Zillow MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
The two tools have distinct jobs: one searches for listings and returns listing-level records, while the other fetches the full property page for a URL or zpid. The search tool also explicitly identifies itself as the entry point for the property endpoint, so an agent can assign each task easily.
Naming Consistency4/5Both names follow the same hasdata_zillow_entity_getThing pattern, so the set is predictable and readable. The minor inconsistency is that the verb portion is verbose and slightly redundant in different ways: getRealEstateListings versus getPropertyDetails, which makes them consistent but not perfectly parallel.
Tool Count3/5Two tools is at the borderline: the pair works well together as a search-then-details workflow, but the server is thin for a general-purpose Zillow data source. A property lookup by address or an agent lookup tool would make the count feel more complete.
Completeness4/5The listing search plus property details covers the core real-estate data workflow: find properties, collect URLs, then fetch the full property record. The main gap is that agents cannot directly look up a property by address without first performing a keyword search, but that is a workaround through the existing search tool.
Average 4.2/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 6 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden and it largely meets it. It discloses the rich return payload, the optional email extraction behavior, the note that email extraction increases cost, and that it treats the URL or zpid as the key. It does not discuss errors, auth, or rate limits, but for a read-style data fetch the behavior is otherwise well disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and then uses a long, valuable list of return fields. It is information-dense but not bloated; each item supports an agent understanding of output. It is not as crisp as a two-sentence version, hence a 4 rather than a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is no output schema and no annotations, the description compensates by listing the major return categories, mentioning input composition, and naming target use cases. The agent can infer what a successful invocation yields. It does not fully specify failure modes or zpid format, but the essential call-and-response context is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameter meaning is already fully documented in the schema. The description adds mild context by framing extractAgentEmails as 'optional agent email extraction' and tying the URL to a full page fetch, but it does not substantially add syntax or domain meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Fetches') and a precise resource ('full Zillow property page by URL/zpid'), then enumerates the concrete data returned. It distinguishes itself from the sibling listing tool by focusing on a single property page rather than real estate listings, even though the sibling is not explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says exactly when to use this tool: 'Use for valuation models, CMA generation, investor underwriting, rental yield analysis, and enriching buyer/seller agent assistants.' This is clear context and use-case targeting. It does not explicitly exclude the sibling tool or state when not to use it, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral burden, and it does a good job by specifying both the search behavior and the returned data: 'address, Zillow URL/zpid, price, Zestimate, beds/baths, sqft, home type, status, days on Zillow, coordinates, thumbnail, listing agent.' It also states 'pagination' as part of the behavior. It does not cover rate limits or errors, but for a listing search this is largely background.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: it starts with the operation, then covers filters and return fields, then adds use cases. The prose is reasonably brisk for a 33-parameter tool, and most sentences earn their place; only a few phrases just echo the schema or the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 33 parameters, no output schema, and no annotations, this description is unusually complete. It covers what the tool searches, what filters are possible, what fields come back, how pagination works, and why someone would use it, plus it connects downstream to the sibling Property endpoint. An agent has what it needs to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, so every parameter already has a structured description. The tool description adds an organized summary of the main filter categories—'price, beds, baths, home type, day built, lot/square footage, HOA, listing status, amenities, views, pet policy, days on Zillow'—but it does not substantially promote per-parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource ('Get Zillow Real Estate Listings') and explicitly states it 'Searches Zillow for-sale, for-rent, and sold listings by keyword with rich filters'. It clearly distinguishes itself as a listing-search tool rather than a property-detail tool, and the closing note about 'collecting URLs for the Zillow Property endpoint' reinforces that distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete intended use cases: 'real-estate market dashboards, rental pricing analysis, agent lead lists, inventory tracking, and collecting URLs for the Zillow Property endpoint.' It gives a clear sense of when to choose this tool, though it does not explicitly name the sibling tool or state 'use getPropertyDetails when you already have a zpid.'
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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