KoltonG/Lunch-Money-MCP
If you are the rightful owner of Lunch-Money-MCP and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.
The Lunch Money MCP Server provides seamless access to financial data through a Model Context Protocol server, enabling AI assistants to interact with the Lunch Money API using standardized tools.
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.
šÆ 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
š§ 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.
š¤ 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 ā TDD ā Tasks ā 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
š Project Structure
āāā docs/ # Project documentation and planning
āāā rules/ # Agent execution rules and specifications
āāā src/ # MCP server implementation
āāā README.md # This file
š§ 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.