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SafraPay 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. Added
  4. Removed
  5. 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"
+}
  6. Added
  7. Removed
  8. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint, idempotentHint, destructiveHint directly consistent with a read-only analysis tool), description adds critical behaviors: 5000/account cap with truncated flag, provider_incident causing incomplete data, and the note that reconnecting won't fix it. This provides essential transparency for reliability.

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 front-loaded with main purpose. Uses structured sentences with clear separations for details. Every sentence adds value, though it could be slightly more compact without losing clarity.

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?

With no output schema, description outlines key return elements (totals, monthly evolution, top expenses, per-account breakdown, truncation, provider_incident). It covers main use cases and expected data, providing sufficient context for an agent to understand tool outputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, so the description carries full burden. It explains item as connector_id/name/item_id, from/to as ISO dates, granularity defaults and effects, detail sub-options, type filter, and bulk item_ids. top_n is implied via output. Most parameters are meaningfully described.

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?

Description clearly states it provides consolidated cash-flow analysis for a whole bank connection, aggregating transactions across accounts. It explicitly distinguishes from sibling tools by noting it eliminates the need to call openfinance_list_accounts or carry account IDs, making its unique value apparent.

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?

Description gives explicit use cases like 'fluxo de caixa' and 'maiores gastos/recebimentos', and explains when to use granularity and detail options. It mentions bulk support but lacks explicit comparison to alternatives like openfinance_list_transactions, though context 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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