Skip to main content
Glama
Crawlora-org

Crawlora MCP

Official

brooklinen_search_suggest

Retrieve Brooklinen search suggestions for products, collections, and queries via predictive search. Accepts a query and optional limits/types to return structured suggestions.

Instructions

Get Brooklinen search suggestions. Returns products, collections, and query suggestions from Brooklinen's (https://www.brooklinen.com) credential-free predictive search Ajax endpoint. The storefront URL is fixed server-side.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query
limitNoMaximum results per type, defaults to 10 and supports up to 20
typesNoComma-separated suggestion types. Allowed values: product, collection, query
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the endpoint is 'credential-free' (no auth needed) and that the storefront URL is fixed server-side (no configuration needed), adding real behavioral context. It does not cover rate limits, error behavior, or response structure, but it goes well beyond a bare statement.

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?

Three concise sentences: a front-loaded one-line summary, a second sentence adding return types and the source endpoint, and a third noting a key constraint. Every sentence earns its place with 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?

For a simple read-only suggest tool with fully documented parameters and no output schema, the description provides enough to invoke it correctly: purpose, return categories, auth model, and URL constraint. It stops short of describing the exact response shape, which is a minor gap given the simplicity of the tool.

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?

Schema description coverage is 100%, so the baseline is 3. The description's mention of 'products, collections, and query suggestions' mirrors the allowed values of the 'types' parameter but adds no new semantic detail beyond what the schema already provides.

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 states a specific action ('Get') and resource ('Brooklinen search suggestions'), and enumerates the returned content (products, collections, and query suggestions). This clearly distinguishes it from Brooklinen product/collection retrieval siblings such as brooklinen_products or brooklinen_collection_products.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit statement of when to use this tool versus alternatives or exclusions. The phrases 'predictive search' and 'suggestions' imply a search-as-you-type use case, but no alternative tools are named, so usage guidance is only implicit.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Crawlora-org/crawlora-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server