productivityanalytics-data

Excel File Processor

by zhiwei5576

Process Excel files efficiently: read sheet names, extract data, and cache workbooks for large files using tools like pd

Enables direct interaction with Excel files for reading sheet names, extracting data, and managing workbook caching to improve performance with large spreadsheets.

github stars

45

Built-in caching for large filesMulti-worksheet supportNo Excel installation required

best for

  • / Data analysts working with Excel spreadsheets
  • / Automating Excel report generation
  • / Converting between Excel and other data formats
  • / Processing large Excel files efficiently

capabilities

  • / Read worksheet names and data from Excel files
  • / Write data to new or existing Excel workbooks
  • / Analyze Excel file structure and metadata
  • / Cache file contents for faster repeated access
  • / Create multi-worksheet Excel files
  • / Export structural analysis to new files

what it does

Reads, writes, and analyzes Excel files directly without requiring external software. Includes caching to optimize performance with large spreadsheets.

about

Excel File Processor is a community-built MCP server published by zhiwei5576 that provides AI assistants with tools and capabilities via the Model Context Protocol. Process Excel files efficiently: read sheet names, extract data, and cache workbooks for large files using tools like pd It is categorized under productivity, analytics data.

how to install

You can install Excel File Processor 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

MIT

Excel File Processor is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Excel MCP Server

npm smithery badge 简体中文 | English

Excel file processing server based on Model Context Protocol (MCP), providing functionalities for reading, writing, and analyzing Excel files.

Features

  • 📖 Read Excel Files

    • Get worksheet list
    • Read specific worksheet data
    • Read all worksheets data
  • ✍️ Write Excel Files

    • Create new Excel files
    • Write to specific worksheet
    • Support multiple worksheets
  • 🔍 Analyze Excel Structure

    • Analyze worksheet structure
    • Export structure to new file
  • 💾 Cache Management

    • Automatic file content caching
    • Scheduled cache cleanup
    • Manual cache clearing
  • 📝 Log Management

    • Automatic operation logging
    • Periodic log cleanup

Installation

Installing via Smithery

To install excel-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @zhiwei5576/excel-mcp-server --client claude

Installing Manually

Installing via NPM excel-mcp-server can be automatically installed by adding the following configuration to the MCP servers configuration.

Windows Platform:

{
  "mcpServers": {
    "excel": {
        "command": "cmd",
        "args": ["/c", "npx", "--yes", "@zhiweixu/excel-mcp-server"],
        "env": {
            "LOG_PATH": "[set an accessible absolute path]",
            "CACHE_MAX_AGE": "1",
            "CACHE_CLEANUP_INTERVAL": "4",
            "LOG_RETENTION_DAYS": "7",
            "LOG_CLEANUP_INTERVAL": "24"
        }
    }
}

Other Platforms:

{
  "mcpServers": {
    "excel": {
        "command": "npx",
        "args": ["--yes", "@zhiweixu/excel-mcp-server"],
        "env": {
            "LOG_PATH": "[set an accessible absolute path]",
            "CACHE_MAX_AGE": "1",
            "CACHE_CLEANUP_INTERVAL": "4",
            "LOG_RETENTION_DAYS": "7",
            "LOG_CLEANUP_INTERVAL": "24"
        }
    }
}

Note: LOG_PATH is optional. If not set, logs will be stored in the 'logs' folder under the application root directory.other arguments are optional.

API Tools

Structure Tools

  1. analyzeExcelStructure

    • Function: Get Excel file structure including sheet list and column headers in JSON format
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file
      • headerRows: Number of header rows (default: 1)
  2. exportExcelStructure

    • Function: Export Excel file structure (sheets and headers) to a new Excel template file
    • Parameters:
      • sourceFilePath: Source Excel file path
      • targetFilePath: Target Excel file path
      • headerRows: Number of header rows (default: 1)

Read Tools

  1. readSheetNames

    • Function: Get all sheet names from the Excel file
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file
  2. readDataBySheetName

    • Function: Get data from a specific sheet in the Excel file
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file
      • sheetName: Name of the sheet to read
      • headerRow: Header row number (default: 1)
      • dataStartRow: Data start row number (default: 2)
  3. readSheetData

    • Function: Get data from all sheets in the Excel file
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file
      • headerRow: Header row number (default: 1)
      • dataStartRow: Data start row number (default: 2)

Write Tools

  1. writeDataBySheetName

    • Function: Write data to a specific sheet in the Excel file (overwrites if sheet exists)
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file
      • sheetName: Name of the sheet to write
      • data: Array of data to write
  2. writeSheetData

    • Function: Create a new Excel file with provided data
    • Parameters:
      • fileAbsolutePath: Absolute path for the new Excel file
      • data: Object containing multiple sheet data

Cache Tools

  1. clearFileCache
    • Function: Clear cached data for the specified Excel file
    • Parameters:
      • fileAbsolutePath: Absolute path of the Excel file to clear from cache

Configuration

Environment Variables

  • LOG_PATH: Log files storage path

    • Optional
    • Default: 'logs' folder under application root directory
  • CACHE_MAX_AGE: Cache expiration time (hours)

    • Optional
    • Default: 1
  • CACHE_CLEANUP_INTERVAL: Cache cleanup interval (hours)

    • Optional
    • Default: 4
  • LOG_RETENTION_DAYS: Log retention days

    • Optional
    • Default: 7
  • LOG_CLEANUP_INTERVAL: Log cleanup interval (hours)

    • Optional
    • Default: 24

Default Configuration

  • Cache Configuration

    • Cache expiration time: 1 hour
    • Cache cleanup interval: 4 hours
  • Log Configuration

    • Log retention days: 7 days
    • Cleanup interval: 24 hours

Dependencies

  • @modelcontextprotocol/sdk: ^1.7.0
  • xlsx: ^0.18.5
  • typescript: ^5.8.2

Development Dependencies

  • @types/node: ^22.13.10
  • nodemon: ^3.1.9
  • ts-node: ^10.9.2

License

This project is licensed under the MIT License. This means you are free to:

  • Use the software for commercial or non-commercial purposes

  • Modify the source code

  • Distribute original or modified code Requirements:

  • Retain the original copyright notice

  • No liability can be claimed against the authors for software use For detailed license information,please see the LICENSE file.

FAQ

What is the Excel File Processor MCP server?
Excel File Processor is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Excel File Processor?
This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
MCP server reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    Excel File Processor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Piyush G· Sep 9, 2024

    We evaluated Excel File Processor against two servers with overlapping tools; this profile had the clearer scope statement.

  • Chaitanya Patil· Aug 8, 2024

    Useful MCP listing: Excel File Processor is the kind of server we cite when onboarding engineers to host + tool permissions.

  • Sakshi Patil· Jul 7, 2024

    Excel File Processor reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Ganesh Mohane· Jun 6, 2024

    I recommend Excel File Processor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Oshnikdeep· May 5, 2024

    Strong directory entry: Excel File Processor surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Dhruvi Jain· Apr 4, 2024

    Excel File Processor has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Rahul Santra· Mar 3, 2024

    According to our notes, Excel File Processor benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Pratham Ware· Feb 2, 2024

    We wired Excel File Processor into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Yash Thakker· Jan 1, 2024

    Excel File Processor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.