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isiahw1

mcp-server-bing-webmaster

get_link_counts

Retrieve inbound link counts for websites using Bing Webmaster Tools data to analyze backlink profiles.

Instructions

Get inbound link counts for a site.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
site_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_link_counts' tool, decorated with @mcp.tool for registration. It takes a site_url, makes an API request to Bing Webmaster Tools' GetLinkCounts endpoint, processes the response by ensuring the __type field is present, and returns the link counts.
    @mcp.tool(name="get_link_counts", description="Get inbound link counts for a site.")
    async def get_link_counts(
        site_url: Annotated[str, "The URL of the site"]
    ) -> Dict[str, Any]:
        """
        Get inbound link counts for a site.
    
        Args:
            site_url: The URL of the site
    
        Returns:
            Link count statistics
        """
        async with api:
            counts = await api._make_request(f"GetLinkCounts?siteUrl={site_url}")
            return api._ensure_type_field(counts, "LinkCounts")
  • Helper method used by the tool to ensure the response data has the required __type field for MCP compatibility.
    def _ensure_type_field(self, data: Any, type_name: str) -> Any:
        """Ensure __type field is present for MCP compatibility."""
        if isinstance(data, list):
            for item in data:
                if isinstance(item, dict) and "__type" not in item:
                    item["__type"] = f"{type_name}:#Microsoft.Bing.Webmaster.Api"
        elif isinstance(data, dict) and "__type" not in data:
            data["__type"] = f"{type_name}:#Microsoft.Bing.Webmaster.Api"
        return data
  • Core helper method in BingWebmasterAPI class that performs HTTP requests to the Bing API, handles OData responses, errors, and is called by the tool handler.
    async def _make_request(
        self,
        endpoint: str,
        method: str = "GET",
        json_data: Optional[Dict[str, Any]] = None,
        params: Optional[Dict[str, Any]] = None,
    ) -> Any:
        """Make a request to the Bing API and handle OData responses."""
        if not self.client:
            raise RuntimeError(
                "API client not initialized. Use 'async with api:' context manager."
            )
    
        headers = {"Content-Type": "application/json; charset=utf-8"}
    
        # Build URL with API key
        if "?" in endpoint:
            url = f"{self.base_url}/{endpoint}&apikey={self.api_key}"
        else:
            url = f"{self.base_url}/{endpoint}?apikey={self.api_key}"
    
        # Add additional parameters if provided
        if params:
            for key, value in params.items():
                url += f"&{key}={value}"
    
        try:
            if method == "GET":
                response = await self.client.get(url, headers=headers)
            else:
                response = await self.client.request(
                    method, url, headers=headers, json=json_data
                )
    
            if response.status_code != 200:
                error_text = response.text
                logger.error(f"API error {response.status_code}: {error_text}")
                raise Exception(f"API error {response.status_code}: {error_text}")
    
            data = response.json()
    
            # Handle OData response format
            if "d" in data:
                return data["d"]
            return data
    
        except httpx.TimeoutException:
            logger.error(f"Request timeout for {endpoint}")
            raise Exception("Request timed out")
        except Exception as e:
            logger.error(f"Request failed: {str(e)}")
            raise
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 'gets' data, implying a read-only operation, but doesn't specify permissions, rate limits, output format, or whether it's a real-time or cached query. For a tool with zero annotation coverage, this is a significant gap in transparency.

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, clearly front-loading the core purpose. It's appropriately sized for a simple tool, making it easy to parse quickly.

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, the description doesn't need to explain return values. However, with no annotations and minimal parameter guidance, it's adequate for a basic read operation but lacks context on usage and behavior, making it minimally viable but with clear gaps.

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?

The description mentions 'for a site', which aligns with the 'site_url' parameter, but adds no details beyond what the schema provides (e.g., format, examples, or constraints). With 0% schema description coverage and only one parameter, the description partially compensates but doesn't fully clarify semantics, meeting the baseline for minimal coverage.

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 action ('Get') and resource ('inbound link counts for a site'), making the purpose understandable. However, it doesn't distinguish this from sibling tools like 'get_url_links' or 'get_url_info', which might also relate to link data, so it lacks sibling differentiation.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools like 'get_url_links' or 'get_url_info', the description offers no context, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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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