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by io.github.mcp-dir

openfinance_search_bank_connectors

Read-onlyIdempotent

Searches the available bank connectors by name (pass keywords[], e.g. ['nubank','btg']) and returns, per match: the connector id, whether it's Open Finance or API (access), PF/PJ (audience), the user's already-linked connections (and accounts when include_accounts=true), and a ready connect_url with the bank pre-selected. Some non-Open-Finance credential connectors carry a caveat warning that they don't auto-update (needs periodic manual reconnection) — surface it so the user can prefer the institution's Open Finance connector for automation. Honors the user's plan (a PF plan hides PJ banks; a PJ plan covers BOTH — PF and PJ banks connect and count under the same plan). Call this BEFORE connecting to hand the user a one-click link to the right bank. keywords[] is REQUIRED — without it returns a hint (never dumps the whole catalog).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsNo
include_accountsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added
  2. Removed
  3. Added
  4. Removed
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  6. Removed
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  8. Removed
  9. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, non-destructive. The description adds important behavioral context: returns a hint if no keywords, non-Open-Finance connectors have a caveat, and the tool honors user plan (PF hides PJ banks, PJ covers both). No contradictions.

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 somewhat long but front-loaded with the main purpose and then details. It is well-structured, though slightly verbose. Every sentence adds value, so it earns its place.

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 the absence of an output schema, the description thoroughly explains what is returned: connector id, access type, audience, linked connections, accounts (if include_accounts), and connect_url. It also covers plan behavior and caveats, making the tool fully understandable.

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?

With 0% schema coverage, the description compensates by explaining that 'keywords' is an array of strings (e.g., ['nubank','btg']) and is REQUIRED despite not being marked as such. It also explains the 'include_accounts' toggle. It adds meaning beyond the raw schema.

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 identifies the verb 'searches', the resource 'bank connectors', and the scope 'by name'. It lists the return fields and special caveats, and it distinguishes itself from sibling tools like 'connect' by specifying it is the preparatory step.

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?

The description explicitly states when to use the tool: 'Call this BEFORE connecting to hand the user a one-click link to the right bank.' It also implies not to call without keywords. However, it does not explicitly mention alternatives among siblings, but the context is 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

A4/5.0
Disambiguation3/5

The openfinance_* tools are mostly distinct resource/action pairs, but several boundaries blur: openfinance_list_transactions vs openfinance_list_transactions_by_item vs openfinance_get_credit_card_bill(include_transactions) all return transaction data, and openfinance_get_item_status / openfinance_provider_status / openfinance_list_connections all concern connection health. The monolithic marketplace tool also bundles search/describe/invoke/install/prompt-library operations, adding further ambiguity.

Naming Consistency4/5

The 19 openfinance_* tools follow a clean snake_case verb_noun pattern (list_accounts, get_item_status, update_transaction_category), but the six platform tools break it with bare verbs (authenticate, connect) and noun-style names (marketplace, toolkit_info). The split is namespace-based and still readable, so it is only a minor inconsistency.

Tool Count3/5

25 tools is on the heavy side, but the server spans two domains: an Open Finance banking surface (accounts, bills, loans, investments, connections) and a marketplace/platform layer (auth, search, prompts, bug reporting). Many openfinance tools are necessary for that breadth, though the count is high enough to feel bloated.

Completeness4/5

The Open Finance surface is nearly complete: connections can be searched, listed, disconnected, force-synced, and health-checked; accounts, transactions, bills, loans, and investments all have read/detail paths; transaction categories can be updated. Minor gaps exist, such as no granular marketplace tools outside the monolithic marketplace tool and no single-transaction detail endpoint, but core workflows do not dead-end.

Resources