Excel/CSV MCP Server

Read, analyze, and manipulate data in Excel (XLSX, XLS) and CSV files with advanced filtering and analytics.

GitHub

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.

License

MIT

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