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KoltonG

Lunch Money MCP Server

by KoltonG

Lunch Money MCP Server

LLM agent-driven development of a Model Context Protocol server for Lunch Money API access through systematic agent execution with rigorous validation processes.


🎯 Repository Goal

This repository builds a Model Context Protocol (MCP) server that provides seamless access to Lunch Money financial data via standard IO (stdio) transport.

Goal 1: Enable AI assistants to interact directly with Lunch Money's API through standardized MCP tools using stdio (not remote), allowing users to:

  • Query transaction data with flexible filtering

  • Access spending categories and budget information

  • Retrieve transaction tags and organizational data

  • Perform financial analysis through natural language

Related MCP server: Lunch Money MCP Server

🚧 Work in Progress

This project is actively under development using a systematic agent execution approach. Every line of code, configuration, and documentation is implemented through LLM agents following structured workflows.

🤖 LLM Agent-Driven Development

This repository showcases a novel development methodology where:

  • LLM agents execute all coding tasks following predefined rules and validation checkpoints

  • No manual coding - agents handle implementation, testing, and documentation

  • Systematic validation ensures quality through mandatory human approval at each step

  • Structured task management breaks complex features into validated sub-tasks

Agent Execution Framework

Significant engineering effort has been invested in creating comprehensive rules and processes that enable:

  • Self-executing agents that can autonomously implement features

  • Clear validation marks with mandatory human approval between sub-tasks

  • Quality assurance through structured TDD and testing requirements

  • Systematic progression from PRD → TDD → Tasks → Implementation

The agent execution rules in /rules/ define:

  • Task breakdown and dependency management

  • Validation checkpoints and quality gates

  • Branch management and PR generation

  • Error handling and feedback loops

📁 Project Structure

├── docs/                    # Project documentation and planning
├── rules/                   # Agent execution rules and specifications
├── src/                     # MCP server implementation
└── README.md               # This file

🔧 Technology Stack

  • Runtime: Bun (fast TypeScript execution)

  • Framework: Model Context Protocol SDK

  • Validation: Zod schemas

  • HTTP Client: Axios

  • Testing: Built-in bun test runner


This README will be updated as the project progresses through agent-driven development milestones.

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