Excel/CSV MCP Server

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

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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