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alexfu

mcp-ynab

by alexfu

getAccounts

Returns all accounts for a specified YNAB plan, with optional filtering to only include changes since a given server knowledge.

Instructions

Returns all accounts

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plan_idYesThe id of the plan. "last-used" can be used to specify the last used plan and "default" can be used if default plan selection is enabled (see: https://api.ynab.com/#oauth-default-plan).
last_knowledge_of_serverNoThe starting server knowledge. If provided, only entities that have changed since `last_knowledge_of_server` will be included.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Returns all accounts' and does not disclose that results are scoped to a plan, that 'all accounts' may be filtered by last_knowledge_of_server, or whether this is a read-only operation. The description is not misleading, but it is severely under-informative.

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

Conciseness3/5

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

The description is extremely short and front-loaded, which is good, but it is under-specified rather than concise. A single sentence that omits scope and filtering behavior does not earn full credit for structure because it fails to convey essential context.

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

Completeness2/5

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

The tool has an output schema and 100% schema coverage, but the description is too thin for a list endpoint with a required plan_id and an optional server-knowledge filter. An agent cannot tell from the description that 'all accounts' are scoped to a plan or that the result set can be a delta. The output schema may describe the response shape, but the description does not explain the tool's selection semantics.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description itself adds no parameter meaning beyond the schema, but the schema already documents plan_id and last_knowledge_of_server well, including the special 'last-used' and 'default' values. The description does not need to compensate.

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

Purpose3/5

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

The description 'Returns all accounts' states a clear verb and resource, but it does not distinguish this from sibling tools like getAccountById or getTransactionsByAccount. It is minimally clear but lacks scope details such as whether it returns accounts for a plan or across the entire system.

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 is provided about when to use this tool versus alternatives. The description does not mention that it is the list counterpart to getAccountById, nor does it explain the plan_id requirement or when to use 'last-used' or 'default' plan selection. The schema covers parameter mechanics but not usage context.

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