Lunch Money FAQs

Question 1

How do I get started with the Lunch Money MCP Server?

Accepted Answer

You need to clone the repository, install dependencies using `uv`, obtain your Lunch Money API token, and set it as an environment variable (`LUNCHMONEY_API_TOKEN`). You can then configure it with your AI application (e.g., Claude Desktop) or run it standalone for testing.

Question 2

Which Lunch Money API features are currently supported?

Accepted Answer

It currently supports retrieving authenticated user details (`get_current_user`), specific transaction details (`get_transaction`), listing transactions by date range with optional aggregates (`get_transactions`), and includes an `add_numbers` helper tool for arithmetic.

Question 3

What is Lunch Money MCP Server?

Accepted Answer

It's a Model Context Protocol (MCP) server that integrates with the Lunch Money v2 API. It's specifically designed to provide minimal, concise, and token-optimized responses for efficient AI interaction, preventing context window bloat.

Question 4

Can I extend it with more Lunch Money API endpoints?

Accepted Answer

Yes, absolutely. The server features a modular design built with FastMCP and `requests-openapi`, making it very easy to add new endpoints one at a time. This design minimizes boilerplate code and leverages the OpenAPI specification for type safety.

Question 5

What are the key benefits for AI applications?

Accepted Answer

Its primary benefit is delivering highly optimized, focused responses from the Lunch Money API. This significantly reduces token usage and prevents large context windows, enabling AI models to interact with your financial data more efficiently and cost-effectively.

Lunch Money

Lunch Money

Key Features

Use Cases

Key Features

Use Cases