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mcp-server-ledger

MCP.Pizza Chef: minhyeoky

mcp-server-ledger is an MCP server that integrates Ledger CLI's powerful double-entry accounting system with Large Language Models. It exposes Ledger CLI commands through a standardized interface, allowing AI assistants to perform financial reporting, budget analysis, and detailed accounting queries. This server simplifies accessing and analyzing financial data programmatically, enabling automated workflows and enhanced financial insights via AI.

Use This MCP server To

Query account balances with date and filter options Retrieve detailed transaction registers for accounts Generate financial reports from Ledger CLI data Automate budget analysis using AI-driven queries Integrate financial data querying into AI assistants Enable real-time financial data insights for applications

README

mcp-server-ledger: A Ledger CLI MCP Server

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Overview

A Model Context Protocol server for interacting with Ledger CLI, a powerful, double-entry accounting system accessible from the command line. This server allows Large Language Models to query and analyze your financial data through the Ledger CLI tool.

This MCP server exposes Ledger CLI's functionality through a standardized interface, making it easy for AI assistants to help you with financial reporting, budget analysis, and accounting tasks.

Features

The server provides the following tools that map to Ledger CLI commands:

  1. ledger_balance

    • Shows account balances with powerful filtering options
    • Inputs: query pattern, date ranges, display options
    • Returns: Formatted balance report
  2. ledger_register

    • Shows transaction register with detailed history
    • Inputs: query pattern, date ranges, sorting options
    • Returns: Formatted register report
  3. ledger_accounts

    • Lists all accounts in the ledger file
    • Input: optional query pattern
    • Returns: List of matching accounts
  4. ledger_payees

    • Lists all payees from transactions
    • Input: optional query pattern
    • Returns: List of matching payees
  5. ledger_commodities

    • Lists all commodities (currencies) used
    • Input: optional query pattern
    • Returns: List of matching commodities
  6. ledger_print

    • Prints transactions in ledger format
    • Inputs: query pattern, date ranges
    • Returns: Formatted ledger entries
  7. ledger_stats

    • Shows statistics about the ledger file
    • Input: optional query pattern
    • Returns: Statistical summary of the ledger
  8. ledger_budget

    • Shows budget analysis
    • Inputs: query pattern, date ranges, reporting period
    • Returns: Budget report
  9. ledger_raw_command

    • Runs a raw Ledger CLI command
    • Input: command arguments as a list of strings
    • Returns: Command output as text

Prerequisites

  • Ledger CLI must be installed and available in your PATH
  • A valid Ledger file with your financial data

Installation

Using uv (recommended)

The easiest way to install and run this server is with uv:

uv sync

Configuration

The server requires a path to your Ledger file. This can be provided through:

  • The LEDGER_FILE environment variable
  • Command-line arguments when starting the server

Using with Claude Desktop

Add this to your claude_desktop_config.json:

"mcpServers": {
  "ledger": {
    "command": "uv",
    "args": [
      "run",
      "--env-file",
      "/path/to/your/.env",  // Optional: to set LEDGER_FILE
      "--with",
      "mcp[cli]",
      "mcp",
      "run",
      "<repo_path>/main.py"  // Path to the main.py file in this repository
    ]
  }

}

Usage Examples

Once configured, you can ask your AI assistant questions about your financial data:

  • "Show me my expenses for the last month"
  • "What's my current balance in all accounts?"
  • "List all transactions with Amazon"
  • "How much did I spend on groceries in 2023?"
  • "Show me my budget performance for Q1"

The AI will use the appropriate Ledger CLI commands through the server to get the information.

Debugging

For more detailed local testing:

mcp dev main.py

Development

This server is built using the Model Context Protocol Python SDK. For more information about MCP and how to develop MCP servers, see the official documentation.

To contribute to this project:

  1. Clone the repository
  2. Install development dependencies
  3. Make your changes
  4. Test using the MCP inspector or by integrating with Claude Desktop

Security Considerations

This server runs Ledger CLI commands on your financial data. While it includes basic validation to prevent command injection, you should:

  • Only use with trusted clients
  • Be careful about which file paths you expose
  • Review all commands before execution

License

This MCP server is licensed under the MIT License. Feel free to use, modify, and distribute it according to the license terms.

mcp-server-ledger FAQ

How does mcp-server-ledger interact with Ledger CLI?
It exposes Ledger CLI commands through a standardized MCP interface, allowing LLMs to query and analyze financial data programmatically.
What types of financial data can I access with this server?
You can access account balances, transaction registers, and generate detailed financial reports using Ledger CLI data.
Can this server handle complex queries with filters and date ranges?
Yes, it supports powerful filtering options including query patterns and date ranges for precise financial data retrieval.
Is mcp-server-ledger compatible with multiple LLM providers?
Yes, it is provider-agnostic and works with OpenAI, Anthropic Claude, and Google Gemini models.
How do I integrate this server into my AI assistant?
You connect the MCP client to this server, enabling your AI assistant to call Ledger CLI commands via the MCP protocol.
Does this server support real-time financial data updates?
It depends on the underlying Ledger CLI data source; the server provides up-to-date data as available.
What programming languages or environments can use this MCP server?
Any environment supporting MCP clients can integrate with this server, regardless of language.
Are there security considerations when exposing financial data through this server?
Yes, ensure proper access controls and secure communication channels when deploying this server in production.