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Bing Webmaster MCP Server

Bing Webmaster MCP Server

bing_plan_remove_country_region_settings

Record a plan to remove a country or region targeting rule from Bing for human review before applying. It saves intent only and returns a plan ID and CLI apply command; it does not change Bing.

Instructions

Record a plan to remove a country or region targeting rule from Bing. Use when the user wants a geotargeting rule removed and a person must review it first. Do not use this to add a rule; call bing_plan_add_country_region_settings. Do not use this to read the current rules; call bing_geo_settings. This sends no change to Bing and only records intent; it may read your quota. Do not tell the user the change was applied; return the plan id and the CLI apply command.

Input Schema

NameRequiredDescriptionDefault
settingsYes
site_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

Adds substantial behavioral context beyond the annotations: it 'sends no change to Bing and only records intent,' may consume quota, and the agent must not claim the change was applied but instead return the plan id plus the CLI apply command. This clarifies the write-but-not-applied semantics that the raw readOnlyHint=false / destructiveHint=false flags cannot convey on their own.

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?

Six short clauses, each carrying load-bearing information: purpose, precondition, two exclusions with alternatives, side-effect/behavior, and required agent response. The most consequential fact (no change is sent) is positioned before the caller-facing instructions.

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 plan-recording mutation with no output schema and no annotation detail, the description covers behavior, side effects, quota, review requirement, and the required follow-up action. The one missing piece is the shape of the nested settings object, though the description implies what it targets.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description gives no guidance on either parameter. It hints at the subject matter (a country/region rule) and 'site_url' is self-evident, but the nested 'settings' object is entirely unspecified in both schema and description, which is a real gap when coverage is this low.

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 and resource: 'Record a plan to remove a country or region targeting rule from Bing.' It is immediately distinguishable from the add-rule sibling and from read tools like bing_geo_settings.

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

Usage Guidelines5/5

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

Explicit when-to-use ('user wants a geotargeting rule removed and a person must review it first') plus two explicit when-not-to-use cases, each naming the correct alternative tool (bing_plan_add_country_region_settings for adds, bing_geo_settings for reads). Nothing is left to inference.

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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