyxl >= 3.1.5

Usage

The server provides three main tools:

1. read_excel

Reads content from all sheets in an Excel file.

{
  "file_path": "path/to/your/excel/file.xlsx"
}

2. read_excel_by_sheet_name

Reads content from a specific sheet by name. If no sheet name is provided, reads the first sheet.

{
  "file_path": "path/to/your/excel/file.xlsx",
  "sheet_name": "Sheet1"  # optional
}

3. read_excel_by_sheet_index

Reads content from a specific sheet by index. If no index is provided, reads the first sheet (index 0).

{
  "file_path": "path/to/your/excel/file.xlsx",
  "sheet_index": 0  # optional
}

Response Format

The server returns data in the following JSON format:

{
  "Sheet1": [
    [
      "Header1",
      "Header2",
      "Header3"
    ],
    [
      "Value1",
      "Value2",
      "Value3"
    ],
    [
      "Value4",
      "Value5",
      "Value6"
    ]
  ]
}

• Each sheet is represented as a key in the top-level object
• Sheet data is an array of arrays, where each inner array represents a row
• All values are converted to strings
• Empty cells are represented as empty strings

Error Handling

The server provides clear error messages for common issues:

• File not found
• Invalid sheet name
• Index out of range
• General Excel file reading errors

License

This project is released under the Apache 2 License. See the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.