Zillow Remote MCP Server

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds valuable context by enumerating the returned fields (address, zpid, Zestimate, coordinates, broker, etc.), which matters given there is no output schema, though pagination behavior and rate limits remain unexplained.

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?

Well-structured and front-loaded: purpose first, then capability/filters, then returns, then use cases. Each sentence earns its place, though the filter enumeration partially restates schema content and the description is on the long side.

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 32-parameter search tool with no output schema, the description compensates by summarizing return fields and listing use cases, so an agent knows what it gets back. It is nearly complete, missing only pagination semantics and an explicit call-out of the two required parameters (keyword, type).

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 all 32 parameters are already documented. The description broadly enumerates filter categories (price, beds, baths, home type, HOA, views, pet policy) but adds no syntax, format, or interaction detail beyond what the schema provides. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb (Searches/Get) and resource (Zillow Real Estate Listings), and specifies the three listing types (for-sale, for-rent, sold). It distinguishes itself from the sibling property endpoint by noting it collects URLs 'for the Zillow Property endpoint,' giving an agent a clear routing signal.

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?

Provides concrete use cases (market dashboards, rental pricing analysis, agent lead lists, inventory tracking) and a downstream relationship to the Zillow Property endpoint. However, it names no explicit alternative tool or 'when-not-to-use' condition, leaving the sibling boundary to inference.

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

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

Annotations already cover safety (readOnlyHint, non-destructive, openWeb). The description adds real behavioral context beyond that: agent-email extraction is optional and raises request cost, and walk/transit scores only exist for building pages. It does not discuss caching, rate limits, or failure modes on invalid URLs.

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?

Front-loads the purpose in the first sentence, then a single dense sentence. The return-field enumeration is long, but it earns its place since no output schema exists. Slightly laundry-list-like but no wasted framing.

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?

With no output schema, the description carries the burden of explaining return values and does so thoroughly (price history, Zestimate, photos, school assignments, agent/broker). Remaining gap is the absence of failure/pagination behavior for what is a scraper-style fetch.

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 coverage is 100%, so the schema already documents both url and extractAgentEmails. The description restates that input is a URL/zpid and that email extraction is optional and costlier, adding marginal value but no syntax or format detail beyond the schema. Baseline 3 is appropriate.

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?

States a specific verb+resource ("Fetches the full Zillow property page by URL/zpid") and clearly scopes it to a single property, which distinguishes it from the listing/search sibling hasdata_zillow_listing_getRealEstateListings. It does not explicitly name that sibling, so sibling differentiation is implied rather than stated.

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?

Gives concrete use contexts (valuation models, CMA generation, investor underwriting, rental yield analysis, agent enrichment), which tells an agent when this tool fits. It stops short of naming alternatives or stating when-not-to-use, so it is clear context without exclusions.

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