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Expense Tracker MCP Server

Expense Tracker MCP Server

๐Ÿ’ธ Expense Tracker MCP Server

A professional Model Context Protocol (MCP) server designed to help you track, analyze, and optimize your personal finances. This server provides tools to add expenses, list transactions, and generate detailed financial summaries with Indian Rupee (โ‚น) support and strategic advice.

๐Ÿš€ Features

  • Add Expenses: Easily log expenses with categories, dates, and notes.

  • Tabular Summaries: Professional reports in tabular format showing counts, totals, and percentages.

  • Financial Advice: Strategic solutions tailored to your spending habits (Needs vs. Wants).

  • Visual Graphs: Built-in support for Mermaid.js charts and Matplotlib PNG graphs for visual distribution.

  • INR Support: All financial values are formatted in Indian Rupees (โ‚น).

Related MCP server: Trackor

๐Ÿ› ๏ธ Installation

1. Clone the Repository

git clone https://github.com/your-username/expense-tracker.git
cd expense-tracker

If you have uv installed, simply run:

uv sync

Alternatively, using standard pip:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install -r requirements.txt

๐Ÿ–ฅ๏ธ Usage

Running the Server

If using uv, you can run the server directly:

uv run main.py

Otherwise, use python:

python main.py

Claude Desktop Integration

To use this with Claude Desktop, add the following to your claude_desktop_config.json:

{
  "mcpServers": {
    "Expense Tracker": {
      "command": "uv",
      "args": ["--directory", "C:/path/to/expense-tracker", "run", "main.py"]
    }
  }
}

Note: Replace C:/path/to/ with the actual absolute path to your project directory.

๐Ÿ“‚ Project Structure

  • main.py: The core MCP server implementation.

  • expenses.db: SQLite database for persistent storage.

  • requirements.txt: List of Python dependencies.

  • pyproject.toml: Project configuration for tools like uv.

๐Ÿง  Smart Tools

  • add_expense: Add a new expense record.

  • list_expenses: Retrieve transactions within a date range.

  • summarize: Get a detailed financial report with graphs and advice.

  • categories: List all supported expense categories.

โš–๏ธ License

MIT

Available Tools

3 tools
add_expenseD

Inputs: date (required), amount (required), category (required), note, +1 more.

list_expensesD

Inputs: end_date (required), start_date (required).

summarizeA

Summarize expenses between two dates, providing a detailed analysis, financial advice, and a visualization graph.

Inputs: end_date (required), start_date (required), category.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelogโ€ฆ

    TDQS

    C2.3/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: adding an expense, listing expenses, and summarizing/analyzing them. There is no overlap in their core functions, making it easy for an agent to choose the right tool.

    Naming Consistency4/5

    Most tools follow the verb_noun pattern (add_expense, list_expenses), but 'summarize' lacks an object, deviating from the pattern. There is also a minor singular/plural inconsistency between 'expense' and 'expenses'. Overall the convention is readable and predictable.

    Tool Count4/5

    With only three tools, the set is minimal but appropriate for a simple expense tracker. The count is not excessively thin (like 1-2) and stays within a reasonable scope, though one could imagine additional tools for management.

    Completeness3/5

    The server covers creating and reading expenses, plus a summary/analysis function, but lacks update and delete operations. For an expense tracker, the inability to modify or remove expenses is a notable gap that agents would have to work around.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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      Enables users to track and manage personal expenses through natural language, including adding entries, filtering by date/category, viewing statistics, and exporting data in JSON or CSV format.
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