Single-property deep-dive: history, price/sqft, days-on-market, comps from a Redfin URL.
Retrieve full property details from Redfin listing page. Returns listing description, tax history, HOA fees, property tax amount, nearby schools with ratings, neighborhood safety metrics, walkability scores, and photo gallery/tour URLs. Use for due diligence before making offers or detailed investment analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Redfin property listing URL (e.g. 'https://www.redfin.com/WA/Seattle/123-Main-St-98101') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe external read. The description adds the list of returned data, which is useful but does not disclose behavioral nuances like rate limits, potential website access issues, or error handling. It does not contradict annotations.
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?
Two sentences, no wasted words. The first sentence states purpose and enumerates return contents; the second gives usage context. Every part earns its place.
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 simple single-parameter read tool with rich annotations, the description covers what it does, what it returns, and when to use it. No output schema exists, but the description explicitly lists the return fields, making it sufficiently complete.
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?
The schema has 100% description coverage for the single 'url' parameter, including an example. The description does not add additional parameter semantics beyond what the schema provides, so 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?
The description clearly states the tool retrieves full property details from a Redfin listing page, and enumerates specific data returned. This distinguishes it from the sibling search_properties, which likely focuses on discovery rather than deep detail.
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?
The description explicitly says 'Use for due diligence before making offers or detailed investment analysis,' providing clear when-to-use context. It does not explicitly name alternatives or exclusions, but the purpose implies this is for when you already have a specific listing URL, differentiating it from search_properties.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Query Redfin real estate listings by location and filters for residential properties. Returns asking price, street address, bedrooms, bathrooms, square footage, property type, HOA status, and listing age. Use for home shopping, market analysis, investment research, or neighborhood comparison.
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes | Property location by city, zip code, or full address (e.g. 'Seattle, WA', '98101', '1600 Pennsylvania Ave') | |
| max_price | No | Maximum asking price filter in USD (e.g. 1000000) | |
| min_price | No | Minimum asking price filter in USD (e.g. 300000) | |
| property_type | No | Property category to filter (e.g. 'house', 'condo', 'townhouse', 'multi-family', 'land') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds behavioral context by listing exactly what fields are returned (asking price, address, bedrooms, etc.) and the nature of the query, going beyond the annotations without contradicting them.
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?
The description is a concise two-sentence structure that front-loads the action ('Query Redfin real estate listings') and follows with return fields and use cases. Every sentence adds value with no redundancy or filler.
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?
The tool has 4 well-documented parameters, no output schema, and annotations indicating read-only open-world behavior. The description covers the return fields and use cases, which is sufficient for a search tool. It does not mention pagination or sorting, but these are not critical given the context, so a small gap prevents a 5.
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%, with all four parameters documented with descriptions and examples. The description's phrase 'by location and filters' adds no new meaning beyond the schema, so the baseline of 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?
The description clearly states the tool queries Redfin real estate listings by location and filters, with a specific verb and resource. It also lists returned fields, distinguishing it from the sibling get_property_details, which is about individual property details rather than search results.
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?
The description provides explicit use cases ('Use for home shopping, market analysis, investment research, or neighborhood comparison'), giving clear context on when to use the tool. However, it does not mention alternatives or when not to use it, so it lacks the explicit exclusion or alternative naming that would warrant a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
get_property_detailssearch_propertiesClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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Redfin listings, sale-comps, and neighborhood market data via natural-language queries.
Zillow for-sale, for-rent and sold listings, and full property details, as structured JSON.
Search real-estate deals, rank top areas, run rental/BRRRR/flip analysis, pull sold comps.
U.S. real-estate data: property records, AVM value + rent estimates, sale/rental listings.
Add one secure layer between your agents and this server.
The two tools have clear, non-overlapping purposes: search_properties returns a list of listings with basic info, while get_property_details returns full details for a single property. An agent can easily decide which to use based on whether it needs a broad search or deep dive, with no ambiguity.
Both tools follow a consistent verb_noun pattern: 'search_properties' and 'get_property_details'. The verbs are distinct and descriptive, and the naming style is uniform with no mixed conventions, making the surface predictable.
With only two tools, the set is on the thin side, fitting the borderline category in the calibration. However, for a focused Redfin server, search and details are the core operations, so each tool earns its place despite the low count.
The tool surface covers the fundamental read-only workflow: find properties via search and then retrieve detailed information for a specific one. Minor gaps exist, such as no explicit tool for market trends or property comparison, but the core due-diligence and investment analysis needs are addressed.
