# 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)
```bash
npm install -g excel-csv-mcp-server
```
Then add to your MCP client:
**Claude Code:**
```bash
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`):
```json
{
"mcpServers": {
"excel-csv": {
"command": "excel-csv-mcp-server"
}
}
}
```
### Option 2: npx (No Install)
No global install needed — runs directly:
**Claude Code:**
```bash
claude mcp add excel-csv stdio npx -- excel-csv-mcp-server
```
**Claude Desktop / Cursor:**
```json
{
"mcpServers": {
"excel-csv": {
"command": "npx",
"args": ["-y", "excel-csv-mcp-server"]
}
}
}
```
### Option 3: From Source
```bash
git clone https://github.com/ishayoyo/excel-mcp.git
cd excel-mcp
npm install
npm run build
```
**Claude Code:**
```bash
claude mcp add excel-csv stdio node /path/to/excel-mcp/dist/index.js
```
**Claude Desktop / Cursor:**
```json
{
"mcpServers": {
"excel-csv": {
"command": "node",
"args": ["/path/to/excel-mcp/dist/index.js"]
}
}
}
```
## What It Can Do
| Category | Tools | Examples |
|----------|-------|---------|
| **Read & Navigate** | `read_file`, `get_cell`, `get_range`, `get_headers`, `search`, `filter_rows`, `aggregate` | Read files, search values, filter rows, sum columns |
| **Large Files** | `read_file_chunked`, `get_file_info` | Stream 100MB+ files in chunks |
| **Write & Format** | `write_file`, `add_sheet`, `write_multi_sheet`, `export_analysis`, `format_cells`, `auto_fit_columns` | Create Excel/CSV, multi-sheet with formulas, style cells |
| **Analytics** | `statistical_analysis`, `correlation_analysis`, `data_profile`, `pivot_table` | Stats, correlations, profiling, pivot tables |
| **Financial** | `dcf_analysis`, `budget_variance_analysis`, `ratio_analysis`, `scenario_modeling`, `trend_analysis` | DCF valuation, budget vs actual, financial ratios, what-if scenarios |
| **Data Cleaning** | `find_duplicates`, `data_cleaner`, `vlookup_helper` | Remove duplicates, fix dates/phones/names, cross-file lookups |
| **Bulk Ops** | `bulk_aggregate_multi_files`, `bulk_filter_multi_files` | Aggregate/filter across multiple files |
| **Validation** | `validate_data_consistency` | Cross-file referential integrity checks |
| **AI-Powered** | `evaluate_formula`, `parse_natural_language`, `explain_formula`, `smart_data_analysis`, `ai_provider_status` | Evaluate 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:
```bash
cp .env.example .env
```
```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
