Skip to main content
Glama
jamiew

Monarch Money MCP Server

Get Spending Summary

get_spending_summary
Read-only

Retrieve an intelligent spending summary for any date range, grouped by category, account, or month.

Instructions

Get intelligent spending summary with aggregations.

Args: start_date: Start date (supports natural language like 'last month') end_date: End date (supports natural language) group_by: Group spending by 'category', 'account', or 'month'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNo
end_dateNo
group_byNocategory

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodYes
group_byYes
groupsYes
totalsYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true, so the description adds some value by mentioning natural language date support and aggregation grouping. However, it does not elaborate on aggregation details, performance, or data scope, which would further enhance transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with two sentences and a bullet list for parameters. Every element adds value, though the bullet list could be integrated more tightly into the main text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present (though not shown), the description need not detail return values. However, it does not specify what aggregations are computed (e.g., total spending, averages) or include any caveats, leaving some gaps for a tool with three parameters and no required inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description compensates by explaining that start_date and end_date support natural language and that group_by accepts 'category', 'account', or 'month'. This adds significant meaning beyond the bare schema types, though it could mention defaults and optionality.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets an intelligent spending summary with aggregations, specifying the verb and resource. However, it does not distinguish this tool from siblings like analyze_spending_patterns or get_cashflow, which may also provide spending summaries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description only explains what the tool does, not when it should be chosen over siblings like get_complete_financial_overview or analyze_spending_patterns.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jamiew/monarch-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server