Query Bancadia's registry of US business checking account products with structured filters.
Scored across 2 tools
The two tools have clearly distinct purposes: one performs broad querying/searching across listings, while the other retrieves detailed information about a single pre-identified listing. There is no overlap or ambiguity, as they operate at different levels of granularity.
Both tool names follow the verb_noun pattern, beginning with action-oriented verbs ('query', 'get') and sharing the 'business_checking' domain noun. The naming is predictable and consistent, making it easy to infer which tool to use.
With only two tools, the server is quite minimal, but each tool earns its place for the narrow domain of browsing business checking account listings. The count feels reasonable for a read-only registry service, even though it is on the lower end.
The tool surface fully covers the apparent read-only workflow: discovering listings via a compound query and then retrieving full details for a selected listing. There are no obvious missing operations such as searching by slug, listing all, or filtering, since the query tool handles these cases.
Get full detail on one specific business checking listing, including gotcha fees (business_deposit_fees, e.g. overdraft, NSF, dormancy) and feature narrative (business_deposit_account_features) not returned by query_business_checking's broad list results. Fees/features that apply to only one plan tier (e.g. a Standard/Plus/Premier ladder) are nested under that tier in plan_tiers[].fees / plan_tiers[].features; tier-agnostic ones are in the top-level general_fees / general_features. Use this as a follow-up after query_business_checking to dig deeper on one listing the caller already identified by its listing_slug.
| Name | Required | Description | Default |
|---|---|---|---|
| listing_slug | Yes | The listing's stable public identifier, as returned in query_business_checking results (e.g. 'found-business-checking'). Do not use an internal database id. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral disclosure burden. It explains that tier-specific fees/features are nested under plan_tiers whereas general ones are top-level, and that certain details are not returned by the sibling tool. It does not discuss auth or side effects, but the read-only nature is strongly implied by 'Get' and the detail-oriented purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two moderately dense sentences, front-loaded with the core purpose. Each clause adds meaningful context—excluded fields, tier nesting, follow-up usage—though the long parenthetical around gotcha fees makes the opening sentence somewhat heavy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter tool with no output schema, the description sufficiently explains what is returned (fees, features, tier nesting) and how it differs from the sibling tool. The agent has enough context to decide when to invoke this tool and what to expect from the response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description reinforces that the slug should come from query_business_checking results and must not be an internal database id, but it adds little beyond the schema's own parameter description. No new parameter semantics are introduced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Get full detail') and a specific resource ('one specific business checking listing'), and explicitly contrasts it with query_business_checking's broad list. It clearly distinguishes the tool from its sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this as a follow-up after query_business_checking and names the alternative tool. It also identifies the trigger: when the caller has already identified one listing by slug, implying when not to use it (for broad list results).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Query the Bancadia registry for business checking account products using compound filter criteria. Returns active, verified listings from financial institutions. Optionally accepts target_industries/target_business_profiles to soft-rank results toward listings built for a given business type or stage — non-matching but eligible listings are still returned, just ranked lower.
| Name | Required | Description | Default |
|---|---|---|---|
| apy_min | No | Only return accounts whose best available rate (apy_max) is at least this value, as a decimal (e.g. 0.02 = 2%). This is the best rate the account can pay, not what a typical customer gets — many accounts pay less by default. Check apy_default in the results for the standard rate. | |
| rtp_network | No | Which real-time payment rail is supported | |
| rtp_supported | No | Whether real-time payments (any rail) are supported at all | |
| insurance_type | No | Deposit insurance type | |
| monthly_fee_max | No | Maximum monthly fee | |
| available_states | No | Returns listings available in all specified states | |
| interest_bearing | No | Whether the account earns interest | |
| target_industries | No | Soft-ranks results toward listings built for these business types. Does not exclude non-matching but otherwise-eligible listings. | |
| entity_types_accepted | No | Returns listings accepting all specified entity types (e.g. llc, s_corp) | |
| free_transactions_min | No | Minimum free transactions per month | |
| cash_deposit_available | No | Whether cash deposits are supported | |
| sub_accounts_supported | No | Whether sub-accounts are supported | |
| target_business_profiles | No | Soft-ranks results toward listings built for this business stage/shape. Does not exclude non-matching but otherwise-eligible listings. | |
| tax_integration_available | No | Whether the account connects to any tax-prep or tax-filing software/service | |
| minimum_opening_deposit_max | No | Maximum minimum opening deposit | |
| expense_integration_available | No | Whether the account connects to any expense/spend-management software | |
| accounting_integration_available | No | Whether the account connects to any accounting software (e.g. QuickBooks, Xero) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral disclosure burden. It discloses that results are active/verified and that soft-ranking does not exclude non-matching eligible listings, which is valuable. However, it does not mention compound filter combination semantics, pagination/limits, or result ordering beyond the soft-rank note.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, followed by result status and the key soft-ranking nuance. Every sentence contributes information and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 17-parameter query tool with no output schema or annotations, the description is useful but incomplete: it leaves out how multiple filters are combined, any result limits/pagination, and the relationship to the sibling get_business_checking_listing. The schema compensates for parameter detail but not these operational gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 17 parameters. The description repeats the soft-ranking behavior of target_industries/target_business_profiles but does not add meaning beyond what the schema entries already state, so it earns the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the operation (Query), the resource (Bancadia registry for business checking account products), and the result (active, verified listings). It stops short of explicitly contrasting with the sibling get_business_checking_listing, so it is clear but not fully differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives concrete context for when to use the tool: search by compound filter criteria, with target_industries/target_business_profiles acting as optional soft-ranking inputs rather than filters. It does not state when to use get_business_checking_listing instead, so exclusions/alternatives are missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
query_business_checking1 field changedInput schema / properties / apy_min / descriptionPrevious value: -"Minimum APY (inclusive), for interest-bearing accounts"New value: +"Only return accounts whose best available rate (apy_max) is at least this value, as a decimal (e.g. 0.02 = 2%). This is the best rate the account can pay, not what a typical customer gets — many accounts pay less by default. Check apy_default in the results for the standard rate."get_business_checking_listingquery_business_checkingCitable US facts w/ curated query templates: SEC financials, bank call reports, nonprofits. No key.
US business location data: search, sample, count, query rows or buy CSVs (Stripe or x402 USDC).
Search a directory of real, owner-confirmed small businesses. Read-only; attribution required.
Tools for your business banking with Rho, including accounts, transactions, and more
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