A Model Context Protocol server for the Lunch Money API with optimized, minimal responses
Project description
Lunch Money MCP Server
A Model Context Protocol (MCP) server for the Lunch Money API v2, designed with minimal response sizes to prevent context window bloat.
Features
- Optimized responses: Concise, formatted output to minimize token usage
- Simple authentication: Uses environment variable for API token
- Type-safe: Built with modern Python type hints
- Easy to extend: Add more endpoints one at a time
Currently Supported Endpoints
add_numbers- Helper tool for arithmetic operationsget_current_user- Get information about the authenticated user (GET /me)get_transaction- Get details about a specific transaction by ID (GET /transactions/{id})get_transactions- List transactions for a date range (GET /transactions)
Installation
- Clone this repository:
git clone <your-repo-url>
cd lunchmoney-mcp-mini
- Install dependencies using uv:
uv sync
Configuration
Get Your API Token
- Log in to Lunch Money
- Go to the Developers page
- Create a new API token or use an existing one
Set Environment Variable
export LUNCHMONEY_API_TOKEN="your-api-token-here"
Or create a .env file (not committed to git):
LUNCHMONEY_API_TOKEN=your-api-token-here
Usage
With Claude Desktop
Add to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"lunchmoney-mini": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/lunchmoney-mcp-mini",
"run",
"lunchmoney_mcp_mini/main.py"
],
"env": {
"LUNCHMONEY_API_TOKEN": "your-api-token-here"
}
}
}
}
Standalone Testing
# Make sure LUNCHMONEY_API_TOKEN is set
uv run lunchmoney_mcp_mini/main.py
Available Tools
add_numbers
Helper tool for performing arithmetic operations with precise decimal handling to avoid floating-point precision issues.
Parameters:
numbers(required): List of numbers to add together. Can include negative values for subtraction.
Returns:
sum: Sum rounded to 2 decimal placesinput_count: Number of values provided
Example output:
{
"sum": 123.45,
"input_count": 3
}
get_current_user
Get details about the authenticated Lunch Money user.
Returns:
name: User's full nameemail: User's email addressuser_id: Unique user identifieraccount_id: Unique account identifierbudget_name: Name of the budgetprimary_currency: Primary currency code (e.g., 'usd')api_key_label: Label for the API key being used
Example output:
{
"name": "John Doe",
"email": "john@example.com",
"user_id": 12345,
"account_id": 67890,
"budget_name": "Family budget",
"primary_currency": "usd",
"api_key_label": "Development key"
}
get_transaction
Get full details about a specific transaction by its ID.
Parameters:
transaction_id(required): ID of the transaction to retrieve
Returns: Complete transaction object with all available fields including:
- Core data: id, date, amount, currency, payee, original_name
- Category/accounts: category_id, manual_account_id, plaid_account_id, recurring_id
- Metadata: plaid_metadata, custom_metadata, files (if any)
- Grouping/splitting: is_split_parent, split_parent_id, is_group_parent, group_parent_id, children
- Timestamps: created_at, updated_at
- Status: status, is_pending, source, external_id, tag_ids, notes
Example output:
{
"id": 2112150655,
"date": "2024-07-28",
"amount": -45.50,
"currency": "USD",
"payee": "Whole Foods",
"original_name": "WHOLE FOODS #1234",
"category_id": 82,
"status": "reviewed",
"is_pending": false,
"created_at": "2024-07-28T12:34:56.789Z",
"updated_at": "2024-07-28T12:34:56.789Z"
}
get_transactions
List transactions within a specified date range.
Parameters:
start_date(required): Start date in YYYY-MM-DD formatend_date(optional): End date in YYYY-MM-DD format. Defaults to last day of start_date's monthcategory_id(optional): Filter by category IDtag_id(optional): Filter by tag IDstatus(optional): Filter by status ("reviewed", "unreviewed", "delete_pending")is_pending(optional): Filter by pending statusmanual_account_id(optional): Filter by manual account IDplaid_account_id(optional): Filter by plaid account IDrecurring_id(optional): Filter by recurring item IDinclude_pending(optional): Include pending transactionslimit(optional): Maximum number of transactions (1-2000, default 100)offset(optional): Pagination offsetinclude_aggregates(optional): If True, calculates totals per category for full date range (respects all filters)
Returns:
transactions: Array of transaction objectshas_more: Boolean indicating if more transactions are availableaggregates(optional): Category totals and counts wheninclude_aggregates=True
Transaction fields:
id: Transaction IDdate: Transaction date (YYYY-MM-DD)amount: Transaction amount (numeric string)payee: Payee namecategory_id: Category IDstatus: Transaction statusis_pending: Pending status
Aggregates fields (when include_aggregates=True):
by_category: Array sorted bytotal_amountdescending, each with:category_id: Category ID (or null for uncategorized)category_name: Category namecount: Number of transactions in this categorytotal_amount: Sum of transaction amounts (numeric string)
total_count: Total number of transactionstotal_amount: Sum of all transaction amounts (numeric string)
Example output (without aggregates):
{
"transactions": [
{
"id": 2112150655,
"date": "2024-07-28",
"amount": "1250.8400",
"payee": "Paycheck",
"category_id": 88,
"status": "reviewed",
"is_pending": false
}
],
"has_more": false
}
Example output (with aggregates):
{
"transactions": [...],
"has_more": false,
"aggregates": {
"by_category": [
{"category_id": 88, "category_name": "Rent", "count": 2, "total_amount": "2500.00"},
{"category_id": 82, "category_name": "Groceries", "count": 5, "total_amount": "245.50"},
{"category_id": null, "category_name": "Uncategorized", "count": 3, "total_amount": "45.00"}
],
"total_count": 10,
"total_amount": "2790.50"
}
}
Design Philosophy
This MCP server is intentionally designed to return minimal, focused responses to avoid filling up the context window. Each tool:
- Returns only essential information
- Uses concise formatting
- Avoids verbose JSON dumps
- Provides human-readable output
Technical Details
This server uses:
- FastMCP: A high-level Python framework for building MCP servers
- requests-openapi: Automatically generates API client from OpenAPI spec
- OpenAPI 3.0 spec: Ensures type safety and accurate API calls
The combination of FastMCP and requests-openapi means:
- Less boilerplate code
- Automatic request/response validation
- Easy to add new endpoints from the spec
- Type-safe API calls
Resources
License
MIT
Project details
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