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DataForSEO MCP Server

dataforseo_labs_google_related_keywords

Discover related search keywords from Google's "searches related to" results. Get keyword ideas with search volume, trends, CPC, and competition data for SEO research and content planning.

Instructions

The Related Keywords endpoint provides keywords appearing in the "searches related to" SERP element You can get up to 4680 keyword ideas by specifying the search depth. Each related keyword comes with the list of relevant product categories, search volume rate for the last month, search volume trend for the previous 12 months, as well as current cost-per-click and competition values. Moreover, this endpoint supplies minimum, maximum and average values of daily impressions, clicks and CPC for each result.

Datasource: DataForSEO SERPs Database Search algorithm: depth-first search for queries appearing in the "search related to" element of SERP for the specified seed keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYestarget keyword
depthNokeyword search depth
location_nameNofull name of the location required field only in format "Country" (not "City" or "Region") example: 'United Kingdom', 'United States', 'Canada'United States
language_codeNolanguage code required field example: enen
limitNoMaximum number of keywords to return
offsetNooffset in the results array of returned keywords optional field default value: 0 if you specify the 10 value, the first ten keywords in the results array will be omitted and the data will be provided for the successive keywords
filtersNoyou can add several filters at once (8 filters maximum) you should set a logical operator and, or between the conditions the following operators are supported: regex, not_regex, <, <=, >, >=, =, <>, in, not_in, match, not_match, ilike, not_ilike, like, not_like you can use the % operator with like and not_like, as well as ilike and not_ilike to match any string of zero or more characters merge operator must be a string and connect two other arrays, availible values: or, and. example: ["keyword_data.keyword_info.search_volume",">",0] [["keyword_info.search_volume","in",[0,1000]], "and", ["keyword_data.keyword_info.competition_level","=","LOW"]] [["keyword_data.keyword_info.search_volume",">",100], "and", [["keyword_data.keyword_info.cpc","<",0.5], "or", ["keyword_data.keyword_info.high_top_of_page_bid","<=",0.5]]]
order_byNoresults sorting rules optional field you can use the same values as in the filters array to sort the results possible sorting types: asc – results will be sorted in the ascending order desc – results will be sorted in the descending order you should use a comma to set up a sorting type example: ["keyword_data.keyword_info.competition,desc"] default rule: ["keyword_data.keyword_info.search_volume,desc"] note that you can set no more than three sorting rules in a single request you should use a comma to separate several sorting rules example: ["keyword_data.keyword_info.search_volume,desc","keyword_data.keyword_info.cpc,desc"]
include_clickstream_dataNoInclude or exclude data from clickstream-based metrics in the result

Implementation Reference

  • The handler function executes the tool logic by making a POST request to the DataForSEO Labs API endpoint '/v3/dataforseo_labs/google/related_keywords/live' with the provided parameters, formats filters and order_by, and handles the response or error.
    async handle(params: any): Promise<any> {
      try {
        const response = await this.client.makeRequest('/v3/dataforseo_labs/google/related_keywords/live', 'POST', [{
          keyword: params.keyword,
          location_name: params.location_name,
          language_code: params.language_code,
          depth: params.depth,  
          limit: params.limit,
          offset: params.offset,
          filters: this.formatFilters(params.filters),
          order_by: this.formatOrderBy(params.order_by),
          include_clickstream_data: params.include_clickstream_data
        }]);
        return this.validateAndFormatResponse(response);
      } catch (error) {
        return this.formatErrorResponse(error);
      }
    }
  • Zod schema defining the input parameters for the tool, including keyword, depth, location, language, limits, filters, ordering, and clickstream data options.
      getParams(): z.ZodRawShape {
        return {
          keyword: z.string().describe(`target keyword`),
          depth: z.number().min(0).max(4).default(1).describe(`keyword search depth`),
          location_name: z.string().default("United States").describe(`full name of the location
    required field
    in format "Country"
    example:
    United Kingdom`),
          language_code: z.string().default("en").describe(
            `language code
            required field
            example:
            en`),
          limit: z.number().min(1).max(1000).default(10).optional().describe("Maximum number of keywords to return"),
          offset: z.number().min(0).optional().describe(
            `offset in the results array of returned keywords
            optional field
            default value: 0
            if you specify the 10 value, the first ten keywords in the results array will be omitted and the data will be provided for the successive keywords`
          ),
          filters: z.array(
            z.union([
              z.array(z.union([z.string(), z.number(), z.boolean()])).length(3),
              z.enum(["and", "or"])
            ])
          ).max(8).optional().describe(
            `you can add several filters at once (8 filters maximum)
            you should set a logical operator and, or between the conditions
            the following operators are supported:
            regex, not_regex, <, <=, >, >=, =, <>, in, not_in, match, not_match, ilike, not_ilike, like, not_like
            you can use the % operator with like and not_like, as well as ilike and not_ilike to match any string of zero or more characters
            merge operator must be a string and connect two other arrays, availible values: or, and.
            example:
          ["keyword_info.search_volume",">",0]
    [["keyword_info.search_volume","in",[0,1000]],
    "and",
    ["keyword_info.competition_level","=","LOW"]][["keyword_info.search_volume",">",100],
    "and",
    [["keyword_info.cpc","<",0.5],
    "or",
    ["keyword_info.high_top_of_page_bid","<=",0.5]]]`
          ),
          order_by: z.array(z.string()).optional().describe(
            `results sorting rules
    optional field
    you can use the same values as in the filters array to sort the results
    possible sorting types:
    asc – results will be sorted in the ascending order
    desc – results will be sorted in the descending order
    you should use a comma to set up a sorting type
    example:
    ["keyword_data.keyword_info.competition,desc"]
    default rule:
    ["keyword_data.keyword_info.search_volume,desc"]
    note that you can set no more than three sorting rules in a single request
    you should use a comma to separate several sorting rules
    example:
    ["keyword_data.keyword_info.search_volume,desc","keyword_data.keyword_info.cpc,desc"]`
          ),
          include_clickstream_data: z.boolean().optional().default(false).describe(
            `Include or exclude data from clickstream-based metrics in the result`)
        };
      }
  • The getTools() method registers all DataForSEO Labs tools, including GoogleRelatedKeywordsTool at line 35, into a map using their getName() as key, providing description, params, and handler.
    getTools(): Record<string, ToolDefinition> {
      const tools = [
        new GoogleRankedKeywordsTool(this.dataForSEOClient),
        new GoogleDomainCompetitorsTool(this.dataForSEOClient),
        new GoogleDomainRankOverviewTool(this.dataForSEOClient),
        new GoogleKeywordsIdeasTool(this.dataForSEOClient),
        new GoogleRelatedKeywordsTool(this.dataForSEOClient),
        new GoogleKeywordsSuggestionsTool(this.dataForSEOClient),
        new GoogleHistoricalSERP(this.dataForSEOClient),
        new GoogleSERPCompetitorsTool(this.dataForSEOClient),
        new GoogleBulkKeywordDifficultyTool(this.dataForSEOClient),
        new GoogleSubdomainsTool(this.dataForSEOClient),
        new GoogleKeywordOverviewTool(this.dataForSEOClient),
        new GoogleTopSearchesTool(this.dataForSEOClient),
        new GoogleSearchIntentTool(this.dataForSEOClient),
        new GoogleKeywordsForSiteTool(this.dataForSEOClient),
        new GoogleDomainIntersectionsTool(this.dataForSEOClient),
        new GoogleHistoricalDomainRankOverviewTool(this.dataForSEOClient),
        new GooglePageIntersectionsTool(this.dataForSEOClient),
        new GoogleBulkTrafficEstimationTool(this.dataForSEOClient),
        new DataForSeoLabsFilterTool(this.dataForSEOClient),
        new GoogleHistoricalKeywordDataTool(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),
        },
      }), {});
    }
  • Static map in the filter tool that associates the tool name 'dataforseo_labs_google_related_keywords' with the API response path 'related_keywords.google' for filter handling.
    private static readonly TOOL_TO_FILTER_MAP: { [key: string]: string } = {
      'dataforseo_labs_google_ranked_keywords': 'ranked_keywords.google',
      'dataforseo_labs_google_keyword_ideas': 'keyword_ideas.google',
      'dataforseo_labs_google_keywords_for_site': 'keywords_for_site.google',
      'dataforseo_labs_google_competitors_domain': 'competitors_domain.google',
      'dataforseo_labs_google_serp_competitors': 'serp_competitors.google',
      'dataforseo_labs_google_subdomains': 'subdomains.google',
      'dataforseo_labs_google_domain_intersection': 'domain_intersection.google',
      'dataforseo_labs_google_page_intersection': 'page_intersection.google',
      'dataforseo_labs_google_historical_serp': 'historical_serp.google',
      'dataforseo_labs_google_historical_rank_overview': 'domain_rank_overview.google',
      'dataforseo_labs_google_relevant_pages': 'relevant_pages.google',
      'dataforseo_labs_google_top_searches': 'top_searches.google',
      'dataforseo_labs_google_keyword_overview': 'keyword_overview.google',
      'dataforseo_labs_google_search_intent': 'search_intent.google',
      'dataforseo_labs_google_bulk_keyword_difficulty': 'bulk_keyword_difficulty.google',
      'dataforseo_labs_google_related_keywords': 'related_keywords.google',
      'dataforseo_labs_google_keyword_suggestions': 'keyword_suggestions.google',
      'dataforseo_labs_google_domain_rank_overview': 'domain_rank_overview.google',
      'dataforseo_labs_google_domain_metrics_by_categories': 'domain_metrics_by_categories.google',
      'dataforseo_labs_google_domain_whois_overview': 'domain_whois_overview.google',
      'dataforseo_labs_google_categories_for_domain': 'categories_for_domain.google',
      'dataforseo_labs_google_keywords_for_categories': 'keywords_for_categories.google',
      'dataforseo_labs_amazon_product_competitors': 'product_competitors.amazon',
      'dataforseo_labs_amazon_product_keyword_intersections': 'product_keyword_intersections.amazon',
      'dataforseo_labs_google_app_competitors': 'app_competitors.google',
      'dataforseo_labs_apple_app_competitors': 'app_competitors.apple',
      'dataforseo_labs_google_app_intersection': 'app_intersection.google',
      'dataforseo_labs_apple_app_intersection': 'app_intersection.apple',
      'dataforseo_labs_google_keywords_for_app': 'keywords_for_app.google',
      'dataforseo_labs_apple_keywords_for_app': 'keywords_for_app.apple',
      'dataforseo_labs_database_rows_count': 'database_rows_count'
    };
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 describes the search algorithm ('depth-first search'), maximum results ('up to 4680 keyword ideas'), and data metrics included (volume, trends, CPC, competition, impressions, clicks). However, it doesn't mention rate limits, authentication requirements, data freshness, error conditions, or whether this is a read-only operation versus a mutation tool.

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 with three focused paragraphs. The first paragraph clearly states the core functionality, the second lists the data returned, and the third provides important context about data source and algorithm. There's minimal redundancy, though the second paragraph could be slightly more concise in listing metrics.

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 9 parameters, no annotations, and no output schema, the description provides adequate but incomplete context. It covers the core functionality, data returned, and algorithm, but lacks information about response format, error handling, rate limits, and authentication requirements. The absence of an output schema means the description should ideally explain what the return structure looks like, which it doesn't do.

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?

The schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description adds context about 'search depth' and 'seed keyword' that helps understand the relationship between parameters, but doesn't provide significant additional parameter semantics beyond what's in the schema. With high schema coverage, the baseline is 3, but the description adds some useful context about how parameters interact.

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 tool's purpose: to provide keywords from the 'searches related to' SERP element with detailed metrics. It specifies the verb ('provides'), resource ('keywords'), and data source ('DataForSEO SERPs Database'), but doesn't explicitly differentiate it from sibling tools like 'dataforseo_labs_google_keyword_ideas' or 'dataforseo_labs_google_keyword_suggestions' that might offer similar keyword discovery functionality.

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 'seed keyword' and 'search depth' for getting related keywords, but doesn't provide explicit guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, limitations, or compare it to sibling tools for keyword research, leaving the agent to infer appropriate usage scenarios.

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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