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global-solo

banking-access-index-mcp

by global-solo

Get one provider record

get_provider

Retrieve a provider's full evidence-cited record across all index dimensions and per-country acceptance statuses, each claim with its source URL and read date.

Instructions

Return the full evidence-cited record for one provider across every dimension held in the index (entity, residency, rails, receive, card, phone/2FA, FDIC, onboarding, marketplace) plus its per-country statuses. Each claim carries its source URL and the date that URL was read.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
providerYesProvider id, e.g. "mercury", "wise-business", "relay".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does well: it reveals the output structure (all ten dimensions plus per-country statuses) and the evidence-citation behavior (each claim carries its source URL and the read date). For a read-only fetch tool, this transparently communicates what the agent will receive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero filler. The core purpose is front-loaded ('Return the full evidence-cited record for one provider'), followed by the dimension list and the citation format detail. Every clause earns its place; no redundant restatement of the title or schema.

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?

For a single-parameter read tool with no output schema, the description is largely complete: it enumerates the returned dimensions, per-country statuses, and the evidence format (source URL + read date). The only gaps are error behavior for unknown provider ids and any access requirements, which are minor for a fetch operation.

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

Parameters3/5

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

Schema description coverage is 100% — the sole 'provider' parameter is documented with format guidance and examples. The description adds no parameter-level detail beyond the schema, so the baseline of 3 applies. The evidence-cited framing in the description is about the output, not the input.

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 states a specific verb ('Return'), a precise resource ('full evidence-cited record for one provider'), and a comprehensive scope ('across every dimension held in the index' plus per-country statuses). It is clearly distinguished from siblings: list_providers returns many, check_banking_access is a narrow access check, and dataset_info is metadata — none overlap with a full single-provider record fetch.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The singular focus ('for one provider') implies this is the tool for a single detailed lookup versus list_providers for a collection, but the description never explicitly states when to prefer this tool or names alternatives. The guidance is implied by the wording rather than stated, leaving the agent to infer the selection logic.

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