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mcp-livedatapro

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getConsumerLoanRates

Average commercial mortgage, auto loan, and personal credit interest rates by country and credit tier. Use when comparing national average retail consumer borrowing APRs (30-year/15-year fixed mortgages, 5-year auto loans, personal loans, credit cards) by country. Do not use for macroeconomic central bank policy rates (use getCentralBankRates) or commercial property leases (use getCommercialRealEstate).

Input Schema

NameRequiredDescriptionDefault
loan_typeYesRetail consumer loan product category (defaults to 'mortgage_30y_fixed').mortgage_30y_fixed
country_codeYes2-letter uppercase ISO country code (e.g., US, GB, DE, FR).US

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / country_code / default
      Added value: +"US"
    • addedInput schema / properties / country_code / examples
      Added value: +[
+  "US"
+]
    • addedInput schema / properties / country_code / pattern
      Added value: +"^[A-Z]{2}$"
    • addedInput schema / properties / loan_type / default
      Added value: +"mortgage_30y_fixed"
    • addedInput schema / properties / loan_type / enum
      Added value: +[
+  "mortgage_30y_fixed",
+  "mortgage_15y_fixed",
+  "auto_loan_5y",
+  "personal_loan",
+  "credit_card_avg"
+]
    • addedInput schema / properties / loan_type / examples
      Added value: +[
+  "mortgage_30y_fixed"
+]
  2. Changed2 schema fields changed
    • changedInput schema / properties / country_code / description
      Previous value: -"2-letter ISO country code (e.g., US, UK, DE)"New value: +"2-letter uppercase ISO country code (e.g., US, GB, DE, FR)."
    • changedInput schema / properties / loan_type / description
      Previous value: -"Loan category"New value: +"Retail consumer loan product category (defaults to 'mortgage_30y_fixed')."
  3. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full load. It does disclose that values are country-level averages of retail APRs, which implies read-only aggregate data, but it does not state units/format (percent vs basis points), whether figures are a point-in-time snapshot or a series, or the sourcing/refresh cadence. It also promises breakdown 'by credit tier', which is not actually a parameter in the schema - a small but real disclosure problem.

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?

Three sentences, front-loaded with the resource definition then the use case then the exclusions. No filler, and each sentence carries a distinct piece of routing information.

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 simple two-parameter read-only lookup with a fully documented schema, the description plus schema is close to sufficient. The remaining gaps are the credit-tier reference that is not backed by any input, and the lack of any indication of return shape or unit, which the absence of an output schema leaves undocumented.

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% and both parameters carry descriptions, patterns, defaults, and an enum with examples, so the baseline is 3. The description adds mild value by expanding what the loan products mean in plain terms, but it introduces a 'credit tier' dimension that has no corresponding parameter, which slightly muddies rather than clarifies.

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?

States a specific resource (average commercial mortgage, auto loan, and personal credit interest rates) with the two dimensions that scope it: country and credit tier. A reader can immediately tell it returns retail consumer borrowing APRs, and the enumeration of products (30/15-year fixed, 5-year auto, personal, credit card) pins the exact dataset.

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

Usage Guidelines5/5

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

Explicitly gives the use case (comparing national average retail consumer borrowing APRs by country) and two named exclusions with routing: central bank policy rates go to getCentralBankRates, commercial property leases go to getCommercialRealEstate. This resolves the most likely confusions among the siblings in one sentence.

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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