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ninetails-io

gnucash-mcp

list_accounts

Read-only

List GnuCash accounts with filtering by root or query, pagination, and compact or verbose output.

Instructions

List all accounts in the GnuCash chart of accounts.

Leads with a Showing X-Y of Z accounts line, then a compact one-line-per-account format by default. Page with offset; limit=0 returns the count only. Use verbose=true for full JSON with guid, type, commodity, etc.

To FIND an account without paging the whole chart, pass query — a case-insensitive substring matched against each account's full path and description (e.g. query="grocer" or query="4930" on a numbered chart). Results emit %short GUIDs that every account-taking tool accepts. For searching transactions by text or amount, use search_transactions.

Args: root: Filter to a subtree (e.g., "Expenses" for expense accounts only). 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. limit: Page size (default 50, max 250). 0 = count only. offset: 0-indexed first row to return (default 0). query: Case-insensitive substring filter on account path/description. Combines with root.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootNo
limitNo
queryNo
offsetNo
verboseNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.2

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses output format ('Showing X-Y of Z accounts', one-line-per-account), page size behavior, count-only mode, case-insensitive substring matching, and that results emit %short GUIDs accepted by other account-taking tools. This is rich behavioral context that the annotations do not provide.

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 detailed but every sentence earns its place, covering purpose, output format, paging, query behavior, and parameter semantics. It is front-loaded with the core action, then organized into usage guidance and an Args list. The length is proportionate to the tool's five parameters and non-trivial behaviors.

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?

For a read-only listing tool with an output schema and readOnlyHint, the description is complete: it covers all parameters, output variants, paging, filtering, query semantics, and even how returned GUIDs interoperate with other tools. Nothing an agent needs to select or invoke this tool correctly is missing.

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?

The input schema provides only names, types, and defaults, with 0% description coverage. The tool description compensates fully by explaining each parameter: root subtree filtering, verbose output mode, limit paging semantics, offset indexing, and query substring matching. It adds concrete examples and combination behavior not available in the schema.

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 opens with a specific verb and resource: 'List all accounts in the GnuCash chart of accounts.' It clearly distinguishes this from transaction searching by explicitly directing users to search_transactions for text/amount search, and from single-account retrieval by framing this as the whole-chart listing tool.

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

Usage Guidelines5/5

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

The description gives explicit guidance on when to use the query parameter instead of paging, when to switch to search_transactions, and when to choose verbose=true vs compact output. It also explains the root subtree filter and the count-only behavior, leaving no ambiguity about selection among closely related tools.

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