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ssi_lookup

Look up correspondent banking / settlement instructions (SSI) for a bank.

Returns the correspondent banks (nostro accounts) that a given bank uses to settle payments in a specific currency, including account numbers (when available) and intermediary chains. Essential for payment routing and pre-validation.

Each correspondent is annotated with a clearing_note indicating whether it can clear the currency directly (located in a home country for that currency) or needs its own correspondent. If the note suggests a further lookup, call ssi_lookup on the correspondent's SWIFT code to find the full clearing chain.

IMPORTANT — known data gaps to respect:

  • Account numbers may be empty for some/all correspondents. The response surfaces an account_availability_note in those cases. Do NOT invent account numbers. Use swift_lookup() to find the bank's own published correspondent banks page when accounts are missing.

  • is_preferred is rarely populated — its absence is a DATA gap, not a signal. When preferred_correspondent_note is present (all flags false), do NOT infer a "preferred"/"natural" correspondent, and equally do NOT tell the user the bank "has no preference" or "rotates" — do not draw attention to the flag at all. Any listed BIC is a valid clearing route.

  • intermediaries is almost always empty in our dataset — an empty list does NOT mean the payment is direct.

  • Asset category per correspondent is COMMERCIAL (for customer MT103 credit transfers) or FINANCIAL (for bank-own-account / interbank MT202/pacs.009 settlements). Read asset_categories (the full list) rather than the single asset_category, which shows the commercial view only: one entry is one BIC+account and the same account is often published under BOTH categories, so the single field can never establish what an account may NOT be used for. The asset_category_note summarises the split — match the listed correspondents to the user's flow type (customer payment vs treasury/interbank).

  • If correspondents is EMPTY, we have no SSI on file for that bank/currency. The response carries a no_ssi_note (no SSI in any currency) or requested_currency_unavailable_note (SSI on file for other currencies only). This is a coverage gap, NOT a finding that the bank has no correspondents. Do NOT name a correspondent for the missing currency from training data — surface the published_ssi_document / the bank's website and tell the user to confirm SSI with the bank.

Always inspect the response's top-level next_steps array — it chains the swift_lookup / country_banking_rules / bank_holidays calls that complete a settlement-instruction answer.

Requires an API key with an active FI subscription. To get started: call mcp_register → mcp_verify → subscribe to an FI plan at https://ohmyfin.ai/subscription.

Args: swift: SWIFT/BIC code of the bank (e.g., "DEUTDEFF", 8 or 11 chars). currency: ISO 4217 currency code (e.g., "USD", "EUR", "GBP"). api_key: Your Ohmyfin API key (prod-...). Can also be passed via KEY header or Authorization: Bearer header.

Examples: ssi_lookup("DEUTDEFF", "USD") # Deutsche Bank USD correspondents ssi_lookup("HSBCHKHH", "EUR") # HSBC HK EUR correspondents ssi_lookup("DEUTDEFF", "USD", api_key="prod-abc123...")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
swiftYes
api_keyNo
currencyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: data gaps (account numbers empty, is_preferred rarely populated, intermediaries empty), interpretation of fields like asset_categories, and error scenarios (empty correspondents). It also warns against inventing data and clarifies subscription requirements.

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 lengthy but well-structured with sections (purpose, data gaps, usage notes, examples). It is front-loaded with the main goal and progressively detailed. Some repetition could be trimmed, but the complexity justifies the length.

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 tool's complexity and the presence of an output schema, the description covers all necessary aspects: response field meanings, error handling, data limitations, and integration with other tools via next_steps. It leaves no significant gaps.

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?

Schema coverage is 0%, so the description compensates fully. It explains 'swift' as a SWIFT/BIC code with format (8 or 11 chars), 'currency' as ISO 4217, and 'api_key' as optional with alternative passing methods. Examples illustrate usage.

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's purpose: 'Look up correspondent banking / settlement instructions (SSI) for a bank.' It specifies the resource (SSI for a bank) and differentiates from siblings like swift_lookup by focusing on settlement instructions.

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 explains when to use the tool ('Essential for payment routing and pre-validation') and provides guidance on next steps, such as calling ssi_lookup on correspondent SWIFT codes and inspecting the next_steps array. It also mentions using swift_lookup for missing account numbers, but lacks explicit 'when not to use' criteria.

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

A4.3/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlapping areas (goods_classify vs hs_code_lookup vs eccn_lookup; fx_rate vs fx_rate_history vs fx_volatility) require close reading of descriptions to select correctly. The detailed descriptions help, but the shear number of lookup tools creates mild ambiguity.

Naming Consistency3/5

Names mix verb-first (track_payment, mcp_verify) and noun-first patterns (iban_validate, fx_rate, ssi_lookup), with some phrase-like names (banks_using_correspondent, is_business_day_check). While readable, there is no single consistent convention.

Tool Count3/5

33 tools is heavy, but the server's broad scope (payments, FX, sanctions, export controls, company registries, SWIFT) justifies most of them. A few marginal tools (mcp_register, mcp_verify, company_search_result) add bulk without core value.

Completeness5/5

The tool set covers the payment lifecycle end-to-end: tracking, settlement, FX, compliance, sanctions, and company due diligence. There are no obvious dead ends; the tools chain together via next_steps and search_id flows.

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