Skip to main content
Glama

Necton MCP

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

TDQS

A4.7/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations (readOnlyHint, idempotentHint, destructiveHint). It explains plan-based filtering (PF vs PJ), the caveat warning for non-Open-Finance connectors, and the behavior when keywords are omitted (returns a hint instead of dumping the catalog).

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 relatively long but each sentence adds value. It is well-structured, starting with the main function, then return fields, then caveats, plan behavior, usage guidance, and a note about the 'keywords' parameter. Slightly verbose but justified by the complexity.

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?

Without an output schema, the description thoroughly explains the return values (connector id, access, audience, connections, accounts, connect_url) and special cases (caveat, plan filtering, missing keywords). This provides sufficient context for an AI agent to understand the tool's behavior completely.

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?

With 0% schema description coverage, the description fully compensates. It explains that 'keywords' is an array of bank names (with examples) and that it's REQUIRED, despite the schema not marking it as required. It also explains 'include_accounts' as a boolean to include accounts in the response.

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 searches bank connectors by name with specific keywords, and details the returned fields (connector id, access, audience, connections, accounts, connect_url). This distinguishes it from siblings like 'connect' and 'marketplace' which have different purposes.

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 advises to call this tool BEFORE connecting to provide a one-click link, and mentions preferring Open Finance connectors for automation. While it doesn't name specific alternatives, the context is clear enough for an AI agent to decide when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Necton MCP toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., force_sync vs get_item_status, list_accounts vs get_accounts_detail). Minor overlap exists between list_transactions and list_transactions_by_item, and between get_account_balance and list_accounts (which also contains balance), but descriptions clarify when each should be used.

Naming Consistency4/5

All openfinance_* tools follow a consistent snake_case verb_noun pattern (list, get, force_sync, disconnect, update). The generic tools (authenticate, connect, marketplace, report_bug, show_version, toolkit_info) are also lowercase with underscores where needed, though they lack the openfinance prefix. No mixing of camelCase or chaotic patterns, so mostly consistent with minor deviation.

Tool Count3/5

25 tools is on the heavy side for a single server, but justified given the breadth of Open Finance operations (accounts, transactions, bills, loans, investments, connections, categories, provider status). The count is borderline heavy but not excessive for the domain, though some consolidation could be possible (e.g., merging get_account_balance into list_accounts).

Completeness5/5

The tool surface covers the full lifecycle for financial data: listing, getting details, forcing syncs, disconnecting, updating categories, checking provider status, and handling investments/loans/bills. No obvious dead ends; even connection management includes search, connect URLs, and re-authentication flows. The set appears comprehensive for its intended purpose.

Resources