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ScottyOmega

YNAB MCP Server

search_transactions

Find transactions in a budget by payee, category, account, or date range. Combine optional filters to locate specific records.

Instructions

Searches transactions in a budget by payee, category, account, and/or date range. All filters are optional and combine together.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return, most recent first.
budget_idNoThe budget ID, or 'last-used' for the most recently used budget.last-used
payee_nameNoPartial, case-insensitive match on payee name.
since_dateNoOnly include transactions on or after this date (YYYY-MM-DD).
until_dateNoOnly include transactions on or before this date (YYYY-MM-DD).
account_nameNoPartial, case-insensitive match on account name.
category_nameNoPartial, case-insensitive match on category name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it delivers only the AND-combination semantics. It says nothing about the result cap (limit defaults to 50), ordering (most recent first), whether results are paginated, or any permission/auth requirements — all of which matter for a search tool.

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?

Two short sentences, no redundancy, and the core purpose is front-loaded before the filter semantics. Every clause earns its place.

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?

For a 7-parameter search tool with no annotations and no output schema, the description covers the input semantics but omits the return shape: how many transactions come back, their ordering, and whether the limit is a hard cap. It is minimally adequate but not complete.

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 every parameter (limit, budget_id, payee_name, since_date, until_date, account_name, category_name) is already documented in the schema. The description adds only the meta-claim that filters are optional and combinable, so the baseline 3 applies.

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?

States a specific verb (searches) and resource (transactions) scoped to a budget, and enumerates the filter dimensions (payee, category, account, date range), which is far more informative than the bare name. It does not, however, distinguish itself from siblings like list_uncategorized_transactions or list_unapproved_transactions, which are also transaction listings with implicit filters.

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

Usage Guidelines3/5

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

"All filters are optional and combine together" tells the agent that no parameters are required and that filters intersect, which is a genuine usage hint. But there is no statement of when to prefer this tool over the sibling listers (list_uncategorized_transactions, list_unapproved_transactions, spending_by_category), leaving the routing decision to inference.

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