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The core read surface of Breadbox. Agents query transactions, aggregate spending, and read activity context through the tools on this page. All amounts use the Plaid sign convention: positive = money out, negative = money in. See Conventions for the full cross-cutting rules.

query_transactions

Returns a paginated list of transactions matching the supplied filters. This is the workhorse read tool — almost every agent session goes through it. Scope: Read Mirrors: GET /api/v1/transactions

Parameters

start_date
string (YYYY-MM-DD)
Start date inclusive.
end_date
string (YYYY-MM-DD)
End date exclusive.
account_id
string
Filter to a single account (UUID or short ID).
user_id
string
Filter to all accounts owned by a family member. Attribution-aware — includes transactions attributed to this user via account links.
category_slug
string
Filter by category slug. Parent slugs include all children.
min_amount
number
Minimum amount (positive = debit, negative = credit).
max_amount
number
Maximum amount.
pending
boolean
Filter by pending status. Omit to return both.
Case-insensitive substring match on name and merchant_name. Comma-separate values for OR.
search_mode
string
default:"contains"
contains, words, or fuzzy.
Exclude transactions whose name or merchant matches this text.
tags
array of strings
Tags the transaction must have (AND). The review queue is ["needs-review"].
any_tag
array of strings
Tags the transaction must have at least one of (OR).
limit
integer
default:"50"
Max 500.
cursor
string
Opaque pagination cursor from a previous response. Only valid with sort_by=date.
sort_by
string
default:"date"
date, amount, or name.
sort_order
string
default:"desc"
desc or asc.
fields
string
Comma-separated fields or aliases (minimal, core, category, timestamps). See Conventions. id is always included.
session_id
string
Optional session ID to associate this read with a session.
reason
string
Optional rationale for this query.

Example input

{
  "start_date": "2026-03-01",
  "end_date": "2026-04-01",
  "category_slug": "food_and_drink_groceries",
  "fields": "core,category",
  "limit": 100
}
{
  "transactions": [
    {
      "id": "k7Xm9pQ2",
      "date": "2026-03-28",
      "amount": 67.43,
      "name": "WHOLE FOODS MARKET #10452",
      "iso_currency_code": "USD",
      "category": {
        "slug": "food_and_drink_groceries",
        "display_name": "Groceries",
        "primary_slug": "food_and_drink",
        "primary_display_name": "Food and Drink"
      },
      "category_primary_raw": "FOOD_AND_DRINK",
      "category_detailed_raw": "FOOD_AND_DRINK_GROCERIES"
    }
  ],
  "next_cursor": "eyJkYXRlIjoiMjAyNi0wMy0yOCIsImlkIjoiazdYbTlwUTIifQ",
  "has_more": true,
  "limit": 100
}

count_transactions

Returns the count of transactions matching the filters, without fetching any rows. Agents use this as a cheap pre-flight to decide whether to paginate or narrow filters. Scope: Read Mirrors: GET /api/v1/transactions/count

Parameters

Accepts the same filters as query_transactions except cursor, limit, sort_by, sort_order, and fields.

Example input

{
  "start_date": "2026-01-01",
  "end_date": "2026-04-01",
  "category_slug": "food_and_drink_groceries"
}

Example output

{ "count": 128 }

transaction_summary

Returns aggregated transaction totals grouped by category, month, week, day, or category × month. Replaces the need to paginate through every transaction for spending analysis. Amounts follow the Plaid convention — positive = money out. Scope: Read Mirrors: GET /api/v1/transactions/summary

Parameters

group_by
string
required
One of category, month, week, day, category_month.
start_date
string (YYYY-MM-DD)
Defaults to 30 days ago.
end_date
string (YYYY-MM-DD)
Defaults to today.
account_id
string
Filter by account.
user_id
string
Filter by family member (attribution-aware).
category
string
Filter by primary category before aggregating.
include_pending
boolean
default:"false"
Include pending transactions.

Example input

{
  "group_by": "category",
  "start_date": "2026-03-01",
  "end_date": "2026-04-01"
}
{
  "summary": [
    {
      "category": "food_and_drink_groceries",
      "total_amount": 843.21,
      "transaction_count": 34,
      "iso_currency_code": "USD"
    },
    {
      "category": "transportation_gas",
      "total_amount": 312.50,
      "transaction_count": 18,
      "iso_currency_code": "USD"
    }
  ],
  "totals": {
    "total_amount": 1155.71,
    "transaction_count": 52
  },
  "filters": {
    "start_date": "2026-03-01",
    "end_date": "2026-04-01",
    "group_by": "category"
  }
}

merchant_summary

Lists distinct merchants with aggregated stats — count, total, average, and date range. Agents use this to scan for recurring charges, find top merchants, or surface unknown subscriptions. Scope: Read Mirrors: GET /api/v1/transactions/merchants

Parameters

start_date
string (YYYY-MM-DD)
Defaults to 90 days ago.
end_date
string (YYYY-MM-DD)
Defaults to today.
account_id
string
Filter by account.
user_id
string
Filter by family member.
category_slug
string
Filter by category.
min_amount
number
Minimum per-transaction amount.
max_amount
number
Maximum per-transaction amount.
search
string
Search merchant/transaction names.
search_mode
string
default:"contains"
contains, words, fuzzy.
exclude_search
string
Exclude merchants matching this text.
min_count
integer
default:"1"
Minimum transaction count to include a merchant. Set to 2 for recurring, 3 for likely subscriptions.
spending_only
boolean
default:"false"
Only include positive amounts (spending).

Example input

{
  "start_date": "2026-01-01",
  "end_date": "2026-04-01",
  "min_count": 3,
  "spending_only": true
}
{
  "merchants": [
    {
      "merchant": "Netflix",
      "transaction_count": 3,
      "total_amount": 42.00,
      "avg_amount": 14.00,
      "first_date": "2026-01-15",
      "last_date": "2026-03-15",
      "iso_currency_code": "USD"
    },
    {
      "merchant": "Whole Foods Market",
      "transaction_count": 12,
      "total_amount": 843.21,
      "avg_amount": 70.27,
      "first_date": "2026-01-03",
      "last_date": "2026-03-28",
      "iso_currency_code": "USD"
    }
  ],
  "totals": {
    "merchant_count": 2,
    "transaction_count": 15,
    "total_amount": 885.21
  },
  "filters": {
    "start_date": "2026-01-01",
    "end_date": "2026-04-01",
    "min_count": 3
  }
}

list_transaction_comments

Deprecated. Use list_annotations with kinds=['comment'] instead. The new tool returns the same comment data using the canonical annotation shape — note the field renames: actor_type / actor_id / actor_name (was author_*) and payload.content (was top-level content). list_transaction_comments will be removed in a future release.
Returns all comments attached to a transaction, ordered chronologically. Agents should check comments before writing to understand prior context. Scope: Read

Parameters

transaction_id
string
required
UUID or short ID of the transaction.

Example input

{ "transaction_id": "k7Xm9pQ2" }

Example output

[
  {
    "id": "c4Xp2mQr",
    "transaction_id": "k7Xm9pQ2",
    "content": "Shared grocery run — split with roommate.",
    "author_type": "user",
    "author_id": "u4Xm9pQ2",
    "author_name": "Alice",
    "created_at": "2026-03-29T10:12:00Z",
    "updated_at": "2026-03-29T10:12:00Z"
  }
]

list_transaction_matches

Lists transaction pairs matched by an account link. Used to audit which primary-account transactions were attributed to a dependent user via the account-link dedup system. Scope: Read

Parameters

The account link ID to list matches for.

Example input

{ "link_id": "L9Xm2pQr" }

Example output

[
  {
    "id": "M4Xp9mQr",
    "account_link_id": "L9Xm2pQr",
    "primary_transaction_id": "k7Xm9pQ2",
    "dependent_transaction_id": "n3Xr5mQp",
    "match_confidence": "auto",
    "matched_on": ["date", "amount"],
    "primary_txn_name": "WHOLE FOODS MARKET #10452",
    "primary_txn_merchant": "Whole Foods",
    "dependent_txn_name": "WHOLE FOODS #10452",
    "dependent_txn_merchant": "Whole Foods",
    "amount": 67.43,
    "date": "2026-03-28",
    "created_at": "2026-03-28T08:15:00Z"
  }
]

list_annotations

Returns the activity timeline for a single transaction: comments, tag adds/removes, rule applications, and category sets. Ordered by created_at ascending. Use this to reconstruct “what happened to this transaction and when” before making further changes. Each row carries a generic kind plus an action for the specific event, so you can branch on the action without parsing the kind string:
kindaction valuesNotes
comment(omitted)Free-form comment. payload.content carries the body.
ruleappliedA transaction rule fired. payload.rule_name and rule_id are populated.
tagadded / removedTag attached to or detached from the transaction. tag_id and payload.slug are populated.
categorysetCategory was set (manual override or via rule).
Scope: Read

Parameters

transaction_id
string
required
UUID or short ID of the transaction.
kinds
string[]
Optional kind filter. Any of comment, rule, tag, category. Empty (default) returns the full timeline. Pass ['comment'] for the comment-only view (replaces the deprecated list_transaction_comments); pass ['tag'] for both add and remove tag events; pass ['comment','tag','category'] to skip rule-application churn.Only the generic kinds above are accepted at the MCP boundary — the underlying DB-level values (tag_added, tag_removed, rule_applied, category_set) will be rejected with an invalid kind error.

Example input

{ "transaction_id": "k7Xm9pQ2" }
Comment-only view (replaces list_transaction_comments):
{ "transaction_id": "k7Xm9pQ2", "kinds": ["comment"] }
All tag events (added and removed):
{ "transaction_id": "k7Xm9pQ2", "kinds": ["tag"] }
[
  {
    "id": "a1Xm2pQ9",
    "transaction_id": "k7Xm9pQ2",
    "kind": "tag",
    "action": "added",
    "actor_type": "system",
    "actor_name": "system",
    "tag_id": "t1Xm9pQ2",
    "payload": { "slug": "needs-review" },
    "created_at": "2026-03-28T06:00:00Z"
  },
  {
    "id": "a2Yn3qR0",
    "transaction_id": "k7Xm9pQ2",
    "kind": "category",
    "action": "set",
    "actor_type": "agent",
    "actor_name": "Review Agent",
    "session_id": "s9Xm2pQk",
    "payload": {
      "category_slug": "food_and_drink_groceries",
      "note": "clearly groceries"
    },
    "created_at": "2026-03-29T10:12:00Z"
  },
  {
    "id": "a3Zo4rS1",
    "transaction_id": "k7Xm9pQ2",
    "kind": "tag",
    "action": "removed",
    "actor_type": "agent",
    "actor_name": "Review Agent",
    "session_id": "s9Xm2pQk",
    "tag_id": "t1Xm9pQ2",
    "payload": { "slug": "needs-review", "note": "clearly groceries" },
    "created_at": "2026-03-29T10:12:00Z"
  }
]
kind carries the generic event family (comment, rule, tag, category) and action carries the specific event (added, removed, set, applied). Comment rows omit action because there is only one event. Actor identity is split across actor_type (user / agent / system), actor_name, and optional actor_id. When a write tool passed a session_id, it’s echoed here so you can group events by session. Rule applications set rule_id; tag events set tag_id.
Last modified on May 27, 2026