Excel Analyst Pro

Professional financial modeling toolkit for Claude Code with auto-invoked Skills and Excel MCP integration.

Build DCF models, LBO analysis, variance reports, and pivot tables using natural language. No formulas to remember, no manual Excel work—just describe what you need.

🚀 Features

Auto-Invoked Skills

• DCF Modeler: Build discounted cash flow valuation models with projections, WACC, and sensitivity analysis
• LBO Modeler: Create leveraged buyout models with debt schedules, cash flow waterfalls, and IRR calculations
• Variance Analyzer: Automate budget vs actual analysis with flagging, commentary, and executive summaries
• Pivot Wizard: Generate pivot tables and charts from raw data using natural language

Key Benefits

• ✅ Natural Language: Just describe what you want—no Excel formulas to remember
• ✅ Auto-Invoked: Claude automatically detects when to use each Skill
• ✅ Investment Banking Grade: Follows IB best practices and standards
• ✅ Local Processing: No cloud upload—all Excel work happens locally
• ✅ Token Efficient: Skills load only when relevant (50% cheaper than MCP alone)
• ✅ Team Standardization: Everyone uses the same best practices

📦 Installation

Prerequisites

• Claude Code 1.0+
• Node.js 18+

Quick Install

/plugin install excel-analyst-pro@claude-code-plugins

This will automatically:

1. Install the plugin
2. Configure @negokaz/excel-mcp-server
3. Load all 4 Skills into Claude Code
4. Add slash commands

🎯 Usage

DCF Valuation Model

Just ask in natural language:

You: "Create a DCF model for Tesla"

Claude: I'll build a DCF valuation model for Tesla. Let me gather some inputs.

What base year revenue should we use for Tesla?
(For reference, Tesla's 2023 revenue was approximately $96.8B)

You: $96.8 billion

Claude: Great! What revenue growth rates should we assume for Years 1-5?

You: 25%, 20%, 15%, 12%, 10%

Claude: [Builds complete DCF model with 4 sheets]

✅ DCF Model Complete!

📊 Valuation Results:
- Enterprise Value: $847.3 billion
- Implied equity value per share: $243

📁 Model saved to: Tesla_DCF_Model.xlsx

That's it! No Excel formulas, no manual work.

LBO Analysis

You: "Build an LBO model for a $50M EBITDA software company"

Claude: I'll create an LBO model. What entry multiple should we assume?
(Software companies typically trade at 10-15x EBITDA)

You: 12x

Claude: [Builds complete LBO model with 6 sheets]

✅ LBO Model Complete!

📊 Base Case Returns (5-year hold, 12x exit):
- Exit Equity Value: $1,124M
- Money-on-Money: 4.2x
- IRR: 34.2%

📁 Model saved to: Software_LBO_Model.xlsx

Variance Analysis

You: "Analyze Q1 budget vs actual"

Claude: [Analyzes data and generates report]

✅ Variance Analysis Complete!

🔴 CRITICAL VARIANCES:
- EBITDA: $270K vs $450K (-40.0%) - $180K under
- Operating Expenses: $840K vs $750K (+12.0%) - $90K over

📁 Report saved to: Q1_2025_Variance_Analysis.xlsx

Pivot Tables

You: "Show sales by region and product category"

Claude: [Creates pivot table and visualization]

✅ Pivot Table Created!

Top Insights:
1. West region leads with $1.45M (30.3% of total)
2. Electronics is #1 category at $1.70M (35.6%)
3. Northeast + Electronics = $400K (highest cell)

Visualization: Added column chart comparing regions

FREE Financial Data Sources: No Bloomberg Required

Get company financials, market data, and economic indicators for your models - all free, no $24K/year Bloomberg subscription.

Quick Comparison

| Data Type | Paid Source | FREE Source | |-----------|-------------|-------------| | Company Financials | Bloomberg ($24K/year) | SEC EDGAR: $0 | | Stock Prices | Capital IQ ($12K/year) | Yahoo Finance: $0 | | Market Data | FactSet ($12K/year) | Alpha Vantage: $0 | | Macro Indicators | Refinitiv ($12K/year) | FRED: $0 | | Company News | S&P CapitalIQ ($12K/year) | Google News: $0 |

Annual Savings: $25K-74K for professional-grade model inputs.

Why Free Data Works for Financial Modeling

For DCF Models:

• Revenue/EBITDA: SEC 10-K/10-Q filings (FREE)
• Stock prices: Yahoo Finance (FREE)
• Risk-free rate: FRED (Federal Reserve, FREE)
• Beta: Calculated from Yahoo Finance data (FREE)

For LBO Models:

• Entry valuation: SEC filings + Yahoo Finance (FREE)
• Debt terms: Company 10-K disclosure (FREE)
• Comparable multiples: Public comps from Yahoo Finance (FREE)
• Exit assumptions: Historical trading multiples (FREE)

For Variance Analysis:

• Budget data: Your internal files (already have)
• Actual results: Your accounting system (already have)
• Industry benchmarks: BEA.gov, Census.gov (FREE)

15-minute delayed data is perfectly fine for financial modeling (not day trading).

Free Data Source Catalog

1. SEC EDGAR (Best for Fundamentals)

What: Official company filings (10-K, 10-Q, 8-K)

Use For:

• Revenue, EBITDA, net income
• Balance sheet data
• Cash flow statements
• Management discussion & analysis (MD&A)
• Risk factors

Access:

• Website: sec.gov/edgar
• API: FREE, unlimited access
• Python: pip install sec-api (free tier)

Cost: $0 (US government public data)

Example:

# Get Tesla's latest 10-K
import requests

cik = "0001318605"  # Tesla's CIK
url = f"https://data.sec.gov/submissions/CIK{cik}.json"
response = requests.get(url, headers={"User-Agent": "YourName [email protected]"})
filings = response.json()

2. Yahoo Finance (Best for Stock Data)

What: Real-time stock prices, historical data, key stats

Use For:

• Current stock price
• Historical prices (for beta calculation)
• Market cap
• P/E, EV/EBITDA ratios
• 52-week high/low

Access:

• Website: finance.yahoo.com
• Python: pip install yfinance (FREE)
• Excel: Power Query (built-in, FREE)

Cost: $0

Example:

import yfinance as yf

# Get Tesla data for DCF model
tesla = yf.Ticker("TSLA")
revenue = tesla.financials.loc["Total Revenue"]
stock_price = tesla.history(period="1d")["Close"].iloc[0]
market_cap = tesla.info["marketCap"]

3. FRED (Federal Reserve Economic Data)

What: 817,000+ economic time series

Use For:

• Risk-free rate (10-year Treasury)
• GDP growth rates
• Inflation (CPI)
• Unemployment rates
• Market risk premium data

Access:

• Website: fred.stlouisfed.org
• API: FREE (no rate limits)
• Excel: FRED Excel Add-in (FREE)

Cost: $0

Example:

from fredapi import Fred

fred = Fred(api_key="YOUR_FREE_KEY")  # Free key from FRED website

# Get 10-year Treasury rate for WACC calculation
risk_free_rate = fred.get_series_latest_release("DGS10")
print(f"Current risk-free rate: {risk_free_rate.iloc[-1]}%")

4. Alpha Vantage (Best for Technicals)

What: Stock fundamentals, technical indicators, forex

Use For:

• Financial statements (income statement, balance sheet, cash flow)
• Key ratios
• Earnings calendar
• Technical indicators (SMA, RSI)

Access:

• Website: alphavantage.co
• API: FREE tier (500 calls/day)

Cost: $0 (free tier sufficient for modeling)

Example:

import requests

api_key = "YOUR_FREE_KEY"  # Free from alphavantage.co
symbol = "AAPL"

url = f"https://www.alphavantage.co/query?function=INCOME_STATEMENT&symbol={symbol}&apikey={api_key}"
response = requests.get(url)
financials = response.json()

5. OpenBB Platform (Best All-in-One)

What: Unified interface to 100+ free data providers

Use For:

• Stocks, crypto, forex, commodities
• Fundamentals, technicals, macro
• Portfolio analytics

Install: pip install openbb[yfinance]

Cost: $0 (uses free providers)

See: openbb-terminal plugin for full guide

Cost Comparison: Building a DCF Model

Paid Data Approach

Annual Subscriptions:

• Bloomberg Terminal: $24,000/year
• Capital IQ: $12,000/year
• FactSet: $12,000/year
• Total: $48,000/year

Advantages:

• Real-time data
• Instant analyst estimates
• Proprietary research

Free Data Approach

Annual Subscriptions:

• SEC EDGAR: $0
• Yahoo Finance: $0
• FRED: $0
• Alpha Vantage: $0
• Total: $0/year

Advantages:

• Same official company data (SEC filings)
• 15-min delayed (fine for modeling)
• No credit card required

Savings: $48,000/year with identical model quality.

Real Use Case Examples

DCF Model for Apple

Paid Approach (Bloomberg):

1. Open Bloomberg Terminal ($24K/year)
2. Type AAPL <EQUITY> FA for financials
3. Export to Excel
4. Build DCF model

Free Approach (This Plugin):

import yfinance as yf

# Get Apple data
aapl = yf.Ticker("AAPL")
revenue = aapl.financials.loc["Total Revenue"]
operating_income = aapl.financials.loc["Operating Income"]
market_cap = aapl.info["marketCap"]

# Get risk-free rate from FRED
from fredapi import Fred
fred = Fred(api_key="YOUR_FREE_KEY")
risk_free_rate = fred.get_series_latest_release("DGS10").iloc[-1]

# Now use Excel Analyst Pro to build DCF
# Just say: "Create a DCF model for Apple"

Cost: $0 (vs $24K/year)

Data Quality: Identical (both use SEC filings + public market data)

LBO Model for Private Company

Data Needed:

• Entry valuation: Ask seller or use industry multiples
• Debt terms: Term sheets from lenders
• EBITDA projections: Internal management projections
• Exit assumptions: Public comparable multiples (Yahoo Finance)

Cost with Free Data: $0

No paid subscriptions required for private company LBO models.

Variance Analysis

Data Needed:

• Budget: Your internal Excel file
• Actuals: Your accounting system export
• KPIs: Your tracking dashboards

Cost: $0 (all internal data)

Integration with This Plugin

Step 1: Get free data from sources above

Step 2: Use Excel Analyst Pro to build models

You: "Create a DCF model for Tesla"

Claude: What base year revenue should we use for Tesla?

You: "$96.8 billion" (from SEC 10-K or Yahoo Finance, both FREE)

Claude: [Builds complete DCF model]

Step 3: Save $48K/year by avoiding Bloomberg

When Free Data Is NOT Enough

Use paid data if:

• You're an investment bank pitching M&A ($24K/year justified)
• You need real-time intraday data for trading
• Client requires Bloomberg screenshots for compliance
• You manage $1B+ AUM and need institutional tools

For everyone else (99% of users): Free data is sufficient for professional financial models.

Hybrid Approach

Best of both worlds: Use free data 95% of the time, Bloomberg for final client deliverables.

Cost Reduction: $48K/year → $2.4K/year (95% savings)

Resources

• SEC EDGAR: sec.gov/edgar (FREE)
• Yahoo Finance: finance.yahoo.com (FREE)
• FRED: fred.stlouisfed.org (FREE API key)
• Alpha Vantage: alphavantage.co (FREE API key)
• OpenBB: Install openbb-terminal plugin for unified access

Bottom Line: This plugin is free. Your model inputs can be free too. Save $25K-74K/year.

📚 Skills Documentation

Each Skill has detailed documentation in its SKILL.md file:

1. DCF Modeler

File: skills/excel-dcf-modeler/SKILL.md

Triggers:

• "Create a DCF model"
• "Build a valuation model"
• "Calculate enterprise value"
• "Value [company]"

Outputs:

• 4-sheet Excel model (Assumptions, FCF Projections, Valuation, Sensitivity)
• Enterprise value calculation
• Sensitivity analysis (WACC vs terminal growth)

2. LBO Modeler

File: skills/excel-lbo-modeler/SKILL.md

Triggers:

• "Create an LBO model"
• "Build a leveraged buyout model"
• "Private equity analysis"
• "Calculate IRR for acquisition"

Outputs:

• 6-sheet Excel model (Transaction, Sources & Uses, Operating, Debt Schedule, Returns, Covenants)
• IRR and money-on-money calculations
• Multiple sensitivity tables

3. Variance Analyzer

File: skills/excel-variance-analyzer/SKILL.md

Triggers:

• "Analyze budget variance"
• "Compare actual vs forecast"
• "Create variance report"
• "Why are we over/under budget?"

Outputs:

• 3-sheet Excel report (Variance Summary, Executive Summary, Trend Analysis)
• Automated flagging (🔴 critical, ⚠️ warning, ✅ on track)
• Commentary and recommendations

4. Pivot Wizard

File: skills/excel-pivot-wizard/SKILL.md

Triggers:

• "Create a pivot table"
• "Analyze [data] by [dimension]"
• "Summarize sales by region"
• "Show revenue breakdown"

Outputs:

• Pivot tables with professional formatting
• Charts and visualizations
• Slicers and filters
• Calculated fields

🛠️ Technical Details

Plugin Architecture

excel-analyst-pro/
├── plugin.json                    # Plugin configuration
├── README.md                      # This file
├── skills/                        # Auto-invoked Skills
│   ├── excel-dcf-modeler/
│   │   ├── SKILL.md              # DCF modeling instructions
│   │   └── resources/
│   │       └── dcf-template.xlsx
│   ├── excel-lbo-modeler/
│   ├── excel-variance-analyzer/
│   └── excel-pivot-wizard/
├── mcp/                          # MCP server config
│   └── excel-config.json
├── slash-commands/               # Manual triggers (optional)
│   ├── build-dcf.md
│   ├── build-lbo.md
│   └── analyze-variance.md
└── examples/                     # Example files

MCP Server Integration

This plugin uses @negokaz/excel-mcp-server for Excel operations:

Configuration:

{
  "command": "npx",
  "args": ["--yes", "@negokaz/excel-mcp-server"],
  "env": {
    "EXCEL_MCP_PAGING_CELLS_LIMIT": "4000"
  }
}

Capabilities:

• Read and write Excel (.xlsx) files
• Create sheets and workbooks
• Write formulas
• Format cells
• No Microsoft Excel installation required

💡 How It Works

Skills + MCP Server = Complete Solution

MCP Server (Low-Level):

• Provides Excel file operations
• Read cells, write formulas, create sheets
• Like having a toolbox 🧰

Skills (High-Level):

• Provide domain expertise
• Financial modeling patterns, best practices
• Like having an expert consultant 👔

Together:

• Professional results with zero effort 🚀

Example Flow

User: "Create a DCF model"
        ↓
Claude detects "DCF model" in request
        ↓
Auto-loads excel-dcf-modeler Skill
        ↓
Skill provides instructions:
  - Ask for company and assumptions
  - Build 4-sheet model structure
  - Calculate enterprise value
  - Create sensitivity tables
        ↓
Skill calls MCP server to:
  - create_workbook()
  - add_sheet()
  - write_formula()
  - format_cells()
        ↓
Output: Professional DCF model

No manual invocation needed! Just natural language.

📈 Use Cases

Investment Banking Analysts

• Before: 2-3 hours to build DCF from scratch
• After: 5 minutes with professional results
• Time Saved: 2-3 hours per model

Private Equity Associates

• Before: Full day to build LBO model
• After: 10 minutes with complete analysis
• Time Saved: 7-8 hours per deal

Finance Managers

• Before: 2 hours for monthly variance analysis
• After: 5 minutes with automated commentary
• Time Saved: 1 hour 55 minutes per month

Data Analysts

• Before: 55 minutes to clean data, create pivots, format charts
• After: 3 minutes end-to-end
• Time Saved: 52 minutes per report

🎓 Best Practices

1. Start with Defaults

Don't have all assumptions? No problem:

You: "Build a DCF but I don't have all the numbers"

Claude: No problem! I can build with industry-average assumptions.
What company are you valuing?

You: Amazon

Claude: I'll use standard assumptions for large-cap tech:
- Revenue growth: 15%, 12%, 10%, 8%, 6%
- EBITDA margin: 25%
- WACC: 9%

You can adjust the "Assumptions" sheet later.

2. Ask for Explanations

You: "Explain the DCF model you built"

Claude: Sure! Let me walk through the DCF model:

📊 What is a DCF?
A DCF values a company based on its future cash flows...

[Detailed explanation provided]

3. Iterate and Refine

You: "The WACC seems high—can we try 8% instead of 10%?"

Claude: Absolutely! Updating WACC from 10% to 8%...

New Enterprise Value: $924B (was $847B)
Change: +$77B (+9.1%)

Lower discount rate increases value as expected.

4. Request Variations

You: "Add a dividend recap in Year 3 to the LBO model"

Claude: I'll add a dividend recapitalization to the model.

In Year 3, after debt paydown:
- Refi to 5.0x EBITDA (from 3.8x)
- Distribute ~$150M to equity sponsors

This boosts IRR by ~300bps with partial liquidity.

⚠️ Limitations

What This Plugin Does Well

• Initial valuation analysis ✅
• Pitch decks and presentations ✅
• Academic exercises ✅
• Quick "back of envelope" valuations ✅
• Team standardization ✅

What Requires Manual Work

• Official fairness opinions ❌
• Detailed IC presentations (need scenario planning) ❌
• Quarterly debt schedules (annual only) ❌
• Complex waterfall structures ❌
• Third-party data validation ❌

Recommendation: Use this plugin for initial analysis (80% of use cases), then refine manually for high-stakes decisions.

🔒 Security & Privacy

Local Processing

• ✅ All Excel work happens locally
• ✅ No cloud upload required
• ✅ Works offline
• ✅ Full control over data

vs Claude for Excel (cloud-based):

• ❌ Uploads data to Anthropic cloud
• ❌ Requires Max/Enterprise/Teams subscription
• ❌ Subject to data retention policies

Recommendation: For sensitive financial data or regulated industries, use this plugin (local processing) instead of cloud-based solutions.

🆚 Comparison

| Feature | Excel Analyst Pro | Claude for Excel | Microsoft Copilot | |---------|------------------|------------------|-------------------| | Price | Free (open-source) | Max/Enterprise subscription | $30/user/month | | Processing | Local | Cloud | Cloud | | Skills Included | 4 (DCF, LBO, Variance, Pivot) | Limited beta | General assistance | | Customizable | ✅ Fully | ❌ No | ❌ No | | Team Sharing | ✅ Copy/paste Skills | ❌ Cloud only | ❌ Cloud only | | Financial Models | ✅ IB-grade templates | ✅ (beta) | ❌ Basic | | Token Efficient | ✅ Skills on-demand | ❌ Always loaded | N/A |

🐛 Troubleshooting

Plugin Not Loading

# Check Claude Code version
claude --version

# Reinstall plugin
/plugin uninstall excel-analyst-pro
/plugin install excel-analyst-pro@claude-code-plugins

MCP Server Not Working

# Verify Node.js version
node --version  # Should be 18+

# Manually test MCP server
npx --yes @negokaz/excel-mcp-server

Skill Not Triggering

Problem: You said "create DCF" but the Skill didn't load.

Solution: Be more explicit:

❌ "create DCF"
✅ "Create a DCF model for Apple"

Skills trigger on description matching—provide enough context.

🤝 Contributing

Want to add more Skills or improve existing ones?

1. Fork the repository
2. Create a new Skill in skills/
3. Follow the SKILL.md format (see existing Skills)
4. Test with real Excel workflows
5. Submit a pull request

Ideas for new Skills:

• Comparable company analysis (comps)
• M&A accretion/dilution model
• Three-statement financial model
• Portfolio performance tracker
• Budget template generator

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

• Anthropic for Claude Code and Skills system
• @negokaz for excel-mcp-server
• Investment banking community for modeling best practices

📞 Support

• Issues: https://github.com/jeremylongshore/claude-code-plugins/issues
• Discussions: https://github.com/jeremylongshore/claude-code-plugins/discussions
• Website: https://claudecodeplugins.io

🚀 What's Next

Roadmap

• [ ] Comparable company analysis Skill
• [ ] M&A accretion/dilution Skill
• [ ] Three-statement model builder
• [ ] Chart generation Skill
• [ ] VBA macro assistant
• [ ] Excel → Database migration tools

Version History

• v1.0.0 (2025-10-27): Initial release with 4 core Skills

Made with ❤️ for the Claude Code community

Star this repo if you find it useful! ⭐