Expense Manager MCP Server

An MCP server for managing personal expenses using Python, FastMCP, and SQLite.

Connect it to Claude Desktop and manage your expenses using natural language.

Features

• Add, update, and delete expenses

• Search expenses

• List expenses by date range

• Summarize spending by category

• Store data locally using SQLite

• Expose expense categories through an MCP resource

Related MCP server: Expense Tracker MCP Server

Tech Stack

• Python 3.11+

• FastMCP

• Model Context Protocol (MCP)

• SQLite

• uv

Setup

git clone https://github.com/sonali1103/expense-manager-mcp-server.git
cd expense-manager-mcp-server
uv sync

Connect to Claude Desktop

1. Find your project path

From the project directory, run:

pwd

Copy the path returned. You'll need it in the Claude configuration.

2. Open Claude Desktop configuration

In Claude Desktop:

Settings → Developer → Edit Config

This opens claude_desktop_config.json.

On macOS, the file is located at:

~/Library/Application Support/Claude/claude_desktop_config.json

3. Add the MCP server

Add the following inside mcpServers:

{
  "mcpServers": {
    "expense-manager": {
      "command": "uv",
      "args": [
        "--directory",
        "/YOUR/PATH/expense-manager-mcp-server",
        "run",
        "main.py"
      ]
    }
  }
}

Replace:

/YOUR/PATH/expense-manager-mcp-server

with the path you copied from pwd.

4. Restart Claude Desktop

Completely quit and reopen Claude Desktop.

Then click the Connectors icon near the chat box and verify that expense-manager is connected. Claude Desktop will show the MCP tools provided by the server.

Try It

Once connected, ask Claude:

"Add a $45 grocery expense for today."

"Show me my expenses for this month."

"How much did I spend on food this month?"

"Find my travel expenses."

"Delete expense 12."

MCP Tools

Database

Expenses are stored locally in:

expenses.db

The database and expenses table are created automatically when the server starts.

Project Structure

expense-manager-mcp-server/
├── main.py
├── categories.json
├── pyproject.toml
├── uv.lock
└── .gitignore

This project demonstrates how Model Context Protocol connects an AI assistant to real application functionality and data through standardized tools.