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gnucash-mcp

income_by_source

Read-only

Retrieve income totals by source for a date range, with optional grouping by month, quarter, or year and configurable category depth.

Instructions

Get income breakdown by source for a period.

Returns a compact aligned text table by default. Use verbose=true for the structured dict.

Args: start_date: Start of period (YYYY-MM-DD) end_date: End of period (YYYY-MM-DD) depth: Hierarchy depth for grouping (1 = top-level categories, 2 = subcategories) verbose: If false (default), compact text output — optimized for reading and token efficiency. If true, structured JSON, for when you need machine-readable fields rather than a report. group_by: Optional "month", "quarter", or "year" — split the range into sub-period columns and return a multi-period TSV table (source rows, one column per period plus Total and Avg). Overrides verbose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
verboseNo
end_dateYes
group_byNo
start_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.2

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses the default compact text output, the verbose structured JSON alternative, and the group_by override behavior. It also explains that group_by returns a multi-period TSV table with Total and Avg columns, giving substantial behavioral detail an agent needs to anticipate output.

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

Conciseness5/5

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

The description is front-loaded with the core purpose and default output, then organized into a compact Args list. Every sentence adds useful information; no filler or repetition of schema defaults that could confuse.

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

Completeness5/5

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

Given the tool's 5 parameters, read-only annotation, and existing output schema, the description covers everything needed for correct invocation: date formats, grouping depth, output format choice, and group_by's interaction with verbose. Return values are sufficiently described, and the output schema handles further detail.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden, and it succeeds: start_date and end_date get YYYY-MM-DD formats, depth gets concrete hierarchy meanings, verbose gets default and output implications, and group_by gets allowed values plus override semantics. This fully compensates for the lack of schema-level descriptions.

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

Purpose5/5

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

The description clearly states a specific verb and resource: 'Get income breakdown by source for a period.' It is distinct from sibling report tools like spending_by_category because it names income and source as the subject, and the rest of the description reinforces the report's scope.

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

Usage Guidelines4/5

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

The description provides clear context: it is for income breakdowns over a date range, with optional grouping by depth or sub-period. It does not explicitly name alternatives or exclusions, but the tool's purpose and parameters are specific enough for an agent to infer when it is appropriate.

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