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Banco do Brasil MCP

by io.github.mcp-dir

openfinance_list_transactions_by_item

Read-onlyIdempotent

Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call. Resolves the connection's accounts internally and fans out their transactions, so you do NOT need to call openfinance_list_accounts first nor carry account_id uuids between calls. Pass item (connector_id, connector_name or item_id) to target one bank, or OMIT it to analyze ALL linked banks at once. from/to are ISO dates (YYYY-MM-DD). Default granularity:'monthly' returns a COMPACT summary (no raw rows): total entradas, saídas, saldo_liquido, monthly evolution (por_mes), and top_despesas/top_recebimentos (largest N each), plus a per-account breakdown (by_account). Use this for 'análise anual/mensal', 'fluxo de caixa', 'entradas e saídas', 'maiores gastos/recebimentos'. Set granularity:'raw' to ALSO get every consolidated transaction (heavier — only when itemized rows are needed); combine with detail:'rich' to enrich those rows with merchantInfo (cnpj/cnae/businessName/category) + extra creditCardMetadata (billId, purchaseDate, fees), or detail:'raw' for the full untouched Pluggy object per row, when the connector provides them. type filters BANK or CREDIT accounts. On a connection with many transactions the scan caps at 5000/account and flags truncated:true. May include a provider_incident block when the Open Finance provider has an OPEN incident affecting a connected bank: the totals/rows may be incomplete or wrong until the provider recovers, and reconnecting does not fix it.

Bulk support: accepts item_ids for batched execution.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
itemNo
typeNo
top_nNo
detailNo
item_idNo
item_idsNo
granularityNo

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint), the description adds important behaviors: scanning caps at 5000/account with truncation flag, provider incident block affecting data completeness, and that reconnecting doesn't fix incidents. This provides rich behavioral context.

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 fairly long but well-structured, starting with main purpose, then parameter details, then special behaviors. Every sentence adds value, though it could be slightly trimmed without losing clarity.

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 no output schema, the description still describes the return structure (total entradas, saídas, por_mes, top lists, by_account) and caveats like truncation and provider incidents. This is very complete for a complex tool.

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 0% schema description coverage, the description fully compensates by explaining all key parameters: item (as connector_id/name or item_id, omit for all banks), from/to as ISO dates, granularity (monthly vs raw), detail (compact/rich/raw), type filtering, top_n implicit in top_despesas/recebimentos, and item_ids for bulk.

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 clearly states it provides consolidated cash-flow analysis for a whole bank connection in one call, resolving accounts internally and fanning out transactions. It distinguishes from sibling tools like openfinance_list_accounts by noting you don't need to call that first.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool (for cash-flow analysis, with example Portuguese phrases) and explains parameter choices like granularity and detail. However, it lacks explicit comparisons to other transaction tools like openfinance_list_transactions, so not a 5.

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

A4/5.0
Disambiguation4/5

Most tools target distinct resources and operations (balance, accounts, loans, investments, connections, provider status), but credit card bill handling is split across three overlapping tools (get_credit_card_bill, list_credit_card_bills, list_transactions), which could cause misselection. The platform-level tools (authenticate, connect, marketplace, etc.) are clearly distinct from the finance tools.

Naming Consistency3/5

The openfinance_* tools mostly follow a verb_noun snake_case pattern (list_accounts, get_account_balance, update_transaction_category), but a few deviate (openfinance_provider_status, openfinance_search_bank_connectors). The non-prefixed platform tools break the pattern entirely with mixed styles: verbs (connect, authenticate), nouns (marketplace), and noun_verb (report_bug, show_version).

Tool Count3/5

At 25 tools, this sits at the high end of reasonable scope. Each Open Finance tool maps to a specific endpoint or workflow, and the platform tools are needed for the MCP meta-layer, but the sheer number makes the set feel heavy and harder to navigate.

Completeness4/5

The Open Finance surface is thorough: connection lifecycle, accounts, balances, transactions, credit card bills, loans, investments, categories, and provider health. Minor gaps exist (e.g., no webhook management, no bulk CSV export), but core workflows are well covered and there are no dead ends.

Resources