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ScrapingDog-MCP

ScrapingDog-MCP

by alessandrobenigni
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

walmart_autocomplete

Get Walmart autocomplete search suggestions for any query, including related category links to refine navigation.

Instructions

Retrieves Walmart autocomplete search suggestions for any query, including a list of suggested search terms and category navigation data. [Credits: 5 API credits per successful request.] Notes: No domain/country localization parameters documented for this endpoint. No pagination applicable. Returns: { queries: [{displayName, url}], fns: [{title, image, url}] } — fns are suggested category/browse links related to the query.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "walmart_autocomplete"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesThe Walmart search query to get autocomplete suggestions for (e.g. football, laptop).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
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 credit cost per request, notes on missing localization documentation, and describes the return structure. However, it does not cover rate limits, authentication, or error handling.

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?

The description is concise and front-loaded with the purpose. It includes essential notes on credits, localization, pagination, and return structure without unnecessary words. Every sentence provides value.

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?

Given the tool is simple with one parameter and no output schema, the description adequately covers purpose, return structure, and usage constraints. Minor omissions like error handling prevent a perfect score.

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% with only one parameter (query) that includes an example. The main description adds no additional parameter semantics beyond what the schema already provides. Baseline 3 applies.

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 clearly states the tool retrieves Walmart autocomplete search suggestions for any query, specifying it includes suggested search terms and category navigation data. This distinguishes it from sibling tools like google_autocomplete or walmart_search.

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?

The description provides context on credits, lack of localization parameters, and no pagination, but does not explicitly state when to use this tool versus alternatives like walmart_search or other autocomplete tools. Usage guidance is implied rather than direct.

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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