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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

bringatrailer_makes

Retrieve Bring a Trailer's makes and models directory with model pages and numeric model_id values for results queries, filterable by text or exact make slug.

Instructions

Bring a Trailer makes and models. Returns Bring a Trailer's Makes and Models Directory: every make with its model pages and the numeric model_id that bringatrailer_results accepts. Narrow with q (matches make or model names) or make (exact slug).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "bringatrailer_makes"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNoCase-insensitive text matched against make and model names
makeNoExact make slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.20

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden, and it discloses that the result is a directory enumerating every make and model page plus numeric model_ids, which implies a read-only, potentially large listing. It omits any note on response size, pagination, or rate limiting, so it stops just short of full behavioral disclosure.

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 front-loaded sentences: what it returns, what the payload contains, and how to narrow it. No filler, and the linkage to bringatrailer_results is placed before the filter details where it matters most.

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 two-optional-parameter directory lookup with no output schema, the description adequately covers the return contents and the downstream use of model_id. Only minor gaps remain, such as expected response size or whether the full directory is returned when no filter is applied.

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 coverage is 100%, so both parameters are already documented, and the description largely restates them ('q matches make or model names', 'make exact slug'). It adds the useful framing that these narrow the directory rather than replace it, but no syntax or format detail beyond the schema.

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?

States a specific resource and verb-equivalent ('Returns Bring a Trailer's Makes and Models Directory') and names the exact payload: every make with its model pages and the numeric model_id. It also distinguishes itself from the sibling bringatrailer_results by explaining that results accepts the model_id this tool yields.

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?

Gives clear context for use: it's the vocabulary/directory lookup whose model_id feeds bringatrailer_results, and it names the two narrowing options (q for text matching, make for exact slug). It does not explicitly exclude other lookup siblings like bringatrailer_filters, so it stops short of full when-not guidance.

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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