Lunchmoney MCP Server

A Model Context Protocol (MCP) server that lets you interact with your Lunchmoney transactions and budgets through Claude and other AI assistants.

Features

This server provides four main tools:

1. get-recent-transactions: View your recent transactions from the past N days
2. search-transactions: Search transactions by keyword in payee names or notes
3. get-category-spending: Analyze spending in specific categories
4. get-budget-summary: Get detailed budget information including spending, remaining amounts, and recurring items

Installation

Installing via Smithery

To install Lunchmoney MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @leafeye/lunchmoney-mcp-server --client claude

You can use this server directly in Claude Desktop without installation:

{
  "mcpServers": {
    "lunchmoney": {
      "command": "npx",
      "args": ["-y", "lunchmoney-mcp-server"],
      "env": {
        "LUNCHMONEY_TOKEN": "your_token_here"
      }
    }
  }
}

Replace your_token_here with your Lunchmoney API token, which you can get from your Lunchmoney developer settings.

Example Usage

Once configured in Claude Desktop, you can ask questions like:

Transactions

• "Show me my recent transactions from the past week"
• "Search for all transactions at Amazon"
• "How much did I spend on restaurants last month?"
• "Find transactions tagged as business expenses"

Budgets

• "Show me my budget summary for this month"
• "What's my budget status from January to March 2024?"
• "How much of my food budget is remaining?"
• "Show me categories where I'm over budget"

What is MCP?

The Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context to Large Language Models (LLMs). Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools.

Some key benefits of MCP:

• Standardized way to expose data and functionality to LLMs
• Human-in-the-loop security (all actions require user approval)
• Growing ecosystem of pre-built integrations
• Works with multiple AI models and applications

Development

To develop locally:

1. Clone this repository
2. Install dependencies:

npm install

3. Build the TypeScript code:

npm run build

4. Run with your API token:

LUNCHMONEY_TOKEN=your_token_here node build/index.js

5. Test with MCP Inspector:

LUNCHMONEY_TOKEN=your_token_here npx @modelcontextprotocol/inspector node build/index.js

API Notes

• Budget data must use month boundaries for dates (e.g., 2024-01-01 to 2024-01-31)
• Transactions can use any date range
• All monetary values are returned in their original currency
• Category names are case-insensitive when searching

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.