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Porto Bank MCP

by io.github.mcp-dir
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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

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

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral details beyond annotations: scanning caps at 5000 per account with a truncation flag, possibility of a provider_incident block that may make totals/rows incomplete, and bulk support. 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 verbose but front-loaded with the core purpose. Each paragraph adds essential information for a complex tool with 9 parameters and multiple behaviors. Could be slightly more streamlined, but every sentence earns its place, making it efficient overall.

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 there is no output schema, the description thoroughly explains the return structure: compact summary with totals, monthly evolution, top expenses/revenues, per-account breakdown, and raw mode options. It also covers provider incidents, truncation, and bulk support. This is highly complete for such a feature-rich 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?

Schema description coverage is 0%, so the description carries the full burden. It explains all 9 parameters: 'item' can be connector_id/connector_name/item_id; 'from'/'to' are ISO dates; 'granularity' options ('monthly' for compact summary, 'raw' for rows); 'detail' options with their effects; 'type' filters; 'top_n' implied; and 'item_ids' for bulk. This is comprehensive and goes well beyond what the schema alone provides.

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 performs consolidated cash-flow analysis for a whole bank connection in one call. It specifies the resource (transactions) and action (list/analyze), and distinguishes from sibling tools by noting users do not need to call openfinance_list_accounts first, implying a higher-level aggregated approach.

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?

Explicitly states when to use: for 'análise anual/mensal', 'fluxo de caixa', etc. Provides guidance on when to omit the 'item' parameter to analyze all linked banks and when to set granularity to 'raw' for itemized rows. However, it does not explicitly name the sibling tool openfinance_list_transactions as an alternative for when only raw transactions are needed without aggregation, which is a minor gap.

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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