Navigation
OpenPyXL_MCP_Server: MCP Integration & AI-Driven Excel Automation - MCP Implementation

OpenPyXL_MCP_Server: MCP Integration & AI-Driven Excel Automation

Empower developers to expose Excel data to MCP clients like Claude via this streamlined OpenPyXL wrapper, enabling seamless AI-driven workflows.

Developer Tools
4.1(13 reviews)
19 saves
9 comments

Users create an average of 55 projects per month with this tool

About OpenPyXL_MCP_Server

What is OpenPyXL_MCP_Server: MCP Integration & AI-Driven Excel Automation?

OpenPyXL_MCP_Server is a specialized tool designed to integrate Microsoft Cognitive Services (MCP) with Excel automation, enabling AI-driven analysis and manipulation of spreadsheet data. It leverages machine learning capabilities to interpret user queries, navigate complex datasets, and perform tasks such as data extraction, form population, and compliance validation directly within Excel workbooks. The server acts as an intermediary between AI platforms and Excel files, streamlining workflows for government reporting, financial management, and data-driven decision-making.

How to Use OpenPyXL_MCP_Server: MCP Integration & AI-Driven Excel Automation?

To utilize the server, users must first install the package via Python dependencies and configure integration with their preferred AI platform (e.g., Microsoft Azure). After deploying the server, Excel files can be analyzed through API requests or user prompts, with the server dynamically querying spreadsheet content to generate contextual responses. Configuration involves setting up file paths, authentication for AI services, and defining access controls for sensitive datasets.

Installation Steps

  • Install required Python packages listed in requirements.txt
  • Configure MCP service credentials in environment variables
  • Deploy the server using pyinstaller for standalone executables
  • Test connectivity with sample Excel files and AI query interfaces

OpenPyXL_MCP_Server Features

Key Features of OpenPyXL_MCP_Server

  • MCP Integration: Directly interfaces with AI models to interpret user intent and automate spreadsheet tasks
  • Format Compatibility: Supports .xlsx, .xls, and modern Excel macros for diverse dataset handling
  • Contextual Analysis: Identifies key cells, tables, and form sections through AI-driven pattern recognition
  • Security Protocols: Implements role-based access controls and audit trails for sensitive government/financial data
  • Error Mitigation: Detects incomplete entries, conflicting data, and potential compliance issues during form population

Use Cases of OpenPyXL_MCP_Server

  • Government Reporting: Automates DPR973 form completion for California State Parks associations by identifying required fields and validating numerical entries
  • Financial Analysis: Analyzes federal property inventories to determine largest buildings by square footage while handling pagination and data overflow
  • Compliance Management: Validates HOA financial reports against planned vs actual figures, highlighting discrepancies in revenue streams
  • Data Discovery: Extracts key metrics from public datasets like the IOLP inventory for journalistic or policy analysis

OpenPyXL_MCP_Server FAQ

FAQ from OpenPyXL_MCP_Server

Q: What are the system requirements?

A: Requires Python 3.8+, 8GB RAM minimum, and compatible MCP service tier. Standalone builds available for Windows/macOS without Python dependency.

Q: How does it handle large datasets?

A: Implements incremental reading for files exceeding 10MB, with caching mechanisms to prevent context overflow errors. Users should split excessively large files into smaller workbooks.

Q: Can it modify Excel files directly?

A: Currently read-only for safety, though planned updates will allow controlled modifications via auditable workflows. Form population examples use metadata pointers rather than direct edits.

Q: Are there usage limits?

A: API calls are rate-limited based on MCP service plan. Free tier allows 100 queries/month, with enterprise plans for high-volume government/financial users.

Q: How is security ensured?

A: Implements AES-256 encryption for file transfers, role-based access controls, and GDPR-compliant data handling. Audit logs track all server interactions.

Content

openpyxl_mcp_server

What is this?

A thin wrapper around the OpenPyXl Python library that exposes some of its features as Model Context Protocol (MCP) server. This allows Claude and other MCP clients to fetch data from Excel files.

Related links:

Installation

General Steps

  1. Download the latest version of the executable from https://github.com/jonemo/openpyxl-mcp-server/releases. openpyxl_mcp_server is for MacOS, openpyxl_mcp_server.exe is for Windows.
  2. Configure your MCP Client. Most commonly this will be Claude Desktop, see instructions in next section.

Windows will try to talk you out of running a random executable downloaded from the internet. You will have to click "Keep" or "Keep anyway" in various places to convince it to not delete the file. The details of this depend on which browser you use and what your Windows Defender settings are.

Alternatively, if you don't trust my executables, you can also install the source version of the code directly from this repo. See the "From Source" section below.

Configuring Claude Desktop

Note that this only works with theClaude Desktop app, not with Claude running in the web browser.

  1. Have Claude Desktop installed.

  2. Have the MCP server executable downloaded (see previous section). This assumes that you have downloaded the executable to your Downloads folder. You can use any other folder, adjust the paths in the configuration below accordingly.

  3. In Claude Desktop, open the "Settings..." menu:

  4. Navigate to the "Developer" section of the settings.

  5. Click "Edit Config". This will create a config file for MCP servers if you didn't have one already. The default location of this file is:
    * macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    * Windows: %APPDATA%\Claude\claude_desktop_config.json

  6. On MacOS, add the following to your claude_desktop_config.json. Replace <YOUR-USERNAME> with your MacOS username. If you already use other MCP servers, you'll have to merge the JSON into the existing contents.

    {
    "mcpServers": {
    "inspect_excel_xlsx_file": {
    "command": "/Users//Downloads/openpyxl_mcp_server",
    "args": []
    }
    }

}
  1. On Windows, add the following to your claude_desktop_config.json. Replace <YOUR-USERNAME> with your MacOS username. If you already use other MCP servers, you'll have to merge the JSON into the existing contents.

    {
    "mcpServers": {
    "inspect_excel_xlsx_file": {
    "command": "C:\Users\\Downloads\openpyxl_mcp_server.exe",
    "args": []
    }
    }

}
  1. After updating your configuration file, you need to restart the Claude app for the changes to take effect. It is not enough to close the Claude app window. On Windows you must right click the Claude icon in your system tray and select "Quit". On macOS you can use Command+Q.

If you encounter problems, please consult these resources:

Configuring other MCP clients

Instructions for configuring MCP servers in other tools that support them:

From Source (for development)

This section only applies if you wish to modify the source code or if you do not trust the provided executables and prefer to run from source code.

git clone [[email protected]](/cdn-cgi/l/email-protection):jonemo/openpyxl-mcp-server.git
cd openpyxl-mcp-server
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Assuming you've cloned your repo to /Users/jonas/repos/openpyxl_mcp_server, the configuration file contents should now change to:

{
  "mcpServers": {
    "inspect_excel_xlsx_file": {
      "command": "/Users/jonas/repos/openpyxl_mcp_server/venv/bin/python",
      "args": ["/Users/jonas/repos/openpyxl_mcp_server/openpyxl_mcp_server.py"]
    }
  }
}

Example prompts

Example 1

Uses the file KimbroughEvelyn_A-5qg0_Dataset_20160624.xlsx from the "Near-Port Air Quality Assessment Utilizing a Mobile Monitoring Approach" dataset from https://catalog.data.gov/dataset/near-port-air-quality-assessment-utilizing-a-mobile-monitoring-approach

From a quick glance at description and file contents it wasn't obvious to me what ports this dataset is about. Let's ask Claude:

I have an Excel file in ~/Downloads/KimbroughEvelyn_A-5qg0_Dataset_20160624.xlsx that contains data associated with some study about air pollution near one or more ports in the United States. Can you infer from the file contents which ports are covered by this study?

https://claude.ai/share/d87f67a9-dbc0-4223-86ff-3b4c1f9fa2e7

After 11 calls to the MCP server, the response is:

Looking at the latitude and longitude coordinates from the Fig 2 sheet and combining this with the location information, I can infer that this study is focused on the Port of Charleston, South Carolina.

The coordinates in the dataset (approximately latitude 32.83 and longitude -79.87) correspond to the Charleston area, and the references to downtown, rail yard, and airport monitoring stations are consistent with air quality monitoring around a port city.

This dataset appears to contain air pollution measurements (PM2.5 and PM10) collected near the Port of Charleston, with comparisons between port locations and background/reference sites.

Example 2:

I'm the treasurer of a small 10-unit home owners association. Our book keeping happens in an Excel file in Google Sheets. The file has 9 sheets with nine sheets for things like the transactions list, members' dues accounts, quarterly reports.

The file contains non-public information, therefore this example only shows the prompt, a few key "insights", and the final answer:

~/Downloads/CASH FLOW 2024.xlsx are the finances of my home owner association. How much did we get billed for sprinkler system maintenance in 2024? How many transactions contributed to this total? When did each transaction happen?

[...]

I see a "Transactions" sheet that likely contains the detailed expense records. Let me search for "sprinkler" in this sheet to find relevant transactions:

[...]

Let me examine the YEAR 2024 summary sheet to see if sprinkler maintenance is listed as a category:

[...]

Great! I found "Sprinkler Maintenance" listed as a category in row 24 of the YEAR 2024 sheet. Now, let me check the actual transactions related to sprinkler maintenance:

[...]

Let me check more entries by searching specifically for "Sprinkler Maintenance" in the entire Transactions sheet:

[...]

Based on my analysis of your HOA's financial records in the "CASH FLOW 2024.xlsx" file, here's what I found about the sprinkler system maintenance expenses in 2024:

Total amount billed for sprinkler system maintenance in 2024: $565.00 Number of transactions: 1 transaction Transaction date: September 9, 2024

The expense appears as a single transaction in the Transactions sheet. The spreadsheet also contains a budgeted amount for sprinkler maintenance of $750.00 for the year > in the "YEAR 2024 Actuals vs Planned" sheet, with a note stating "Not received any invoices yet" (which may be outdated since there is now one invoice recorded). Would you like me to analyze any other aspects of your HOA's sprinkler maintenance expenses or other financial information from the spreadsheet?

True story. Our sprinkler guy only billed us for the one visit in the spring and forgot to send the bill for the work later in the year. Don't worry, he got paid but it's booked in 2025.

Example 3: Filling out a form

My Google searches for interesting Excel workbooks turned up form DPR 973 by the California Natural Resources Agency: https://www.parks.ca.gov/pages/22374/files/Annual%20Report%20DPR973.xls This appears to be a form that gets filled out by "associations" that support the California State Parks. To be clear, I am not affiliated with such an association. But I converted the form from .xls format to .xlsx and asked Claude to help me fill it out:

I need to file DPR973 because I work for a "cooperating association" for California State Parks. The form I have to fill out is this Excel sheet: /Users/jonas/Downloads/Annual Report DPR973.xlsx. We supported the State Parks by publishing books and generated revenue by selling firewood. Where in the workbook do I have to fill out cells?

After 11 calls to the tool the response seems correct, although I don't understand why Claude did not look at the remaining sheets at all:

Based on my examination of the DPR973 form, I'll now provide guidance on where you need to fill out cells for your cooperating association that publishes books and sells firewood:

  1. Page 1 :
* You'll need to fill out the Association Information (Part I) with your organization's details (name, address, contact information)
* Update the year in cell C4 to the current reporting year
  1. Page 2 (A) - This is where you'll record your sales information:
* For your book sales (which would be considered interpretive/educational):

  * Line 1 (Cell F22): Gross Sales - Materials (for your published books)
  * Line 2 (Cell F23): Any returns or refunds
  * Line 3 (Cell F24): Cost of Goods Sold for the books
* For your firewood sales:

  * Line 23 (Cell F51): Gross Sales - Firewood
  * Line 24 (Cell F52): Any refunds/returned/damaged firewood
  * Line 25 (Cell F53): Cost of Goods Sold for firewood
* The form will automatically calculate totals in cells F25 (book profits), F54 (firewood profits), and F58 (total net profits)
  1. Page 3 - Financial Summary:
* Your sales figures will automatically populate from Page 2(A) into:

  * Line 6 (Cell F11): Total gross sales
  * Line 7 (Cell F12): Total cost of goods/services + returns/refunds
  * Line 8 (Cell H13): Net profits for all materials and services
* You'll need to manually enter:

  * Any donations/contributions (Line 1, Cell F6)
  * Membership dues if applicable (Line 4, Cell H9)
  * Interest/investment income if any (Line 5, Cell H10)
  * Fundraising information if applicable (Lines 9-11)
  * Other income if applicable (Line 12, Cell H17)
* For expenses:

  * Line 15 (Cell F21): Any direct grants to California State Parks
  * Line 16 (Cell F22): Interpretive program support expenses
  * Line 17 (Cell F23): Other CSP program support
  * Line 19 (Cell H25): Management and general expenses
* For assets/liabilities:

  * Line 22 (Cell F30): Total assets
  * Line 23 (Cell H31): Total liabilities
  * Lines 24-26 (Cells F32-F34): Net assets by restriction type
  1. Page 4 (not fully examined but likely contains):
* Additional notes, explanations, and signatures

For your specific activities (book publishing and firewood sales), focus on accurately completing:

  1. The Interpretive and Educational Sales section on Page 2(A) for your book sales
  2. The Firewood Sales section on Page 2(A) for your firewood revenue
  3. The complete financial summary on Page 3

Would you like me to explain any specific section in more detail?

Example 4

This uses the file 2025-3-7-iolp-buildings.xlsx from the Inventory of Owned and Leased Properties (IOLP) dataset available at https://catalog.data.gov/dataset/inventory-of-owned-and-leased-properties-iolp If you've followed the news in recent weeks you will know why this is currently the most popular dataset on data.gov.

Prompt:

Using the Excel file in "/Users/jonas/Downloads/2025-3-7-iolp-buildings.xlsx": What is the largest federal building by square footage in the state of Utah?

I used this file and prompt repeatedly as test case and got mixed results:

  • Chats that terminated without a response because they had reached the context limit. This happened when Claude got into a loop of querying many rows one at a time.
  • Incorrect answers because Claude made "bad assumptions" along the way. For example in this chat it decides that the largest building must be in Salt Lake City and starts to search the spreadsheet for arbitrary terms.
  • Correct answers, for example this chat: The IRS Service Center in Ogden is the largest federally-owned building in Utah on the list.

Footnote: The IRS Service Center is correct insofar that it is the largest building on the list. The "Bumblehive" aka "Utah Data Center" aka "Intelligence Community Comprehensive National Cybersecurity Initiative Data Center" is almost certainly larger but is not included in the file.

Contributing and Development

Building standalone executables

To create standalone executables that don't require Python installation:

  1. Make sure you have all dependencies installed:

    pip install -r requirements.txt

pip install -r requirements-dev.txt
  1. Build the executable:

    pyinstaller openpyxl_mcp_server.spec

The executable will be created in the dist directory. On Windows, it will be named openpyxl_mcp_server.exe. On macOS, it will be named openpyxl_mcp_server.

Note: When building on macOS, you might need to sign the executable for it to run properly. You can do this with:

codesign --force --deep --sign - dist/openpyxl_mcp_server

MCP Server Directories

openpyxl-mcp-server is currently listed in these MCP server directories:

Related MCP Servers & Clients