by zhiwei5576
Process Excel files efficiently: read sheet names, extract data, and cache workbooks for large files using tools like pd
Reads, writes, and analyzes Excel files directly without requiring external software. Includes caching to optimize performance with large spreadsheets.
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.
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.
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.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Excel File Processor benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Excel File Processor has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
I recommend Excel File Processor for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, Excel File Processor benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Strong directory entry: Excel File Processor surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Excel File Processor is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We wired Excel File Processor into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Excel File Processor is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated Excel File Processor against two servers with overlapping tools; this profile had the clearer scope statement.
Excel File Processor reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
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简体中文 | English
Excel file processing server based on Model Context Protocol (MCP), providing functionalities for reading, writing, and analyzing Excel files.
📖 Read Excel Files
✍️ Write Excel Files
🔍 Analyze Excel Structure
💾 Cache Management
📝 Log Management
To install excel-mcp-server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @zhiwei5576/excel-mcp-server --client claude
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.
analyzeExcelStructure
exportExcelStructure
readSheetNames
readDataBySheetName
readSheetData
writeDataBySheetName
writeSheetData
LOG_PATH: Log files storage path
CACHE_MAX_AGE: Cache expiration time (hours)
CACHE_CLEANUP_INTERVAL: Cache cleanup interval (hours)
LOG_RETENTION_DAYS: Log retention days
LOG_CLEANUP_INTERVAL: Log cleanup interval (hours)
Cache Configuration
Log Configuration
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.
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.