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Banco Bmg 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

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral details: truncation at 5000/account, provider_incident block affecting data completeness, and behavior of granularity/detail modes. No contradictions 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.

Conciseness4/5

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

The description is structured logically: purpose, internal mechanics, parameter details, use cases, caveats. While long, every sentence adds value. Could be slightly more concise, but well-organized.

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?

Given no output schema, the description explains return values for both granularity modes, including truncation and provider_incident indicators. It covers bulk support and filter options. Does not detail structure of by_account or por_mes, but overall sufficient for a tool with 9 parameters.

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 explains most parameters (item, from, to, granularity, detail, type, item_ids, top_n is implied but not explicitly tied to top_n parameter). However, the interaction between granularity and detail is slightly confusing, and top_n parameter is not explicitly mentioned.

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 the tool's purpose: 'Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call.' It distinguishes from siblings by noting that it resolves accounts internally, eliminating the need for openfinance_list_accounts, and contrasts with openfinance_list_transactions by handling multiple accounts without explicit account IDs.

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 provides explicit usage scenarios: 'análise anual/mensal', 'fluxo de caixa', etc. It explains when to omit item to analyze all banks and when to set granularity to raw. However, it does not explicitly contrast with sibling openfinance_list_transactions, though the distinction is implied.

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
Disambiguation3/5

The openfinance_ tools are mostly distinct by resource/action, but there are several overlapping pairs: list_accounts vs get_accounts_detail, list_credit_card_bills vs get_credit_card_bill, list_transactions vs list_transactions_by_item, and connect vs toolkit_info vs openfinance_list_connections. The descriptions help disambiguate, but an agent could still misselect between these related tools.

Naming Consistency4/5

The core banking tools consistently follow an openfinance_<verb>_<noun> pattern, which is a strong and readable convention. The generic platform tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) break that pattern and use mixed naming styles, creating two distinct naming tiers within the same server.

Tool Count3/5

25 tools sits at the upper borderline of what feels reasonable for one server. The Open Finance domain justifies many read/query tools, but the inclusion of platform meta-tools like marketplace, connect, toolkit_info, report_bug, and show_version inflates the count beyond a tightly focused bank-data scope.

Completeness4/5

The Open Finance surface is largely complete: connectors, sync, disconnect, accounts, balances, transactions, categorization, credit card bills, loans, investments, and provider status are all covered. Minor gaps exist, such as the lack of a dedicated investment detail endpoint and limited consent/permission introspection, but agents can work around these with the existing tools.

Resources