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DataForSEO MCP Server

dataforseo_labs_google_keyword_ideas

Generate relevant keyword ideas with search volume, trends, CPC, and competition data for SEO research and content planning.

Instructions

The Keyword Ideas provides search terms that are relevant to the product or service categories of the specified keywords. The algorithm selects the keywords which fall into the same categories as the seed keywords specified in a POST array. As a result, you will get a list of relevant keyword ideas for up to 200 seed keywords. Along with each keyword idea, you will get its 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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYestarget keywords
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_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_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 parameter default rule: ["relevance,desc"] relevance is used as the default sorting rule to provide you with the closest keyword ideas. We recommend using this sorting rule to get highly-relevant search terms. Note that relevance is only our internal system identifier, so it can not be used as a filter, and you will not find this field in the result array. The relevance score is based on a similar principle as used in the Keywords For Keywords endpoint. 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: ["relevance,desc","keyword_info.search_volume,desc"]
include_clickstream_dataNoInclude or exclude data from clickstream-based metrics in the result

Implementation Reference

  • The main handler function that sends the POST request to DataForSEO Labs API endpoint '/v3/dataforseo_labs/google/keyword_ideas/live' with the provided parameters and processes the response.
    async handle(params: any): Promise<any> {
      try {
        const response = await this.client.makeRequest('/v3/dataforseo_labs/google/keyword_ideas/live', 'POST', [{
          keywords: params.keywords,
          location_name: params.location_name,
          language_code: params.language_code,
          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);
      }
    }
  • Input schema definition using Zod for validating tool parameters such as keywords, location, language, filters, etc.
      getParams(): z.ZodRawShape {
        return {
          keywords: z.array(z.string()).describe(`target keywords`),
          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 parameter
    default rule:
    ["relevance,desc"]
    relevance is used as the default sorting rule to provide you with the closest keyword ideas. We recommend using this sorting rule to get highly-relevant search terms. Note that relevance is only our internal system identifier, so it can not be used as a filter, and you will not find this field in the result array. The relevance score is based on a similar principle as used in the Keywords For Keywords endpoint.
    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:
    ["relevance,desc","keyword_info.search_volume,desc"]`
          ),
          include_clickstream_data: z.boolean().optional().default(false).describe(
            `Include or exclude data from clickstream-based metrics in the result`)
        };
      }
  • Instantiation of the GoogleKeywordsIdeasTool instance in the DataForSEOLabsApi module's tools array.
    new GoogleKeywordsIdeasTool(this.dataForSEOClient),
  • Registration logic in getTools() that maps each tool's name to its description, params, and handler function.
      return tools.reduce((acc, tool) => ({
        ...acc,
        [tool.getName()]: {
          description: tool.getDescription(),
          params: tool.getParams(),
          handler: (params: any) => tool.handle(params),
        },
      }), {});
    }
  • Mapping of the tool name to its API filter path in the DataForSeoLabsFilterTool for filter support.
    'dataforseo_labs_google_keyword_ideas': 'keyword_ideas.google',
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. It discloses some behavioral traits: it returns up to 200 seed keywords, includes metrics like search volume and CPC, and supports filtering and sorting. However, it omits critical details such as rate limits, authentication requirements, error handling, pagination behavior (beyond offset/limit), and whether it's a read-only or mutating operation. For a complex tool with 8 parameters, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately concise with three sentences, but it could be more front-loaded. The first sentence states the purpose, but the second and third detail output metrics without prioritizing critical information like limitations or key parameters. Some phrasing is verbose (e.g., 'Along with each keyword idea...'), and it lacks bullet points or structured formatting for clarity.

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

Completeness2/5

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

Given the tool's complexity (8 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose and output metrics but fails to address behavioral aspects like rate limits, error conditions, or response format. Without annotations or an output schema, the agent lacks sufficient context to use the tool effectively, especially for a data-intensive operation like keyword analysis.

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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema: it implies the 'keywords' parameter is for seed keywords and mentions metrics like search volume and CPC, which relate to output rather than inputs. It does not clarify parameter interactions or provide usage examples, so it meets the baseline for high schema 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 tool's purpose: 'provides search terms that are relevant to the product or service categories of the specified keywords' and 'get a list of relevant keyword ideas.' It specifies the verb ('provides,' 'get') and resource ('keyword ideas'), but does not explicitly differentiate from sibling tools like 'dataforseo_labs_google_keyword_suggestions' or 'dataforseo_labs_google_related_keywords,' which may have overlapping functions.

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. It mentions the algorithm selects keywords based on categories of seed keywords, but does not specify use cases, prerequisites, or exclusions. With many sibling tools available (e.g., 'dataforseo_labs_google_keyword_suggestions'), this lack of differentiation leaves the agent without clear selection criteria.

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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