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Carrefour MCP

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openfinance_list_accounts

Read-onlyIdempotent

Returns accounts for a bank connection: BANK (checking/savings) and CREDIT (credit card) with balance, number, type, subtype, bankData, and creditData. Also returns bank (the brand/connector name like 'Nubank Empresas' — same shown in the dashboard UI) and connector_id. Note: each account's name is the legal entity that issues the account (e.g. 'Nu Pagamentos S.A. - Instituição de Pagamento'), which is not the same as the brand — when referring to the bank in user-facing text, use bank. OMIT item to list accounts across ALL linked banks at once — the response aggregates every connection's accounts into results, each row tagged with its own bank/connector_id/item_id (use this when the user asks for 'my accounts/cards' without naming a bank). Pass item to target a single bank (response carries bank/connector_id/item_id at the root). CREDIT (credit card) balance: its meaning is CONNECTOR-DEPENDENT — some banks report the current open-bill partial, others the full revolving/installment debt — so do NOT treat balance as 'this month's bill'. The open billing cycle is defined by creditData.balanceCloseDate (when it closes) / balanceDueDate (when it's due). For a standardized open-bill amount and total debt that mean the same across connectors, use openfinance_list_credit_card_bills (open_bill + total_pending_debt, derived from PENDING transactions); closed bills come from that same tool's results. A CREDIT row may carry creditData.usedAmount (how much of THIS card's limit the bank reports as consumed) and a balance_notice. balance_notice means balance came back 0,00 while the bank's own payload indicates an outstanding amount — some issuers never fill the card's consolidated balance field. When it is present, do NOT tell the user the card has nothing to pay: read the amount from openfinance_list_credit_card_bills instead. bankData.closingBalance and automaticallyInvestedBalance are provider-reported extras that can LAG right after a connection is first created: the bank may publish the connection as UPDATED before those derived fields converge, so they can briefly carry a stale/phantom value that a force sync (openfinance_force_sync) reconciles. The account's own balance is authoritative — treat those two as hints until they agree with it. May include a provider_incident block when the Open Finance provider has an OPEN incident affecting a bank in this response: balances and credit limits may be unreliable (incomplete or wrong, e.g. a credit limit near 1,00) even with the connection UPDATED, until the provider recovers. Do not present those values as real. May include an identity_notice when the SAME account (same number) arrives via two connections stamped with DIFFERENT owner/taxNumber: in Open Finance those fields reflect each connection's CONSENT HOLDER (e.g. a joint account consented by both holders), so dedupe by account number before summing balances and do not attribute ownership by owner/taxNumber for those accounts.

Bulk support: accepts item_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemNo
typeNo
item_idNo
item_idsNo

Schema Changelog

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

  1. Added
  2. Removed
  3. Added
  4. Removed
  5. Changed2 schema fields changed
    • addedInput schema / properties / item_id
      Added value: +{
+  "type": "string"
+}
    • addedInput schema / properties / item_ids
      Added value: +{
+  "items": {
+    "type": "string"
+  },
+  "type": "array"
+}
  6. Added
  7. Removed
  8. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already mark the call read-only, idempotent, and non-destructive, and the description adds substantial behavioral context: connector-dependent credit balances, `balance_notice` semantics, lagging `bankData` fields after initial connection, provider-incident unreliability, and consent-holder/identity notices. These caveats go far beyond the structured annotations and materially change how an agent should interpret results.

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?

The purpose is front-loaded and the remaining content is organized into clear operational caveats, each of which earns its place. Though long, the length is justified by the number of genuine behavioral gotchas an agent must know to use the tool correctly.

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 tool with no output schema, the description covers return fields, field semantics, edge cases, cross-tool routing, and bulk execution exceptionally well. The only notable gap is explicit documentation of the `item_id` parameter and the `type` filter, which are left mostly to inference.

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?

With 0% schema description coverage, the description must carry the parameter burden. It documents `item` (single bank vs omitted for all banks) and `item_ids` (bulk), but it does not explicitly document `item_id` and only implies `type` filtering by naming BANK/CREDIT, leaving two of four parameters under-specified.

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 opening sentence names the exact action and resource ('Returns accounts for a bank connection') and lists the account kinds and returned fields. It also distinguishes the account name from the bank brand, preventing a common misinterpretation, and points to a sibling tool for standardized bill amounts.

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 gives explicit selection rules: omit `item` for an all-banks account list, pass `item` to target one bank, and use `openfinance_list_credit_card_bills` for standardized open-bill/debt values. It also provides a concrete user-intent trigger ('my accounts/cards' without naming a bank) and warns when not to rely on CREDIT `balance`.

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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