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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.

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  13. 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"
      +}
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  16. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description goes far beyond the annotations by revealing important behavioral nuances: connector-dependent `balance` semantics, lagging `bankData` fields, `provider_incident` unreliability, and `identity_notice` deduplication requirements. It also warns against presenting unreliable or stale values as real. This is rich behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, but it is extremely long and unstructured, almost wall-of-text style. Every sentence carries valuable caveats, but the density and lack of bullet points or section breaks makes it harder for an agent to parse efficiently.

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 tool with no output schema and a complex response involving multiple account types, connector-specific behaviors, and reliability notices, the description is remarkably complete. It covers return fields, filter behavior, bulk execution, semantic pitfalls, and alternatives, leaving very little for an agent to guess.

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 description coverage is 0%, so the description must compensate, and it largely does. It explains `item` (omit for all connections, pass to target one), the `type` semantics via BANK/CREDIT categories, and `item_ids` for bulk execution. However, `item_id` is not explicitly documented as a parameter—it is only indirectly inferable from the output row tagging and `item_ids`.

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, unambiguous statement: it returns accounts for a bank connection (BANK and CREDIT) with detailed fields. It clearly differentiates itself from siblings like openfinance_list_credit_card_bills, which the description explicitly references for standardized bill data.

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 when-to-use guidance: omit `item` for accounts across all linked banks, pass `item` for a single bank, and use openfinance_list_credit_card_bills when a standardized open-bill amount or total debt is needed. It also explains how to handle edge cases like `balance_notice` and provider incidents.

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

A3.9/5.0
Disambiguation3/5

Most openfinance_* tools target distinct resources and actions, but several overlap in purpose: list_transactions vs list_transactions_by_item, get_credit_card_bill vs list_credit_card_bills, and multiple connection/status tools expose reconnect URLs. The long descriptions help, but the boundaries are not always immediately obvious.

Naming Consistency4/5

The openfinance_* tools follow a consistent list_/get_ verb_noun pattern and share a clear prefix. The smaller platform cluster is less consistent — marketplace, connect, authenticate, show_version, toolkit_info — mixing nouns, bare verbs, and snake_case, but it is a minor deviation overall.

Tool Count3/5

At 25 tools, this sits at the heavy end of acceptable. The Open Finance surface is broad enough to justify many of them, but there is redundancy (e.g. list_transactions_by_item largely wraps list_transactions plus account resolution) and a separate platform-management cluster that makes the set feel sprawling.

Completeness4/5

The Open Finance domain is well covered: connection lifecycle, accounts, balances, transactions, credit-card bills, loans, investments, categories, and provider status are all present, and data flows connect properly between tools. Minor gaps exist, such as no single-transaction fetch or dedicated prompt-management tools, but the marketplace tool fills those roles.