Skip to main content
Glama

Search active (or inactive) long-term rental listings

search_rental_listings
Read-onlyIdempotent

Return a page of long-term (12-month lease) rental listings — same record shape as search_sale_listings (monthly price is the asking rent), but each record is tagged listingKind:"rental-long-term". Same location-pinning rules and 30-minute upstream cache as the sale-listings endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name; combine with state for an area search.
limitNoMax listings to return per page. Default 50.
priceNoListed rent; supports ranges and multiple values.
stateNo2-character state abbreviation.
offsetNoNumber of listings to skip, for pagination. Default 0.
radiusNoSearch radius in miles (max 100); used with latitude/longitude.
statusNoListing status to return; defaults to Active.
addressNoFull address to match a specific listing.
daysOldNoMax days since the listing was last seen (min 1).
lotSizeNoLot size in square feet; supports ranges and multiple values.
zipCodeNo5-digit ZIP code.
bedroomsNoBedroom count; supports ranges and multiple values.
latitudeNoLatitude of the search center; requires longitude and radius.
bathroomsNoBathroom count; supports fractions, ranges, and multiple values.
longitudeNoLongitude of the search center; requires latitude and radius.
yearBuiltNoYear built; supports ranges and multiple values.
propertyTypeNoFilter by property type.
squareFootageNoLiving-area square footage; supports ranges and multiple values.
includeTotalCountNoWhen true, RentCast also returns the total matching count. Default false.

TDQS

A4.4/5.0
Behavior5/5

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

Annotations declare read-only, open-world, idempotent, and non-destructive. The description adds useful behavioral context: record shape mirrors search_sale_listings, each record is tagged listingKind:'rental-long-term', and upstream cache is 30 minutes. This goes beyond annotations and helps set expectations.

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, front-loaded with the action, and every phrase adds value (lease term, shape, tag, cache). No fluff.

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?

Given the tool has 19 parameters and no output schema, the description references search_sale_listings for record shape, which provides a compact way to communicate return structure. It covers pagination ('page'), listing type, location rules, and cache behavior. It could be more self-contained without relying on sibling knowledge, but is adequate.

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?

The input schema has 100% description coverage for all 19 parameters, so the schema already provides full parameter semantics. The description adds no additional parameter meaning, just references the overall shape and cache, so a baseline score of 3 is appropriate.

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 returns rental listings with a specific lease term ('long-term (12-month lease)'), and distinguishes itself from the sibling search_sale_listings by noting the same record shape but with a listingKind tag and monthly price as rent.

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?

It gives context by referencing search_sale_listings and stating 'Same location-pinning rules and 30-minute upstream cache', implying this tool behaves like the sale-listings endpoint but for rentals. It does not explicitly exclude other tools but the rental/sale distinction is clear.

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.

TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: avm_rent and avm_value target rent vs. property value, while search_properties, search_rental_listings, and search_sale_listings each address different record types (property records, rental listings, sale listings). get_property is the only single-record retrieval tool. No overlap or ambiguity exists.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: avm_rent/avm_value, search_properties/search_rental_listings/search_sale_listings, and get_property. The naming is predictable and uniformly formatted with action prefixes and clear resource targets.

Tool Count5/5

With 6 tools, the set is well-scoped for a real estate data server, covering property search, property detail, valuation models, and both rental and sale listings. Each tool earns its place without redundancy or excessive granularity.

Completeness5/5

The tool surface comprehensively covers the domain: property search with detailed records, single-property lookup, AVM for both rent and sale value, and listing search for both rental and sale. The read-only nature of the API means no CRUD operations are expected, and no obvious gaps remain for core workflows.