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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

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

A4.9/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint=true and idempotentHint=true. Description adds significant behavioral context: truncation at 5000/account with truncated:true flag, provider_incident block when provider has open incident, and bulk support via item_ids. No contradiction 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?

Description is lengthy but well-structured: starts with core purpose, then parameter details, then special behaviours. Every sentence adds valuable info, though some repetition (e.g., detail options) could be tightened. Still, remains effective for agent understanding.

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?

Despite 9 parameters, no output schema, and moderate complexity, the description covers: output format (compact summary, raw rows, per-account breakdown), truncation, provider incidents, bulk execution, and example use cases. Provides sufficient context for accurate tool selection and invocation.

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 has 0% description coverage, but the description fully compensates by explaining all parameters: item (supports multiple identifier types), from/to (ISO dates), granularity (monthly vs raw), detail (compact/rich/raw), type (BANK/CREDIT), top_n, and item_ids. Also explains defaults and effects.

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 performs consolidated cash-flow analysis for a whole bank connection in one call, resolving accounts internally. It distinguishes from sibling tools like openfinance_list_accounts and openfinance_list_transactions by explaining it avoids separate steps.

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?

Explicitly says when to use (e.g., annual/monthly analysis, cash flow, income/expenses) and when not (no need to call list_accounts first). Provides alternative: omit item to analyze all banks. Also advises when to set granularity to 'raw' only if itemized rows are needed.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation or data type (accounts, transactions, bills, loans, investments, connections, etc.) with no ambiguity. Even closely related tools like openfinance_list_transactions and openfinance_list_transactions_by_item are clearly differentiated by scope and output format.

Naming Consistency3/5

The majority of tools follow the 'openfinance_' prefix for banking operations, but utility tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) break this pattern, creating an inconsistent mix. However, the convention is still readable and the utilities are clearly distinct.

Tool Count4/5

25 tools is on the high side but well-justified by the breadth of Open Finance data types (accounts, transactions, credit cards, bills, loans, investments) and supporting operations (sync, status, search, updates). A few tools could potentially be merged, but overall the number is reasonable for the domain.

Completeness4/5

The tool surface covers the core Open Finance workflows: listing, reading details, syncing, updating categories, and checking provider status. Minor gaps exist (e.g., no tool to create or delete accounts/transactions), but these are external constraints. The set enables most user-facing financial queries and actions.

Resources