Santander MCP

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

Name	Required	Description	Default
`to`	No
`from`	No
`item`	No
`type`	No
`top_n`	No
`detail`	No
`item_id`	No
`item_ids`	No
`granularity`	No

TDQS

A4.8/5.0

Behavior5/5

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

Adds rich behavioral context beyond the read-only and idempotent annotations: internal account resolution, 5000/account scan cap with truncated flag, provider_incident block with data integrity caveats, and details on compact vs raw output. 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?

Long but information-dense; every sentence adds value. Uses backticks and examples effectively. Slightly verbose with repeated terms, but well-structured and front-loaded with the main purpose.

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?

Comprehensive for a complex tool with no output schema: describes return structure (compact summary, por_mes, top_despesas, by_account), raw behavior, incident caveats, and bulk execution. Fully equips an agent to invoke correctly.

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?

Despite 0% schema coverage, the description explains most parameters: item, from/to, granularity, detail, type, and item_ids for bulk. However, top_n and item_id are only implied (top_despesas, bulk support), and some enum values (compact vs monthly) are not fully mapped. Still, it compensates well.

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 across a whole connection, resolving accounts internally and fanning out transactions. It explicitly distinguishes itself from openfinance_list_accounts and explains the item targeting, making its purpose unambiguous and differentiated from sibling 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?

Provides explicit guidance on when to use it (e.g., 'análise anual/mensal', fluxo de caixa, maiores gastos), when to use raw granularity, and how to combine with detail settings. It also notes bulk support and omitting item for all banks, offering clear context for selection.

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

A3.9/5.0

Disambiguation3/5

The openfinance_* tools are mostly distinct by resource and action, but several pairs create ambiguity: openfinance_get_item_status vs openfinance_provider_status, openfinance_list_transactions vs openfinance_list_transactions_by_item, and the monolithic marketplace tool overlaps with top-level report_bug and toolkit_info. Descriptions do clarify the differences, but an agent selecting by name alone could easily choose the wrong tool.

Naming Consistency3/5

The openfinance_* family follows a mostly consistent verb_noun pattern (list_accounts, get_balance, update_transaction_category), which is good. However, top-level tools mix bare verbs, nouns, and verb_noun forms (authenticate, connect, marketplace, show_version, toolkit_info), and openfinance_provider_status breaks the verb-first pattern. The naming is readable but not uniform across the whole set.

Tool Count3/5

25 tools sits right at the heavy boundary, though the server covers two domains: mcp.ai platform management and Open Finance data access. Some tools could be consolidated (list_transactions vs list_transactions_by_item, get_item_status vs provider_status), and marketplace is a monolithic super-tool that bundles many sub-capabilities. Overall the count is defensible but slightly bloated.

Completeness4/5

The Open Finance surface is thorough: accounts, balances, transactions, credit card bills, loans, investments, connection management, sync, category updates, and provider health are all covered. Minor gaps exist, such as no investment detail beyond the list and connection actions being URL-based rather than first-class tools, but there are no dead ends for typical read/aggregation workflows.

openfinance_list_transactions_by_item

Input Schema

TDQS

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