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MisarSEO MCP Server

get_bing_keyword_research

Read-onlyIdempotent

GetKeyword + GetKeywordStats + GetRelatedKeywords: real Bing impression data for a query, its recent weekly history, and related queries — read straight from the Bing Webmaster API. FREE (no credits). Unlike derived/estimated keyword metrics, these numbers come from Bing's own search-impression logs. Bring-your-own-key: requires BING_WEBMASTER_API_KEY. Answers { ok: false, reason: 'not_configured' } when unset, or 'no_matching_site' when the project's domain has no verified match on the account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search query to research.
countryNoTwo-letter country code, e.g. 'us'.
endDateNoYYYY-MM-DD. Applies to keyword/relatedKeywords only.
languageNoLanguage-region code, e.g. 'en-US'.
projectIdYesRequired. The MisarSEO project ID to scope this call to. Get one from list_projects.
startDateNoYYYY-MM-DD. Applies to keyword/relatedKeywords only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already cover readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavioral value beyond them: size is FREE (no credits), it requires a bring-your-own BING_WEBMASTER_API_KEY, and it enumerates the exact error payloads (not_configured, no_matching_site). This is exactly the extra context an agent needs before calling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads what the tool returns before the API-key and error caveats, and every sentence carries information. Slightly dense with stacked clauses and em-dashes, but no wasted filler.

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?

With no output schema, the description carries return-value burden and does reasonably well: it names the three data blocks returned and the failure responses. It doesn't detail the shape of the weekly history or related-query payloads, leaving a small gap.

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 all six parameters are already documented in the schema. The description adds only marginal meaning (date fields apply to keyword/relatedKeywords) which the schema itself already states, so the 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?

States a specific verb+resource: real Bing impression data for a query, its weekly history, and related queries, naming the underlying GetKeyword/GetKeywordStats/GetRelatedKeywords methods. It distinguishes itself from derived/estimated keyword siblings by emphasizing Bing's own impression logs.

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?

Clearly frames the use case (real impression data vs derived/estimated metrics) and prerequisite (BING_WEBMASTER_API_KEY), giving the agent context for when this is the right choice. It stops short of explicitly naming an alternative sibling to use instead, so no exclusions are stated.

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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