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Caixa Econômica Federal MCP

by io.github.mcp-dir

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. 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"
+}
  4. Added
  5. Removed
  6. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds substantial behavioral context: connector-dependent balance meaning, balance_notice semantics, provider_incident reliability caveats, identity_notice dedupe instructions, and bankData lag. There is no contradiction with annotations.

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 description is long but well-structured and front-loaded: the first sentence gives the core result, and subsequent paragraphs group caveats by topic. Every paragraph adds operational value, from credit balance caveats to bulk support.

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?

Despite no output schema, the description covers the critical interpretation pitfalls: authoritative balance, balance_notice fallback, provider incidents, identity dedupe, bankData lag, and the recommended alternative for standardized bill data. This is sufficient for an agent to invoke the tool and correctly interpret results.

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?

Schema coverage is 0%, so the description carries the burden. It compensates well for the key parameters by explaining why omitting item is meaningful, what passing item does, and that item_ids enables batched execution. However, the singular item_id parameter is left undocumented and type is only implied as a filter rather than explicitly described.

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?

States a specific verb and resource: returns accounts for a bank connection, distinguishing BANK and CREDIT and enumerating the fields returned. This is immediately distinguishable from sibling tools like openfinance_get_accounts_detail and openfinance_get_account_balance.

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?

Explicitly explains when to omit item to list across all banks, when to pass item for a single bank, and when to use this tool for 'my accounts/cards' without naming a bank. It also directs standardized bill amounts to openfinance_list_credit_card_bills, giving clear when-not guidance and naming an alternative.

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.

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