Skip to main content
Glama
ravinwebsurgeon

DataForSEO MCP Server

by ravinwebsurgeon
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

dataforseo_labs_bulk_keyword_difficulty

Analyze keyword ranking difficulty for up to 1,000 keywords in one request to assess SEO competition and prioritize content strategy.

Instructions

This endpoint will provide you with the Keyword Difficulty metric for a maximum of 1,000 keywords in one API request. Keyword Difficulty stands for the relative difficulty of ranking in the first top-10 organic results for the related keyword. Keyword Difficulty in DataForSEO API responses indicates the chance of getting in top-10 organic results for a keyword on a logarithmic scale from 0 to 100.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordsYestarget keywords required field UTF-8 encoding maximum number of keywords you can specify in this array: 1000
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

Implementation Reference

  • src/core/modules/dataforseo-labs/tools/google/keyword-research/google-bulk-keyword-difficulty.tool.ts:37-48 (handler)
    The async handle method executes the core tool logic by sending a POST request to the DataForSEO Labs API endpoint for bulk keyword difficulty with the input parameters and handles the response or error.
    async handle(params: any): Promise<any> {
  try {
    const response = await this.client.makeRequest('/v3/dataforseo_labs/google/bulk_keyword_difficulty/live', 'POST', [{
      keywords: params.keywords,
      location_name: params.location_name,
      language_code: params.language_code
    }]);
    return this.validateAndFormatResponse(response);
  } catch (error) {
    return this.formatErrorResponse(error);
  }
}
  • src/core/modules/dataforseo-labs/tools/google/keyword-research/google-bulk-keyword-difficulty.tool.ts:18-35 (schema)
    Zod schema defining the input parameters for the tool: keywords (array of strings, up to 1000), location_name (string, default 'United States'), language_code (string, default 'en').
      getParams(): z.ZodRawShape {
    return {
      keywords: z.array(z.string()).describe(`target keywords
required field
UTF-8 encoding
maximum number of keywords you can specify in this array: 1000`),
      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`),
    };
  }
  • src/core/modules/dataforseo-labs/dataforseo-labs-api.module.ts:37-40 (registration)
    Instantiation of the GoogleBulkKeywordDifficultyTool within the tools array in DataForSEOLabsApi.getTools(), which registers the tool using its getName() into the module's tools map for higher-level registration.
    new GoogleHistoricalSERP(this.dataForSEOClient),
new GoogleSERPCompetitorsTool(this.dataForSEOClient),
new GoogleBulkKeywordDifficultyTool(this.dataForSEOClient),
new GoogleSubdomainsTool(this.dataForSEOClient),

Tool Definition Quality

C2.9/5.0
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 explains the metric's meaning (logarithmic scale 0-100) and bulk limits, but lacks critical behavioral details: it doesn't specify if this is a read-only operation, whether it requires authentication, rate limits, error handling, or what the output format looks like. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 concise and well-structured in two sentences: the first states the tool's function and limits, the second explains the metric. There's no unnecessary fluff, and key information is front-loaded. However, it could be slightly more efficient by integrating the metric explanation more tightly.

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's moderate complexity (bulk keyword analysis), no annotations, and no output schema, the description is partially complete. It covers the core purpose and metric definition but misses behavioral context (e.g., safety, performance) and output details. It's adequate as a starting point but requires the agent to infer or seek additional information for effective use.

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 fully documents all three parameters (keywords, location_name, language_code). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain keyword formatting, location/language implications, or default behaviors. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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: 'provide you with the Keyword Difficulty metric' for up to 1,000 keywords. It specifies the verb ('provide') and resource ('Keyword Difficulty metric'), and explains what the metric represents. However, it doesn't explicitly differentiate from sibling tools like 'dataforseo_labs_google_keyword_overview' or 'keywords_data_google_ads_search_volume', which might offer related keyword metrics.

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 bulk capability (1,000 keywords) but doesn't compare it to other keyword analysis tools in the sibling list, such as those for search volume or historical data. There's no mention of prerequisites, use cases, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ravinwebsurgeon/seo-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server