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Ishay Almuly

Ishay Almuly

Local
github.com/ishayoyoData & Analytics38Updated 10w ago

About Ishay Almuly

Excel MCP Server is an MCP server for Excel and CSV files, exposing 37 tools for reading, writing, analysis and financial modeling. It installs via npm and connects to clients such as Claude Code, Claude Desktop and Cursor, with optional AI providers for certain tools.

Key features

  1. 0137 tools for reading, writing and analysis
  2. 02Supports .csv, .xlsx and .xls files
  3. 03Chunked reading for large files
  4. 04DCF, budget variance and ratio analysis
  5. 05CSV formula injection guard, enabled by default
  6. 06Optional workspace directory to restrict file access

Use cases

  1. 01Summarizing and filtering sales or performance spreadsheets
  2. 02Removing duplicates and fixing formatting in datasets
  3. 03Running cross-file lookups and consistency checks

MCP support

This project is an MCP server that exposes spreadsheet read, write, analysis and financial tools to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Excel MCP Server

MCP server that gives Claude full read/write/analyze power over Excel and CSV files. 37 tools — from basic cell reads to financial modeling.

Install

Option 1: npm (Recommended)
npm install -g excel-csv-mcp-server

Then add to your MCP client:

Claude Code:

claude mcp remove excel-csv  # if previously added
claude mcp add excel-csv --transport stdio excel-csv-mcp-server

Claude Desktop / Cursor — add to your MCP config (claude_desktop_config.json or Cursor's mcp.json):

{
  "mcpServers": {
    "excel-csv": {
      "command": "excel-csv-mcp-server"
    }
  }
}
Option 2: npx (No Install)

No global install needed — runs directly:

Claude Code:

claude mcp add excel-csv stdio npx -- excel-csv-mcp-server

Claude Desktop / Cursor:

{
  "mcpServers": {
    "excel-csv": {
      "command": "npx",
      "args": ["-y", "excel-csv-mcp-server"]
    }
  }
}
Option 3: From Source
git clone https://github.com/ishayoyo/excel-mcp.git
cd excel-mcp
npm install
npm run build

Claude Code:

claude mcp add excel-csv stdio node /path/to/excel-mcp/dist/index.js

Claude Desktop / Cursor:

{
  "mcpServers": {
    "excel-csv": {
      "command": "node",
      "args": ["/path/to/excel-mcp/dist/index.js"]
    }
  }
}

What It Can Do

CategoryToolsExamples
Read & Navigateread_file, get_cell, get_range, get_headers, search, filter_rows, aggregateRead files, search values, filter rows, sum columns
Large Filesread_file_chunked, get_file_infoStream 100MB+ files in chunks
Write & Formatwrite_file, add_sheet, write_multi_sheet, export_analysis, format_cells, auto_fit_columnsCreate Excel/CSV, multi-sheet with formulas, style cells
Analyticsstatistical_analysis, correlation_analysis, data_profile, pivot_tableStats, correlations, profiling, pivot tables
Financialdcf_analysis, budget_variance_analysis, ratio_analysis, scenario_modeling, trend_analysisDCF valuation, budget vs actual, financial ratios, what-if scenarios
Data Cleaningfind_duplicates, data_cleaner, vlookup_helperRemove duplicates, fix dates/phones/names, cross-file lookups
Bulk Opsbulk_aggregate_multi_files, bulk_filter_multi_filesAggregate/filter across multiple files
Validationvalidate_data_consistencyCross-file referential integrity checks
AI-Poweredevaluate_formula, parse_natural_language, explain_formula, smart_data_analysis, ai_provider_statusEvaluate formulas, natural language to formula, AI analysis

AI Providers (Optional)

For AI-powered tools (parse_natural_language, explain_formula, smart_data_analysis), create a .env file:

cp .env.example .env
ANTHROPIC_API_KEY=your-key
OPENAI_API_KEY=your-key
DEEPSEEK_API_KEY=your-key
GEMINI_API_KEY=your-key

Any single provider is enough. A local fallback works without any keys.

Data leaves your machine when a provider key is set. The AI tools send the spreadsheet content they are analysing to whichever provider you configured (Anthropic, OpenAI, DeepSeek, or Gemini). Leave the keys unset to keep every operation local -- the built-in fallback provider makes no network calls.

Security

The server reads and writes only .csv, .xlsx, and .xls files, and runs over stdio as a local process with your own user's permissions.

Restricting file access

By default any path you name is allowed, because opening a spreadsheet anywhere on your disk is the point of the tool. If you expose the server to callers you do not fully trust -- or want a guardrail against a malicious spreadsheet talking the model into writing somewhere unexpected -- confine it to one directory:

EXCEL_MCP_WORKSPACE_ROOT=/path/to/your/data

Every read and write then resolves inside that directory, and anything escaping it is rejected. Unset the variable to restore the default behaviour.

Note that containment is checked after the path is resolved, so .. traversal is handled, but symlinks are not followed: a symlink inside the root that points outside it will still resolve. Avoid placing untrusted symlinks in the workspace.

CSV formula injection

Spreadsheet applications evaluate a cell beginning with =, +, -, @, tab, or carriage return as a formula. When writing CSV, this server prefixes such values with a single quote so they stay literal text (CWE-1236). Plain numbers like -5 and +1.5 are recognised and left alone, so numeric data round-trips unchanged.

This guard is on by default. To emit raw values instead:

EXCEL_MCP_CSV_FORMULA_GUARD=off

Excel output is unaffected -- .xlsx cells are written as typed strings, which are never evaluated as formulas.

License

MIT

Comments

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