expense-tracker-mcp-server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@expense-tracker-mcp-server Add a $15 lunch expense for today"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
ExpenseTracker FastMCP server
Lightweight MCP server for tracking personal expenses using FastMCP and SQLite. This repo provides a small, local MCP server you can run on your machine for quick experiments, demos, or as the basis for a remote deployment.
What this is -
A minimal MCP server exposing a few tools to record and query expenses.
Stores data in a local SQLite database:
expenses.db(created automatically).Ships a JSON resource
expense://categoriesbacked bycategories.json.
Main features
add_expense(date, amount, category, subcategory, note)
list_expenses(start_date, end_date)
update_expense(expense_id, ...)
delete_expense(expense_id)
summarize(start_date, end_date, category=None)
categories resource (JSON)
Related MCP server: local-expense-tracker
Quick start (Windows - cmd.exe)
Create a virtual environment and activate it (Windows
cmd.exe):
First of all install uv if you don't have it already globally using:
pip install uvThen create and activate a virtual environment:
python -m venv .venv
.venv\Scripts\activateInstall dependencies. If you use
pipdirectly, at minimum install FastMCP. If your project uses a lockfile orpyproject.toml, prefer that.
pip install fastmcp
# or, if you maintain requirements.txt:
pip install -r requirements.txtOptional: if you're using the uv helper CLI (used in some FastMCP guides), you can add FastMCP via the uv CLI instead of pip. Only run the following if you already have the uv tool installed:
uv add fastmcpRun the server in development mode (opens FastMCP studio if available):
uv run fastmcp dev main.pyRun the server for normal usage:
uv run fastmcp run main.pyNotes
Database:
expenses.dbwill be created next tomain.pyon first run.Edit
categories.jsonto customize categories; the MCPcategoriesresource reads it fresh on each call.
Testing with FastMCP Studio / Claude Desktop
You can test and inspect the MCP server locally either using the FastMCP studio (dev mode) or by adding the server to Claude Desktop.
Run FastMCP studio (dev mode)
uv run fastmcp dev main.pyThis runs the server in development mode and opens FastMCP's studio/inspector (if available) so you can call tools interactively.
Add the server to Claude Desktop (optional)
If you want Claude Desktop to manage and talk to your MCP server, install the Claude Desktop helper using the FastMCP/uv helper (only if you have the uv helper installed):
uv run fastmcp install claude-desktop main.pyImportant notes when using Claude Desktop:
After changing the server code, fully restart Claude Desktop so it reloads the MCP server. That means quitting the app completely (exit from the system tray / taskbar) and then reopening it.
If Claude Desktop fails to load your MCP server, edit the Claude Desktop MCP config: open Claude Desktop, go to Settings → Developer → Edit config. You'll see a JSON like this:
{
"mcpServers": {
"ExpenseTracker": {
"command": "C:\\Users\\Sayoun Parui\\AppData\\Roaming\\Python\\Python313\\Scripts\\uv.exe", # here if u see only uv
"args": [
"run",
"--with",
"fastmcp",
"fastmcp",
"run",
"C:\\Users\\Sayoun Parui\\Desktop\\ExpenceTracker MCP Server\\main.py"
],
"env": {},
"transport": "stdio",
"type": null,
"cwd": null,
"timeout": null,
"description": null,
"icon": null,
"authentication": null
}
},
"preferences": {
"menuBarEnabled": false,
"legacyQuickEntryEnabled": false
}
}If the
commandvalue just showsuv(or a short name) you should replace it with the full path to theuvexecutable. To find the full path, open a Windowscmd.exeand run:
where uvCopy the full path returned (for example C:\Users\You\AppData\Roaming\Python\Python313\Scripts\uv.exe) and paste it into the command field in the Claude config, replacing the short uv value. Save the config and restart Claude Desktop.
If where uv returns multiple results, pick the one that points to your desired Python environment (global or the one where you installed uv).
Tools / API (what you can call)
add_expense(date: str, amount: float, category: str, subcategory: str = "", note: str = "") -> {status, id}
list_expenses(start_date: str, end_date: str) -> list of expense objects
update_expense(expense_id: int, date, amount, category, subcategory, note) -> {status}
delete_expense(expense_id: int) -> {status}
summarize(start_date: str, end_date: str, category: Optional[str]) -> [{category, total_amount}]
Resource:
expense://categories— returnscategories.jsoncontent (mime_type: application/json)
Example call (pseudo):
# with FastMCP client or via the studio, call the `add_expense` tool:
result = mcp.call('add_expense', date='2025-10-01', amount=12.50, category='food', subcategory='snacks', note='coffee')Project layout
main.py— MCP server implementation and tool definitions.categories.json— default categories/subcategories used by the resource.expenses.db— SQLite DB (auto-created).
Deployment & next steps
This project is intentionally small so it's easy to convert to a remote service. Ideas for production-ready deployments:
Move the DB to Postgres or another managed DB (RDS, Cloud SQL).
Containerize the app and deploy to ECS, EKS, GKE, or App Services.
Add authentication to MCP endpoints and secure the server behind a gateway.
Short-term suggestions:
Add basic schema migration tooling (alembic/sqlalchemy or a simple migration script).
Add input validation and richer date handling (ISO 8601 enforcement).
Add unit tests for the tool functions.
Contributing
Small contributions welcome. Suggested workflow:
Fork the repo
Create a feature branch
Open a PR with a short description of changes
Please keep changes small and focused. If you plan a large refactor (DB change, API redesign), open an issue first.
Available Tools
5 toolsadd_expenseC
Add a new expense entry to the database.
Inputs: date (required), amount (required), category (required), subcategory, +1 more.
delete_expenseC
Delete an expense entry by its ID.
Inputs: expense_id (required).
list_expensesC
List expense entries within an inclusive date range.
Inputs: start_date (required), end_date (required).
summarizeB
Summarize expenses by category within an inclusive date range.
Inputs: start_date (required), end_date (required), category.
update_expenseC
Update an existing expense entry.
Inputs: expense_id (required), date (required), amount (required), category (required), +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: add, delete, list, summarize, and update. No overlap or ambiguity.
Four tools follow verb_noun pattern (add_expense, delete_expense, list_expenses, update_expense), but 'summarize' lacks a noun, which is a minor inconsistency.
Five tools is well-scoped for an expense tracker, covering essential operations without being excessive or insufficient.
CRUD operations are present (add, delete, update) along with listing and summarization. Missing a get_expense by ID, but list by date range covers retrieval adequately. Minor gap in filtering without summary.
Maintenance
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Log, query, and edit expenses, budgets, and accounts in Manilo from any MCP-compatible AI assistant.
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Nifty's MCP server — exposes tasks, projects, messages, and files as tools for AI agents.
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