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Caixa Econômica Federal MCP

openfinance_list_transactions

Read-onlyIdempotent

Returns transactions for a bank account (BANK or CREDIT type). For CREDIT (credit card) accounts, this is the ONLY way to get itemized transactions (purchases, subscriptions, etc.). Each credit card transaction MAY carry creditCardMetadata.billId pointing at a bill from openfinance_list_credit_card_bills, but this is a per-connector HINT, not authoritative: some connectors (e.g. Nubank) populate it sparsely (many transactions and installments arrive with no billId) or inconsistently (the same payment tagged to more than one bill). Do NOT reconstruct a bill's total by summing transactions by billId — the bill's own totalAmount from openfinance_list_credit_card_bills is the source of truth. CREDIT PENDING vs POSTED varies by connector: where the bank exposes future-dated status:'PENDING' installments, those represent the OPEN bill plus future bills (future months); where it does NOT, only the last closed bill's POSTED items appear until ~closing. Same query, different coverage per bank (upstream). To get a standardized open-bill total / total debt regardless, use openfinance_list_credit_card_bills (open_bill / total_pending_debt). SCHEDULED (future-dated) ROWS: results are ordered by date DESCENDING, and on a card with long installment plans the TOP of the list is the FUTURE — rows dated months ahead are scheduled installments of purchases already made, not new purchases. Every such row is flagged scheduled:true, the response carries scheduled_count and a notice naming the most recent row that actually happened. NEVER read the first row as 'the latest purchase' without checking scheduled. To list only what already happened, pass to = today. Supports from/to date filters (ISO YYYY-MM-DD) and an optional keyword filter via search_queries (case- and accent-insensitive substring match against description and merchant name, OR semantics across multiple terms). When search_queries is set the tool aggregates up to 5000 transactions within from/to before filtering — narrow from/to if truncated:true is returned. PAGINATION: OMIT both page and page_size (the default) to get ALL transactions in the from/to range in one call — the tool auto-paginates the upstream and returns them under a single logical page (page:1, totalPages:1), up to a 5000 ceiling (truncated:true + warning if exceeded, then narrow from/to). Passing page and/or page_size switches to MANUAL pagination: you get one page (page_size items, default 50, max 500; page defaults to 1) with the REAL total/totalPages, so page_size:5 alone returns the first 5 with totalPages telling you how many pages remain. On upstream errors, returns { total:0, results:[], warning, error } instead of throwing. detail controls how much per-row data you get (default 'compact' = slim, cheap). Use detail:'rich' to enrich each row (when the bank connector provides it) with merchantInfo (estabelecimento: businessName/razão social, cnpj, cnae, category — useful for auto-classifying spending) and extra creditCardMetadata fields: billId (a per-connector HINT toward the transaction's bill — sparse/inconsistent on some connectors like Nubank, so do NOT sum by it to get a bill total; use the bill's totalAmount instead), billForecastDate, cardNumber, purchaseDate, payeeMCC, feeType/feeTypeAdditionalInfo, otherCreditsType/otherCreditsAdditionalInfo. billForecastDate ("YYYY-MM") is the counterpart of billId for the OPEN cycle: PENDING transactions have NO billId (the bank only mints it once the bill closes), so this is the only field telling you which bill a pending purchase will land in — its month OFFSET is per-connector (some banks month+1, others month+0), so surface it as-is and do not derive a due date from it. cardNumber (last 4 digits) separates the primary cardholder's charges from an additional card's when several cards share one account_id. Use detail:'raw' to get the FULL untouched Pluggy transaction object (everything Pluggy returns, un-normalized — heaviest, for when you need a field we don't project). 'rich'/'raw' add tokens per row and coverage varies by bank/Open Finance, so keep the default for normal listings. For the card's statement closing/due dates use openfinance_list_accounts (creditData.balanceCloseDate / balanceDueDate). The response opens with an account echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH account/bank these transactions belong to. When more than one bank is connected, ALWAYS cross-check the echo against the account you intended to query and name the bank when presenting results — never attribute one bank's transactions to another. If total is 0 for a CREDIT account, check the connection health via openfinance_get_item_status — statusDetail.creditCards.isUpdated: false means the credit card sync failed and a force sync (openfinance_force_sync) or reconnection may be needed. May include a provider_incident block when the Open Finance provider has an OPEN incident affecting a connected bank: transactions may come back incomplete or wrong until the provider recovers, and reconnecting does not fix it.

Bulk support: accepts account_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
pageNo
detailNo
page_sizeNo
account_idYes
account_idsNo
search_queriesNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description goes far beyond the annotations, disclosing non-obvious behaviors: descending date ordering with future-dated scheduled rows, scheduled_count/notice fields, auto-pagination vs manual pagination semantics, error-shape (total:0 results with warning instead of throwing), provider_incident blocks, and connector-specific billId sparseness. These are operational details that materially affect how an agent interprets results.

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?

The description is extremely information-dense but also long and somewhat repetitive, especially the billId caveat and do-not-sum-by-total warning, which appear twice. However, it is well structured with front-loaded core behavior and clearly labeled sections like PAGINATION and SCHEDULED, so it earns a high score despite minor redundancy.

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 complex 8-parameter tool with no output schema, the description provides complete context: expected response components (account echo, scheduled_count, notice, provider_incident), error shape, pagination ceiling, detail tradeoffs, and cross-tool references for related data. Nothing critical is left for the agent to guess.

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?

With schema description coverage at 0%, the description compensates fully. It explains from/to filters with ISO format, search_queries semantics (case/accent-insensitive substring, OR across terms), page/page_size two-mode behavior, detail levels compact/rich/raw, and account_id/account_ids batch support. It also explains outputs affected by each detail level, such as merchantInfo and creditCardMetadata fields.

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 action and subject: 'Returns transactions for a bank account (BANK or CREDIT type).' It also establishes a unique scope by declaring that for CREDIT accounts this is 'the ONLY way to get itemized transactions,' clearly distinguishing it from siblings like openfinance_list_credit_card_bills and openfinance_list_transactions_by_item.

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 provides explicit alternative routing: use openfinance_list_credit_card_bills for a standardized open-bill total, openfinance_list_accounts for statement closing/due dates, and openfinance_get_item_status/openfinance_force_sync when credit sync fails. It also warns when NOT to trust the first row without checking the scheduled flag, and when to narrow date filters on truncation.

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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TDQS

A4.2/5.0
Disambiguation4/5

Most tools have distinct purposes, especially with the openfinance_ prefix grouping banking operations. However, pairs like openfinance_list_accounts vs openfinance_get_accounts_detail and openfinance_get_credit_card_bill vs openfinance_list_credit_card_bills could cause minor confusion, though descriptions help.

Naming Consistency5/5

Tools consistently use snake_case with a clear verb_noun pattern. Open finance tools all start with openfinance_, and utility tools use simple verbs like authenticate, connect, report_bug. No mixing of conventions.

Tool Count3/5

At 24 tools, the count is on the higher side of the borderline range. The server combines platform management (6 tools) and banking operations (18 tools), which justifies the number, but it feels slightly heavy for a single server.

Completeness5/5

The tool surface covers all major banking operations (accounts, transactions, credit cards, investments, loans) and includes essential maintenance tools (sync, status, disconnect, search connectors). Platform management is also comprehensive with authentication, marketplace operations, and diagnostics.