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isiahw1

mcp-server-bing-webmaster

get_keyword_stats

Retrieve historical keyword performance data from Bing Webmaster Tools to analyze search trends and optimize website content.

Instructions

Get historical statistics for a specific keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_urlYes
queryYes
countryNo
languageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The complete handler and registration for the 'get_keyword_stats' tool. It constructs parameters and makes an API request to Bing Webmaster Tools' GetKeywordStats endpoint, then ensures MCP type compatibility.
    @mcp.tool(
        name="get_keyword_stats",
        description="Get historical statistics for a specific keyword.",
    )
    async def get_keyword_stats(
        site_url: Annotated[str, "The URL of the site"],
        query: Annotated[str, "The keyword/query to analyze"],
        country: Annotated[str, "Country code (e.g., 'US', 'GB')"] = "",
        language: Annotated[str, "Language code (e.g., 'en', 'fr')"] = "",
    ) -> Dict[str, Any]:
        """
        Get historical statistics for a specific keyword.
    
        Args:
            site_url: The URL of the site
            query: The keyword/query to analyze
            country: Country code (optional)
            language: Language code (optional)
    
        Returns:
            Historical keyword statistics
        """
        async with api:
            params = f"siteUrl={site_url}&query={query}"
            if country:
                params += f"&country={country}"
            if language:
                params += f"&language={language}"
    
            stats = await api._make_request(f"GetKeywordStats?{params}")
            return api._ensure_type_field(stats, "KeywordStats")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves historical statistics but does not specify whether it's a read-only operation, what permissions are required, if there are rate limits, or the format of returned data. While it implies a safe read operation, critical behavioral details are missing for a tool with no annotation coverage.

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 a single, efficient sentence with no wasted words. It is front-loaded with the core purpose, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's function, achieving optimal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which reduces the need to describe return values) but no annotations and 0% schema coverage for parameters, the description is incomplete. It covers the basic purpose but lacks usage guidelines, parameter details, and behavioral context, making it adequate only as a minimal starting point for a read operation with structured output.

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%, meaning none of the four parameters (site_url, query, country, language) are documented in the schema. The description adds no parameter semantics beyond implying 'keyword' relates to 'query.' It does not explain what 'site_url' refers to, how 'country' and 'language' affect results, or their expected formats, failing to compensate for the low schema coverage.

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

Purpose3/5

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

The description states the tool's purpose as 'Get historical statistics for a specific keyword,' which is clear but vague. It specifies the verb 'Get' and resource 'historical statistics,' but lacks specificity about what statistics are retrieved or how they differ from sibling tools like 'get_keyword_data' or 'get_query_stats.' This distinguishes it from unrelated tools but not from similar ones.

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. With sibling tools like 'get_keyword_data' and 'get_query_stats' available, there is no indication of context, prerequisites, or exclusions. This leaves the agent to guess based on tool names alone, which is insufficient for effective selection.

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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