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ravinwebsurgeon

DataForSEO MCP Server

backlinks_bulk_ranks

Analyze backlink authority scores for multiple domains, subdomains, or pages simultaneously to assess their ranking potential based on referring domains.

Instructions

This endpoint will provide you with rank scores of the domains, subdomains, and pages specified in the targets array. The score is based on the number of referring domains pointing to the specified domains, subdomains, or pages. The rank values represent real-time data for the date of the request and range from 0 (no backlinks detected) to 1,000 (highest rank). A similar scoring system is used in Google’s Page Rank algorithm

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetsYesdomains, subdomains or webpages to get rank for required field you can set up to 1000 domains, subdomains or webpages the domain or subdomain should be specified without https:// and www. the page should be specified with absolute URL (including http:// or https://) example: "targets": [ "forbes.com", "cnn.com", "bbc.com", "yelp.com", "https://www.apple.com/iphone/", "https://ahrefs.com/blog/", "ibm.com", "https://variety.com/", "https://stackoverflow.com/", "www.trustpilot.com" ]
rank_scaleNodefines the scale used for calculating and displaying the rank, domain_from_rank, and page_from_rank values optional field you can use this parameter to choose whether rank values are presented on a 0–100 or 0–1000 scale possible values: one_hundred — rank values are displayed on a 0–100 scale one_thousand — rank values are displayed on a 0–1000 scaleone_thousand

Implementation Reference

  • The handler function that performs the core logic: makes a POST request to DataForSEO's /v3/backlinks/bulk_ranks/live endpoint with targets and rank_scale, validates/formats response or handles errors.
    async handle(params: any): Promise<any> {
      try {
        const response = await this.client.makeRequest('/v3/backlinks/bulk_ranks/live', 'POST', [{
          targets: params.targets,
          rank_scale: params.rank_scale        
        }]);
        return this.validateAndFormatResponse(response);
      } catch (error) {
        return this.formatErrorResponse(error);
      }
    }
  • Zod schema definition for input parameters: targets (array of strings) and optional rank_scale (string, default 'one_thousand').
      getParams(): z.ZodRawShape {
        return {
          targets: z.array(z.string()).describe(`domains, subdomains or webpages to get rank for
    required field
    you can set up to 1000 domains, subdomains or webpages
    the domain or subdomain should be specified without https:// and www.
    the page should be specified with absolute URL (including http:// or https://)
    example:
    "targets": [
    "forbes.com",
    "cnn.com",
    "bbc.com",
    "yelp.com",
    "https://www.apple.com/iphone/",
    "https://ahrefs.com/blog/",
    "ibm.com",
    "https://variety.com/",
    "https://stackoverflow.com/",
    "www.trustpilot.com"
    ]`),
          rank_scale: z.string().optional().describe(`defines the scale used for calculating and displaying the rank, domain_from_rank, and page_from_rank values
    optional field
    you can use this parameter to choose whether rank values are presented on a 0–100 or 0–1000 scale
    possible values:
    one_hundred — rank values are displayed on a 0–100 scale
    one_thousand — rank values are displayed on a 0–1000 scale`).default('one_thousand')
        };
      }
  • The getTools() method registers all backlinks tools, including BacklinksBulkRanksTool (line 36), into a record keyed by tool name, defining description, params, and handler wrapper.
    getTools(): Record<string, ToolDefinition> {
      const tools = [
        new BacklinksTool(this.dataForSEOClient),
        new BacklinksAnchorTool(this.dataForSEOClient),
        new BacklinksBulkBacklinksTool(this.dataForSEOClient),
        new BacklinksBulkNewLostReferringDomainsTool(this.dataForSEOClient),
        new BacklinksBulkNewLostBacklinksTool(this.dataForSEOClient),
        new BacklinksBulkRanksTool(this.dataForSEOClient),
        new BacklinksBulkReferringDomainsTool(this.dataForSEOClient),
        new BacklinksBulkSpamScoreTool(this.dataForSEOClient),
        new BacklinksCompetitorsTool(this.dataForSEOClient),
        new BacklinksDomainIntersectionTool(this.dataForSEOClient),
        new BacklinksDomainPagesSummaryTool(this.dataForSEOClient),
        new BacklinksDomainPagesTool(this.dataForSEOClient),
        new BacklinksPageIntersectionTool(this.dataForSEOClient),
        new BacklinksReferringDomainsTool(this.dataForSEOClient),
        new BacklinksReferringNetworksTool(this.dataForSEOClient),
        new BacklinksSummaryTool(this.dataForSEOClient),
        new BacklinksTimeseriesNewLostSummaryTool(this.dataForSEOClient),
        new BacklinksTimeseriesSummaryTool(this.dataForSEOClient),
        new BacklinksBulkPagesSummaryTool(this.dataForSEOClient),
        new BacklinksFiltersTool(this.dataForSEOClient)
        // Add more tools here
      ];
    
      return tools.reduce((acc, tool) => ({
        ...acc,
        [tool.getName()]: {
          description: tool.getDescription(),
          params: tool.getParams(),
          handler: (params: any) => tool.handle(params),
        },
      }), {});
    }
  • Defines the tool name 'backlinks_bulk_ranks' used for registration.
    getName(): string {
      return 'backlinks_bulk_ranks';
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 well by explaining the scoring system, real-time nature, and range of values. However, it doesn't mention important behavioral aspects like rate limits, authentication requirements, potential costs, error handling, or whether this is a read-only operation (though implied by 'provide' and 'rank scores').

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?

The description is appropriately sized at three sentences, front-loading the core purpose. Each sentence adds value: the first states what the tool does, the second explains the scoring basis, and the third provides scoring context and comparison. There's minimal wasted text, though the PageRank comparison could be more directly tied to the tool's functionality.

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?

For a tool with 2 parameters, 100% schema coverage, but no annotations and no output schema, the description provides adequate context about what the tool does and how scores are calculated. However, it lacks information about the response format, error conditions, rate limits, and authentication requirements that would be important for an AI agent to use this tool effectively.

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

Parameters4/5

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

With 100% schema description coverage, the baseline is 3. The description adds value by explaining what the rank scores represent ('based on the number of referring domains') and comparing the scoring system to Google's PageRank, which provides important semantic context beyond what's in the parameter descriptions. However, it doesn't explicitly connect these explanations to the specific parameters.

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?

The description clearly states the tool's purpose: 'provide you with rank scores of the domains, subdomains, and pages specified in the targets array' with specific details about what the score measures ('based on the number of referring domains') and the output format ('range from 0 to 1,000'). It distinguishes itself from sibling tools like 'backlinks_bulk_spam_score' or 'backlinks_summary' by focusing specifically on rank scores rather than other backlink metrics.

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

Usage Guidelines3/5

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

The description implies usage context by mentioning 'real-time data for the date of the request' and the scoring system comparison to PageRank, but doesn't explicitly state when to use this tool versus alternatives like 'backlinks_bulk_referring_domains' or 'backlinks_domain_rank_overview'. It provides some contextual information but lacks explicit guidance on tool 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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