Skip to main content
Glama

Housing affordability and insurance indexes

get_index
Read-onlyIdempotent

MonitorBankRates proprietary indexes. "hai" = MBR Housing Affordability Index (daily; 100 = median household exactly affords the median home at today's average 30-year rate; higher is more affordable), with national score, state score and rank, and 90-day history; with a city, the city score, its rank in the state, and the home value, income and payment behind it. "hibi" = Home Insurance Burden Index and "aibi" = Auto Insurance Burden Index (annual; 100 = U.S. average burden; higher is heavier), with state rankings plus an estimated monthly homeowners or car insurance cost for the state or city, by insurer, with the cheapest insurer.

Input Schema

NameRequiredDescriptionDefault
cityNoOptional city name (needs state), e.g. Stamford. hai: city score, rank and inputs. hibi/aibi: city insurance cost estimate by insurer.
indexYes
stateNoOptional two-letter state code or name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond the schema: hai is daily, hibi/aibi are annual, hai includes a 90-day history, and city input changes the shape of the result. It omits any error behavior (e.g. city without state) or rate-limit/availability info, keeping it from a 5.

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?

Front-loaded with the resource identity, then dense but information-bearing definitions; every clause about the index scale and returned fields earns its place. The long parenthetical for hai is harder to scan than a structured list would be, but nothing is filler.

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?

With three parameters, one required, and no output schema, the description covers what each call returns, the units and direction of each index, and the city/state behavior—enough to invoke correctly. Remaining gaps are behavioral edge cases (city specified without state, unknown state, granularity of national vs state results) rather than core semantics.

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

Parameters4/5

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

Schema coverage is 67% and the 'index' enum has no inline description, but the description compensates fully by defining hai, hibi, and aibi and their scale direction ('higher is more affordable' vs 'higher is heavier'). The city/state relationship ('needs state') and the payoff of supplying a city are explained beyond the schema text.

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 names the resource (MonitorBankRates proprietary indexes) and defines each of the three enum values precisely, including what '100' means for each and what sub-scores come back. An agent can tell immediately this returns index data and nothing that any sibling (calculate_loan, get_average_rates, etc.) offers.

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?

Each index value is explained well enough that the agent can infer which to request, and the city/state interaction is described. However there is no explicit when-to-use versus when-not guidance, no mention of how this differs from get_average_rates or calculate_loan for affordability questions, and no stated prerequisites beyond one schema note.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources