Tiller Money MCP Server

A Model Context Protocol (MCP) server for Tiller Money's Google Sheets-based personal finance tracking. Enables natural language queries against your financial data through Claude Desktop with direct read-only access via the Google Sheets API and OAuth2 authentication.

Quick Start

1. Installation

1. Clone this repository:

   git clone https://github.com/jackstein21/tiller-mcp-server.git
   cd tiller_mcp
   

2. Set up Python environment:

   # Using conda (recommended)
   conda create -n tiller_mcp python=3.12
   conda activate tiller_mcp
   
   # Install dependencies
   pip install -r requirements.txt
   

3. Set up Google Cloud Project:

   Before authenticating, you need to create a Google Cloud Project and enable the Google Sheets API:

   • Go to Google Cloud Console
   • Create a new project (or select an existing one)
   • Enable the Google Sheets API for your project
   • Create OAuth 2.0 credentials (Desktop app type)
   • Download the credentials JSON file
   • Save it as auth/credentials.json in this project

4. Authenticate with Google Sheets:

   # Run the authentication setup script
   python auth/auth_setup.py
   

   Follow the prompts:

   • Your browser will open for Google OAuth consent
   • Grant access to Google Sheets
   • Authentication token will be saved to auth/token.json

5. Configure Claude Desktop: Add this to your Claude Desktop configuration file:

   macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

   Windows: %APPDATA%\Claude\claude_desktop_config.json

   {
     "mcpServers": {
       "Tiller Money": {
         "command": "/opt/anaconda3/envs/tiller_mcp/bin/python",
         "args": [
           "/path/to/your/tiller_mcp/src/tiller_mcp_server/server.py"
         ],
         "env": {
           "TILLER_SHEET_ID": "your_tiller_spreadsheet_id_here"
         }
       }
     }
   }
   

   Important:

   • Replace /path/to/your/tiller_mcp with your actual project path
   • Replace your_tiller_spreadsheet_id_here with your Tiller spreadsheet ID
   • If not using conda, update the command path to your Python interpreter

6. Get your Tiller Spreadsheet ID:

   • Open your Tiller spreadsheet in Google Sheets
   • Copy the ID from the URL: https://docs.google.com/spreadsheets/d/{SPREADSHEET_ID}/edit

7. Restart Claude Desktop

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Features

Account Management

• View all active financial accounts
• Filter by account type (Credit Cards, Retirement, Savings, etc.)

Transaction Queries

• Search and filter transactions with powerful query options
• Date range filtering (start/end date)
• Account filtering (partial matching by account number)
• Category filtering (partial matching, case-insensitive)
• Amount filtering (min/max amounts for expenses or income)
• Description search across transaction text
• Pagination for large result sets
• Chronological sorting (most recent first)
• Detailed transaction lookup by ID

Category Management

• View all category definitions from Tiller
• Filter by category type (Expense, Income, Transfer)
• Filter by category group (Living, Fun, etc.)
• Optional monthly budget allocation data per category

Budget Analysis

• Access monthly budget allocations from Categories sheet
• Compare budgeted vs. actual spending
• Analyze any month or date range
• Natural language budget queries

---

Available Tools

Accounts

Tool	Description	Parameters
get_accounts	Get all active financial accounts	account_type (optional) - Filter by account type/group

Transactions

Tool	Description	Parameters
get_transactions	Query transactions with filtering & pagination	start_date, end_date, account, category, min_amount, max_amount, description, limit, offset (all optional)
get_transaction_details	Get complete details for a single transaction	transaction_id (required) - 24-character hex ID

Categories & Budgets

Tool	Description	Parameters
get_categories	Get all category definitions with optional monthly budgets	category_type (optional) - Filter by type (Expense/Income/Transfer) group (optional) - Filter by group (partial match) include_monthly_budgets (optional, default: false) - Include monthly budget data

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Usage Examples

Account Queries

Ask Claude natural language questions like:

• "Show me all my financial accounts"
• "Show me my credit card accounts"
• "List all my retirement accounts"

Transaction Queries

Query transactions using natural language:

• "Show me my 20 most recent transactions"
• "Show me all transactions in December 2025"
• "Get transactions between 12/01/2025 and 12/20/2025"
• "Show me transactions for account ending in 1234"
• "Show me all grocery transactions"
• "Find all dining expenses in December 2025"
• "Show me all expenses over $100"
• "List all income transactions"
• "Find transactions between $20 and $50"
• "Show me all Starbucks transactions"
• "Find all coffee shop purchases"

Combined Filters

Combine multiple criteria in one query:

• "Show me December 2025 transactions for account 1234"
• "Find dining expenses between $20 and $50 in December 2025"
• "Show all grocery transactions over $100"

Category Queries

Explore your category structure:

• "Show me all my categories"
• "List all expense categories"
• "What categories are in the Living group?"
• "Show expense categories in the Fun group"

Budget Analysis

Analyze budgets vs. actual spending:

• "Show me my budget for December 2025"
• "Get all expense categories with their monthly budgets"
• "How much did I spend on groceries in January vs. my budget?"
• "Which categories am I over budget in for this month?"
• "Show me my total budgeted vs. actual spending for December"

---

Data Structures

Account Object

Each account object contains:

Field	Type	Description	Example
display_name	string	Account name with masked number	"CREDIT CARD (-XXXX)"
account_type	string	Account type/group from Tiller	"Credit Cards", "Retirement", "Savings"
account_number	string	Last 4 digits	"-XXXX"
is_hidden	boolean	Always false (hidden accounts excluded)	false

Transaction Object

Each transaction object contains:

Field	Type	Description	Example
date	string	Transaction date	"12/19/2025"
description	string	Merchant/description	"Coffee Shop Downtown"
category	string	Transaction category	"Restaurants"
amount	float	Amount (negative for expenses)	-15.75
amount_str	string	Formatted amount string	"-$15.75"
account	string	Account display name	"CREDIT CARD (-XXXX)"
account_number	string	Last 4 digits of account	"XXXX"
institution	string	Financial institution	"Chase"
month	string	Month grouping	"12/01/25"
week	string	Week grouping	"12/15/25"
transaction_id	string	Unique 24-char hex ID	"123abc456def789012345678"
check_number	string	Check number if applicable	""
full_description	string	Full uppercase description	"COFFEE SHOP DOWNTOWN"

Category Object

Each category object contains:

Field	Type	Description	Example
category	string	Category name (unique identifier)	"Groceries", "Dining Out", "Salary"
group	string	Category group/classification	"Living", "Fun", "Primary Income"
type	string	Category type	"Expense", "Income", "Transfer"
monthly_budgets	object (optional)	Monthly budget amounts	{"Jan": {"amount": 600.0, "amount_str": "$600.00"}, ...}

Monthly Budgets Structure (when include_monthly_budgets=True):

• Contains 12 months: Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, Nov, Dec
• Each month has:
  • amount (float): Parsed budget amount (e.g., 600.0)
  • amount_str (string): Original currency string (e.g., "$600.00")

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Data Privacy & Security

Read-Only Access

• v1.0 is completely read-only - No write operations to your spreadsheet
• Safe to use without risk of data corruption
• Future write operations will require explicit user consent

Local Execution

• MCP server runs locally on your machine via stdio
• No cloud deployment or data transmission to third parties
• Data never leaves your local environment

Authentication Security

• OAuth2 credentials stored in auth/credentials.json (gitignored)
• Access token stored in auth/token.json (gitignored)
• Tokens automatically refresh when expired
• Full Google OAuth security model

Hidden Accounts

• Hidden accounts are always excluded from results
• No option to include hidden accounts (by design)
• Ensures sensitive accounts remain private

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Tiller Sheet Integration

The MCP server reads from standard Tiller Money spreadsheet tabs:

Accounts Sheet

Uses columns A-D for efficiency:

• Column A: Display name with masked number
• Column B: Class Override (not currently used)
• Column C: Group (account type)
• Column D: Hide flag

Transactions Sheet

Uses columns A-P for complete transaction data including date, description, category, amount, account, institution, and metadata.

Categories Sheet

Uses columns A-C for category definitions, with optional columns D-P for monthly budget allocations (12 months).

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Technical Details

Project Structure

tiller_mcp/
├── auth/
│   ├── credentials.json        # OAuth credentials (gitignored)
│   ├── token.json             # OAuth token (gitignored)
│   └── auth_setup.py          # Authentication setup script
├── src/tiller_mcp_server/
│   ├── __init__.py            # Package initialization
│   ├── server.py              # Main MCP server (FastMCP)
│   ├── sheets_client.py       # Google Sheets API wrapper
│   └── tiller_schema.py       # Pydantic models
├── config.json                # Example Claude Desktop config
├── requirements.txt           # Python dependencies
├── PRD.md                     # Product Requirements Document
└── README.md                  # This documentation

Architecture

Three-layer pattern for clean separation of concerns:

1. Data Models (tiller_schema.py)

   • Pydantic models for type-safe data handling
   • Account, Transaction, and Category models
   • Currency parsing, date handling, and account number extraction
   • Optional monthly budget data support

2. API Client (sheets_client.py)

   • Google Sheets API authentication and connection
   • Automatic token refresh handling
   • Efficient sheet range queries with singleton pattern

3. MCP Tools (server.py)

   • FastMCP framework with @mcp.tool() decorators
   • Read-only operations with comprehensive validation
   • JSON response formatting with helpful error messages

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Troubleshooting

Authentication Issues

Error: "TILLER_SHEET_ID environment variable not set"

• Solution: Add TILLER_SHEET_ID to Claude Desktop config under env section

Error: "Token file not found"

• Solution: Run python auth/auth_setup.py to create authentication token

Error: "Credentials are invalid and cannot be refreshed"

• Solution: Re-run authentication: python auth/auth_setup.py

Server Connection Issues

Error: "Server transport closed unexpectedly" in Claude Desktop

• Solution: Check that the Python path in config is correct
• Solution: Verify all dependencies are installed: pip install -r requirements.txt
• Solution: Test server manually: python src/tiller_mcp_server/server.py

Data Issues

Error: "Failed to parse account row"

• Solution: Check that your Tiller Accounts sheet has the expected column structure
• Solution: Verify columns A-D contain: Display Name, Class Override, Group, Hide

Common Error Messages

Error	Solution
"No valid session found"	Run python auth/auth_setup.py
"Spreadsheet not found"	Verify TILLER_SHEET_ID in config
"Permission denied"	Re-run auth setup to grant Sheets access
"Invalid credentials"	Check auth/credentials.json exists

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Development

Testing

# Test server manually
python src/tiller_mcp_server/server.py

# Server logs to stderr (visible in Claude Desktop logs)

Contributing New Tools

1. Design: Specify tool requirements in PRD.md
2. Data Model: Add Pydantic model to tiller_schema.py
3. API Client: Add sheet query method to sheets_client.py
4. MCP Tool: Add tool definition to server.py
5. Test: Validate in Claude Desktop

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Google Sheets API Quotas

Free Tier:

• 300 requests per minute (project)
• 60 requests per minute (user)
• No billing required for personal use

Expected Usage:

• Typical query: 1-3 API calls
• Daily usage: < 100 API calls
• Well within free tier limits

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Design Principles

• Read-only: No write operations to prevent data corruption
• Local execution: Runs locally via stdio, no cloud deployment
• No caching: Fresh data on every query (within generous API quotas)
• Privacy-first: Hidden accounts always excluded
• Iterative development: One tool at a time, thoroughly tested

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Roadmap

Completed Features

• Google Sheets API authentication and integration
• Tiller sheet structure discovery and documentation
• Account management tools
• Transaction query tools with comprehensive filtering
• Category management with budget data access
• Budget vs. actual analysis capabilities

Future Enhancements

• Balance history queries and trend analysis
• Category summary and aggregation tools
• Advanced analytics (spending patterns, trends, forecasting)
• AutoCat rule management (read-only)
• Export and reporting capabilities

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Support

For issues, follow these troubleshooting steps:

1. Check authentication: python auth/auth_setup.py
2. Verify configuration: Ensure TILLER_SHEET_ID is set in Claude Desktop config
3. Test server manually: python src/tiller_mcp_server/server.py
4. Review logs: Claude Desktop logs show server stderr output
5. Report issues on GitHub with error details and logs

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License

MIT License

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Acknowledgments

Inspiration

Inspired by the MonarchMoney Python library by @hammem - A fantastic unofficial API for Monarch Money with full MFA support.

Further inspired by @drbarq's excellent upgrade: monarch-mcp-server-god-mode

Built With

• Google Sheets API - Data access
• FastMCP - MCP server framework
• Pydantic - Data validation
• Tiller Money - Personal finance tracking platform