Excel MCP Server
An MCP server that brings Excel/CSV data analysis capabilities to Claude, with a custom-built formula engine and AI-powered features.
What makes this different: The world's first conversational data analysis MCP server powered by HyperFormula (395 Excel functions) + multi-provider AI. Ask questions in natural language and get instant insights from your Excel/CSV files. Built for analysts who want AI-powered conversations with their data, not just spreadsheet manipulation.
How It Works
This server acts as a bridge between Claude and your data files, providing:
-
Formula Engine: A complete Excel-compatible formula parser and evaluator built from scratch, supporting 82 functions with proper operator precedence and dependency tracking.
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Data Operations: Direct read/write access to CSV and Excel files with intelligent parsing and type detection.
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AI Integration: Multi-provider AI support that intelligently routes requests to the best available AI service for natural language processing and formula generation.
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Bulk Processing: Parallel operations across multiple files for improved performance on large datasets.
Features
- 395 Excel functions via HyperFormula (battle-tested library)
- AI-powered natural language data queries
- Multi-provider AI support (Anthropic, OpenAI, DeepSeek, Gemini)
- Large file support with intelligent chunking for files >100MB
- Bulk operations across multiple files (3x faster)
- Smart data validation and consistency checking
- Advanced statistical analysis and data profiling
- Formula evaluation with dependency tracking
- Pivot tables and aggregation
- Cross-file referential integrity validation
- Excel styling and formatting with auto-fitting columns and cell formatting
🏢 CFO-Level Financial Analysis
- DCF Valuation Models - Complete discounted cash flow analysis with NPV, IRR, terminal value
- Financial Ratio Analysis - Comprehensive ratios with industry benchmarks (liquidity, profitability, leverage)
- Budget Variance Analysis - Automated budget vs actual comparisons with variance reporting
- Scenario Modeling - What-if analysis with multiple assumption scenarios
- Financial Functions - NPV, IRR, PMT, FV, PV, RATE, depreciation schedules, and more
- Industry Benchmarking - Automatic comparison against industry standards
Installation
git clone https://github.com/ishayoyo/excel-mcp.git
cd excel-mcp
npm install
npm run build
Claude Code Setup
Option 1: Direct MCP Configuration
# Add to Claude Code
claude mcp add excel-csv "node" "C:/path/to/excel-mcp/dist/index.js"
Option 2: Global Install
npm install -g .
# Then configure in Claude Code with:
# Command: npx
# Args: -y excel-csv-mcp
Cursor Claude Desktop Setup
Option 1: Direct MCP Configuration
Edit your Cursor MCP configuration file (%APPDATA%\Cursor\mcp.json on Windows, ~/Library/Application Support/Cursor/mcp.json on macOS):
{
"mcpServers": {
"excel-csv": {
"command": "node",
"args": ["C:/path/to/excel-mcp/dist/index.js"]
}
}
}
Replace C:/path/to/excel-mcp/dist/index.js with the actual path to your built dist/index.js file.
Option 2: Using npx (Recommended)
{
"mcpServers": {
"excel-csv": {
"command": "npx",
"args": ["-y", "excel-csv-mcp"]
}
}
}
This requires a global npm install:
npm install -g .
AI Providers
Create a .env file with your API keys:
cp .env.example .env
ANTHROPIC_API_KEY=your-key-here
OPENAI_API_KEY=your-key-here
DEEPSEEK_API_KEY=your-key-here
GEMINI_API_KEY=your-key-here
Supported providers: Anthropic, OpenAI, DeepSeek, Gemini, Local fallback
Usage Examples
Ask questions in natural language:
- "What's the total revenue in sales_data.csv?"
- "Sum all sales where region is 'North'"
- "Find duplicates in customer_data.xlsx"
- "Clean messy customer data - fix phone numbers and names"
- "Remove duplicate rows from my contact list"
- "Help me VLOOKUP customer details between two files"
- "Generate a formula to calculate average of last 30 days"
- "Validate data consistency between sales.xlsx and branches.xlsx"
- "Create a pivot table by department and export to report.xlsx"
- "Analyze this 500MB dataset in chunks to avoid memory issues"
- "Get file info and optimal chunk size for large_dataset.csv"
Available Tools
Core Operations
read_file- Read CSV/Excel files (supports offset/limit for large files)read_file_chunked- Stream large files in manageable chunks to avoid memory limitsget_file_info- Analyze file size and get chunking recommendations for large datasetsget_cell/get_range- Access specific cells or rangessearch/filter_rows- Find and filter dataaggregate- SUM, AVG, COUNT, MIN, MAX operations
Excel Workflow Tools (NEW)
find_duplicates- Smart duplicate detection and removal with multiple strategiesdata_cleaner- Batch data cleaning operations (trim whitespace, fix phones, standardize names, etc.)vlookup_helper- Intelligent VLOOKUP setup with fuzzy matching and error handling
Bulk Operations
bulk_aggregate_multi_files- Aggregate across multiple files (3x faster)bulk_filter_multi_files- Filter multiple files simultaneously
Formula Engine
evaluate_formula- Execute Excel formulasparse_natural_language- Convert text to formulasexplain_formula- Explain formula functionality
Analytics
statistical_analysis- Comprehensive statisticscorrelation_analysis- Find relationships between columnsdata_profile- Complete data profilingpivot_table- Group and aggregate data
AI Features
smart_data_analysis- AI-powered analysis suggestionsai_provider_status- Check AI provider availability
Styling & Formatting
format_cells- Apply fonts, colors, borders, alignment to Excel cellsauto_fit_columns- Automatically adjust column widths to fit contentwrite_multi_sheet- Create complex Excel files with formulas and formatting
Validation & Export
validate_data_consistency- Cross-file data integrity checkswrite_file/export_analysis- Create and export files
Key Features
🤖 AI-Powered Intelligence
- Ask "What's the correlation between sales and marketing spend?" → Gets instant statistical analysis
- Say "Find all customers who spent over $1000 last quarter" → AI generates complex formulas automatically
- Request "Explain what this VLOOKUP formula does" → Gets plain English explanation
⚡ Bulk Data Processing
- "Sum total revenue across 10 quarterly files" → Processes in parallel (3x faster than manual)
- "Find all employees with 'Manager' in their title across 5 HR spreadsheets" → Multi-file search
- "Aggregate sales data from Q1, Q2, Q3, Q4 files into one report" → Automated consolidation
🧮 Programmatic Formula Engine
- Evaluates
=SUMIFS(C:C, A:A, ">=1/1/2024")without Excel installed - Computes complex nested formulas with proper precedence
- Handles circular references and dependency tracking
- 82 functions implemented programmatically
📊 Advanced Analytics
- Comprehensive statistical profiling of every column
- Correlation analysis between any numeric columns
- Smart data quality validation across multiple files
- Automated outlier detection and data consistency checks
🔍 Smart Cross-File Operations
- "Validate that all customer IDs in sales.xlsx exist in customers.xlsx"
- "Check for duplicate emails across 3 contact lists"
- "Find missing data between related spreadsheets"
- Referential integrity validation (like database foreign keys but for spreadsheets)
🎯 Natural Language Data Conversations
- "Show me the top 10 products by revenue" → AI understands intent and executes
- "Calculate average order value for customers from California" → Generates optimal query
- "Create a summary of sales trends by month" → Suggests best analysis approach
📈 Large File Processing (NEW)
- Intelligent Chunking: Automatically handles files >100MB without memory errors
- Smart Recommendations:
get_file_infoanalyzes files and suggests optimal chunk sizes - Seamless Navigation: Read any chunk with proper headers and metadata
- Memory Efficient: Constant memory usage regardless of file size (tested up to 1M+ rows)
- Progress Tracking: Chunk navigation with hasNext/hasPrevious indicators
Why This Approach Matters
Traditional Excel tools focus on file manipulation - reading, writing, formatting. They treat spreadsheets as static documents.
This server treats your data as a dynamic knowledge base you can have conversations with. It's not about pretty formatting - it's about CFO-level financial modeling, strategic analysis, and executive decision-making powered by AI.
Built for CFOs, financial analysts, and executives who need: 💰 DCF valuations and investment analysis 📊 Financial ratio analysis with benchmarks 🎯 Scenario planning and risk modeling 💼 Budget variance tracking and reporting 🤖 AI-powered financial insights at conversational speed
License
MIT