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Stone Pagamentos MCP

openfinance_list_credit_card_bills

Read-onlyIdempotent

Returns CLOSED credit card bills for a CREDIT-type account: dueDate, totalAmount, minimumPaymentAmount, allowsInstallments, plus payments[] (id, paymentDate, amount, valueType, paymentMode), payments_count, payments_total, finance charges aggregates, and a derived payment_status per bill. IMPORTANT — Brazilian Open Finance semantics: Pluggy does NOT return a paid/status field. The payment goes into the payments[] of the bill whose CYCLE contains the paymentDate (closing ≈ dueDate − 7d): pre-payment before close stays on the bill being paid; payment between close and due, or after due, lands on the NEXT bill. So payments[] on a bill commonly carries the previous bill's payment, NOT the current one's — do NOT assume this bill was paid just because payments[] is non-empty. Use the derived payment_status (PAID | OPEN | PAST_DUE_UNCONFIRMED | PAST_DUE_UNPAID): a bill is PAID when its OWN payments[] (early pre-payment) or ANY newer bill in the payload contains a payment with amount ≈ this bill's totalAmount (±R$0.50). The MOST RECENT bill that's past-due, with no own pre-payment match, cannot be confirmed via cross-bill (the next cycle hasn't closed yet) — it returns PAST_DUE_UNCONFIRMED. NEVER call such a bill 'vencida' categorically; flag that the payment may have been made between close and due and not yet reflected upstream. The full payment_status_legend is returned alongside the results. OPEN BILL & TOTAL DEBT (standardized, derived — OPT-IN): pass include_open_bill:true to ALSO get open_bill (the current not-yet-closed bill, próxima a vencer) and total_pending_debt (saldo devedor total = all pending installments), BOTH derived from PENDING transactions so they mean the same thing across connectors — use these instead of the CREDIT account's balance, whose meaning VARIES by connector (some report the open-bill partial, others the full installment debt). open_bill = { available, method (cycle_dates = real close/due dates | calendar_month_fallback = estimated, confidence:'low'), close_date, due_date, total_amount (net charges − credits), transaction_count }; plus a future_bills[] breakdown per month — LOW-confidence forward projections of PENDING installments (confidence:'low', basis), NOT authoritative bills (for closed months trust the results totalAmount). CONNECTOR ASYMMETRY: where the bank does NOT expose the open bill before closing (only closed bills, no reliable cycle dates), open_bill.available is false with a reason (connector_exposes_no_pending or open_bill_not_published) — that bill isn't retrievable by any endpoint until it closes (upstream limit of the institution's Open Finance feed, not our filter); check the bank app for the current open bill. When per-transaction billId grouping does not reconcile with the bills' totals, a bill_grouping_reliability warning is attached (trust totalAmount, do not sum by billId). Default false (the projection runs an extra accounts+transactions scan, so it's opt-in). The response opens with an account echo block ({ account_id, bank, name, number, type, item_id }) identifying WHICH card/bank these bills belong to. When more than one bank is connected, ALWAYS cross-check the echo against the card you intended to query and name the bank when presenting results — never attribute one bank's bills to another. This tool's results are bill-level summaries — NOT individual transactions, and each bill's totalAmount (from the bank) is the AUTHORITATIVE amount. To see itemized purchases/charges, use openfinance_list_transactions with the CREDIT account_id — but note creditCardMetadata.billId is a per-connector hint that can be sparse/inconsistent (e.g. Nubank), so do NOT reconstruct a bill total by summing transactions by billId. Returns a warning instead of failing if the CREDIT_CARDS product is not enabled.

Bulk support: accepts account_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
page_sizeNo
account_idYes
account_idsNo
include_open_billNo

Schema Changelog

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

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TDQS

A4.9/5.0
Behavior5/5

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

Despite readOnlyHint and idempotentHint annotations, the description adds significant behavioral context: derived payment_status semantics, cycle-based payment attribution, connector asymmetry, confidence levels for fallback estimates, and warning behavior. It does not contradict annotations and enriches them substantially.

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 long but information-dense, with every sentence contributing critical caveats. It is front-loaded with the core purpose, then elaborates. However, the wall-of-text format could benefit from bullet points or section headers for easier agent parsing, so it loses one point.

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?

Given the tool's high complexity and lack of output schema, the description covers response shape, derived fields, error handling (warning instead of failing), connector variance, payment attribution pitfalls, and practical usage. It is extraordinarily complete for an AI agent to invoke correctly.

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?

Schema coverage is 0%, so description carries full burden. It thoroughly explains include_open_bill with opt-in/default, derived values, fallback confidence, and connector asymmetry. It also explains account_ids for bulk support. Only page/page_size are not explicitly described, but those are standard and less critical.

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 verb+resource: 'Returns CLOSED credit card bills for a CREDIT-type account' and lists key fields. It explicitly distinguishes itself from sibling tools by stating results are bill-level summaries NOT individual transactions and directing to openfinance_list_transactions for itemized purchases.

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?

Provides explicit alternatives: 'To see itemized purchases/charges, use openfinance_list_transactions with the CREDIT account_id' and advises using derived total_pending_debt instead of the CREDIT account balance. It also warns never to attribute one bank's bills to another, giving clear usage guidance.

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

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially within the openfinance_* group (list vs get vs sync vs status). A few potential overlaps exist (e.g., openfinance_list_transactions vs openfinance_list_transactions_by_item, openfinance_get_account_balance vs openfinance_list_accounts), but descriptions are detailed enough to guide correct selection.

Naming Consistency4/5

The openfinance_* tools follow a consistent verb_noun pattern (e.g., openfinance_list_accounts, openfinance_get_item_status). However, non-openfinance tools (authenticate, connect, marketplace, toolkit_info) use a different style, and one tool (openfinance_list_transactions_by_item) breaks the pattern slightly. Overall readable and predictable within the primary domain.

Tool Count3/5

With 25 tools, the count is on the heavy side per the calibration rubric (16-25 feels heavy). The server covers a broad financial data domain, which justifies the number, but it may present a steep learning curve and potential overwhelm for agents.

Completeness4/5

The tool surface is comprehensive for read-only Open Finance data access: accounts, transactions, balances, bills, loans, investments, category management, connection lifecycle, and status monitoring. Minor gaps exist (e.g., no direct payment initiation, no investment transaction creation), but for the stated purpose of data and analysis, coverage is strong.