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Braintree MCP by usefulapi

Search transactions

braintree_search_transactions
Read-only

Search transactions by created-at date range, status, and/or customer. Builds a TransactionSearchInput (operators: status in, createdAt greaterThanOrEqualTo/lessThanOrEqualTo, customer.id is). Returns a page of transaction nodes (id, legacyId, amount, status, createdAt). GraphQL search { transactions }.

Input Schema

NameRequiredDescriptionDefault
firstNoMax transactions to return (page size). Default 25.
statusNoOne or more transaction statuses to match (e.g. ["SETTLED","VOIDED"]).
customerIdNoGraphQL global Customer ID to filter to one customer's transactions.
createdAfterNoOnly transactions created at or after this ISO-8601 timestamp.
createdBeforeNoOnly transactions created at or before this ISO-8601 timestamp.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

readOnlyHint=true already establishes this as a safe read, so the burden is lower. The description adds genuinely new behavior: it discloses the return shape (id, legacyId, amount, status, createdAt) and the underlying GraphQL `search { transactions }` call. It stops short of explaining pagination/cursor mechanics beyond the word 'page'.

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?

Three dense sentences with no filler, front-loaded with what is searchable before the implementation and return details. Slightly technical (TransactionSearchInput, GraphQL path) but each clause carries information.

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

Completeness4/5

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

For a read-only search with no output schema, the description supplies the filter model, the returned fields, and the query backing it. The only real gap is pagination behavior when paging past the default 25, which is not addressed.

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?

With 100% schema coverage the baseline is 3, but the description earns extra credit by mapping each visible parameter to the underlying search operator (status `in`, createdAt `greaterThanOrEqualTo`/`lessThanOrEqualTo`, customer.id `is`), clarifying inclusivity and semantics beyond the schema text.

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 (Search) and resource (transactions) plus the three filter axes (date range, status, customer), which separates it from the single-record braintree_find_transaction. It does not name any sibling explicitly, so it stops short of full sibling differentiation.

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?

The phrase 'and/or' signals that filters are optional and composable, which is useful selection context, but there is no explicit when-to-use guidance or routing versus braintree_find_transaction or braintree_list_subscriptions. Usage is only implied.

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

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