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realtystack-mcp

by io.github.IsaiahDupree

AVM sale-value estimate with comparables

avm_value
Read-onlyIdempotent

Run RentCast's automated valuation model for a subject property and return a point price estimate, a priceRangeLow/priceRangeHigh band, the resolved subjectProperty, and comparables[] — recent comparable sales each scored with a distance (miles) and correlation (0-1 similarity). Pin the subject with either address or latitude+longitude; when subject attributes are unknown, supply propertyType/bedrooms/bathrooms/squareFootage (or leave lookupSubjectAttributes true to have RentCast fill them). Cached 6h upstream.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressNoSubject property address. Required unless latitude+longitude are given. e.g. "5500 Grand Lake Dr, San Antonio, TX, 78244".
daysOldNoMax days since comparable listings were last seen (min 1).
bedroomsNoSubject bedroom count; 0 indicates a studio.
latitudeNoSubject latitude; alternative to address (requires longitude).
bathroomsNoSubject bathroom count; supports fractions.
compCountNoNumber of comparables to use in the estimate. Default 15.
longitudeNoSubject longitude; alternative to address (requires latitude).
maxRadiusNoMax distance between comparables and subject, in miles.
propertyTypeNoSubject property type; improves comparable selection.
squareFootageNoSubject living-area square footage.
lookupSubjectAttributesNoWhen true, RentCast looks up any missing subject attributes from its records. Default true.

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark this as read-only/idempotent, and the description adds valuable behavioral context: the 'Cached 6h upstream' note explains freshness, and it discloses that RentCast may fill unknown subject attributes. This goes beyond what annotations provide.

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?

The description packs a lot of information into three sentences: what it does, what it returns, how to specify inputs, and caching behavior. Every sentence earns its place without fluff.

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?

With no output schema, the description compensates by listing the expected return fields (estimate, band, subjectProperty, comparables with distance and correlation). It covers the main input decision points and notes caching, making it complete for an AVM tool of this complexity.

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 100%, so baseline is 3. The description adds meaning by explaining the address/lat-long alternative and the relationship between supplying subject attributes and enabling lookupSubjectAttributes, which helps the agent choose parameters correctly.

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 runs RentCast's AVM for a subject property and returns a point estimate, price range, resolved subject property, and scored comparables. It explicitly distinguishes this from its sibling 'avm_rent' by specifying 'sale-value estimate.'

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 provides concrete instructions on how to specify the subject (address or lat/long) and what to do when subject attributes are unknown, including the option to set lookupSubjectAttributes to true. It doesn't explicitly name alternatives like avm_rent, but the context is clear and actionable.

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

A4.5/5.0
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.

Resources