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Toro 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

A5/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint=false), the description discloses critical behavioral traits: the 5000/account scan cap with truncated flag, the provider_incident block and its implications on data completeness, and the difference between compact monthly summary and raw granularity. It also explains the default behavior and enrichment options.

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?

Although long, every sentence earns its place by adding operational detail, defaults, caveats, and usage examples. The text is front-loaded with the main purpose, then logically flows through parameters, granularity, and edge cases. It avoids repetition and is structured for quick scanning.

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?

With no output schema, the description fully explains return values: total entradas/saídas/saldo_liquido, monthly evolution (`por_mes`), top receipts/expenses, per-account breakdown, optional raw rows, and the `truncated` and `provider_incident` flags. It also covers connection-level behavior and bulk execution, making the tool's full behavior understandable.

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?

Schema description coverage is 0%, so the description carries the full burden for parameter meaning. It explains `item` as connector_id/name/item_id, `from`/`to` as ISO dates, `granularity` and `detail` enums with concrete values, `type` filtering, and bulk support via `item_ids`. It also implies `top_n` via 'largest N each' and covers all key parameters.

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 states a specific verb and resource: 'Consolidated cash-flow analysis for a whole bank CONNECTION over a period, in ONE call.' It clearly distinguishes itself from siblings by noting you do not need to call openfinance_list_accounts first and that it resolves accounts internally, which differentiates it from openfinance_list_transactions and other item-specific tools.

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?

Explicit guidance is provided: use for 'análise anual/mensal', 'fluxo de caixa', 'entradas e saídas', 'maiores gastos/recebimentos', and it tells when to use the raw granularity ('only when itemized rows are needed'). It also contrasts with the alternative of calling openfinance_list_accounts first, making the decision clear.

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
Disambiguation4/5

Each Open Finance resource has a clearly named list/get pair, and connection status vs provider status vs force sync are distinct. The main ambiguity is between list_accounts (which already carries balances) and get_account_balance, and between list_transactions and list_transactions_by_item, which requires reading the descriptions carefully.

Naming Consistency4/5

The openfinance_* tools follow a consistent verb_noun pattern (list_*, get_*, update_*, force_sync, search_*). Exceptions like marketplace, toolkit_info, and openfinance_provider_status break the pattern slightly, but the two logical groups are predictable internally.

Tool Count3/5

At 25 tools this is on the heavy end of the scale. Most tools have a real purpose, but several list/get pairs and the multi-purpose marketplace mega-tool could be consolidated without losing functionality, making the overall surface feel larger than strictly necessary.

Completeness4/5

The Open Finance surface is impressively broad: connections, accounts, balances, transactions, credit-card bills, loans, investments, categorization, sync, provider health, and connector search are all covered. Minor gaps like a single-transaction getter or a consolidated statement export force agents to assemble data with extra calls, but no critical workflow is blocked.

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