Expense Tracker MCP Server

Expense Tracker MCP Server

Enables AI assistants to track, query, summarize, and delete personal expenses stored in a local SQLite database via natural language.

Category
Visit Server

README

Expense Tracker MCP Server

A Model Context Protocol (MCP) server built with Python and FastMCP that allows LLM assistants (like Claude Desktop) to track, query, summarize, and delete personal expenses using a local SQLite database.


📌 Project Summary

This project provides an intelligent financial tracker backend accessible via MCP tools. With this MCP server, an AI assistant can manage your personal expenses directly through conversational prompts.

Available Resources:

  • config://categories: Provides a predefined JSON mapping of categories and sub-categories for both income and expenses.

Available Tools:

  • add_expense: Add a new expense with amount, category, optional description, and optional date.
  • get_expenses: List and filter expenses by category, month, or year.
  • delete_expense: Remove an expense record by its unique ID.
  • add_income: Add a new income record (e.g., Salary, Investments).
  • get_incomes: List and filter income records.
  • delete_income: Remove an income record by its unique ID.
  • get_summary: Generate a monthly summary grouped by spending and income categories.

🚀 Step-by-Step Setup & Implementation Guide

Prerequisites


Step 1: Set Up the Project

Navigate to the project root directory:

cd C:\Users\arjun\Desktop\papi\expense-tracker-mcp

Install the required dependencies using uv:

uv pip install fastmcp

Step 2: Project Architecture (main.py)

The application defines an MCP server using FastMCP and initializes an SQLite database (expenses.db) automatically upon execution:

import datetime
from fastmcp import FastMCP
import os
import sqlite3

DB_PATH = os.path.join(os.path.dirname(__file__), "expenses.db")
mcp = FastMCP(name="Expense Tracker")

# Database Initialization
def init_db():
    with sqlite3.connect(DB_PATH) as c:
        c.execute('''
            CREATE TABLE IF NOT EXISTS expenses (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                amount REAL NOT NULL,
                category TEXT NOT NULL,
                description TEXT,
                date DATE NOT NULL DEFAULT CURRENT_DATE
            )
        ''')

init_db()

Step 3: Test Running the MCP Server

You can run the server locally to ensure there are no syntax errors:

uv run python main.py

Step 4: Integrate with Claude Desktop

Option A: Automatic Installation (Standard Claude Desktop)

If using standard Claude Desktop:

uv run fastmcp install claude-desktop main.py

Option B: Manual Configuration (Windows Store Claude Desktop)

If using the Microsoft Store version of Claude Desktop, open your claude_desktop_config.json:

  • Path: %LOCALAPPDATA%\Packages\Claude_pzs8sxrjxfjjc\LocalCache\Roaming\Claude\claude_desktop_config.json

Add the server entry under mcpServers:

{
  "mcpServers": {
    "expense-tracker": {
      "command": "uv",
      "args": [
        "run",
        "python",
        "C:\\Users\\arjun\\Desktop\\papi\\expense-tracker-mcp\\main.py"
      ]
    }
  }
}

Step 5: Restart Claude Desktop

  1. Close and fully quit Claude Desktop.
  2. Relaunch Claude Desktop.
  3. Look for the 🔌 icon to verify that the Expense Tracker tools are active.

💬 Example Conversational Prompts

Once configured in Claude Desktop, you can interact with your tracker using natural prompts:

  • "Add an expense of $15.50 for lunch under Food category today."
  • "Show all my Food expenses for this month."
  • "Give me a spending summary for August 2026."
  • "Delete expense ID 3."

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured