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mcp-server-bwt

mcp-server-bwt

by agalliani
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_related_keywords

Get related keywords and their impression data for a base query over a selected period, country, and language. Use these insights to identify search term variations.

Instructions

Get keyword impressions for related keywords in the selected period.

Args: query: The base keyword query country: The country code language: The language code start_date: The start date of the period end_date: The end date of the period

Returns: List[Keyword]: List of related keywords and their impression data

Raises: BingWebmasterError: If related keywords cannot be retrieved

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>",
      "country": "<country>",
      "language": "<language>",
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "get_related_keywords"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
countryYes
end_dateYes
languageYes
start_dateYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state the return type (List[Keyword]) and the error raised (BingWebmasterError), which is useful. However, it does not disclose whether the operation is read-only, any authorization requirements, rate limits, or pagination behavior. Since it is a 'get' operation, these are likely non-issues, but the lack of explicit disclosure is a moderate gap.

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 well-structured and concise. It opens with a one-sentence summary, then uses clear sections for Args, Returns, and Raises. There is no fluff, and the most important information is front-loaded. This is an excellent example of efficient, organized documentation.

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 get operation with five parameters, the description covers the essential aspects: purpose, arguments, return type, and error handling. The presence of an output schema likely documents the return structure in detail, so the description doesn't need to. It lacks explicit usage context (when to use vs. alternatives), but that is already scored under usage guidelines. Overall, it is reasonably complete for the tool's complexity.

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 0%, so the description must compensate. It does provide brief explanations for each parameter: query, country, language, start_date, end_date. These add basic meaning beyond the bare schema titles, but they lack details like expected formats (e.g., ISO codes for country/language, date format beyond the schema's date-time hint). This is sufficient but not thorough.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get keyword impressions for related keywords in the selected period.' It uses a specific verb and resource, and the mention of 'related keywords' distinguishes it from sibling tools like get_keyword or get_keyword_stats, though it doesn't explicitly name alternatives.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any conditions for selection, nor does it reference sibling tools. The agent is left to infer that it should be used for related keyword exploration, but no explicit usage guidance is given.

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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