dataforseo-mcp-server/build/main/core/modules/ai-optimization/tools/llm-mentions/llm-mentions-aggregated-metrics.js

A Model Context Protocol (MCP) server for the DataForSEO API, enabling modular and extensible integration of DataForSEO endpoints with support for both HTTP and SSE transports.

import z from "zod";
import { BaseTool } from "../../../base.tool.js";
export class AiOptimizationLlmMentionsAggregatedMetricsTool extends BaseTool {
    constructor(dataForSEOClient) {
        super(dataForSEOClient);
    }
    getName() {
        return "ai_opt_llm_ment_agg_metrics";
    }
    getDescription() {
        return "This endpoint provides aggregated metrics for mentions of the keywords or domains specified in the target array of the request.";
    }
    getParams() {
        return {
            target: z.array(z.union([
                z.object({
                    domain: z.string().describe("Target domain to search for LLM mentions"),
                    search_filter: z.enum(['include', 'exclude']).optional().describe("Search filter to apply (include or exclude)"),
                    search_scope: z.array(z.enum(['any', 'question', 'answer'])).optional().describe("Target search scope for LLM mentions"),
                }),
                z.object({
                    keyword: z.string().describe("Target keyword to search for LLM mentions"),
                    match_type: z.enum(['word_match', 'partial_match']).optional().describe("Match type for the keyword"),
                    search_filter: z.enum(['include', 'exclude']).optional().describe("Search filter to apply (include or exclude)"),
                    search_scope: z.array(z.enum(['any', 'question', 'answer'])).optional().describe("Target search scope for LLM mentions"),
                })
            ])).describe("Array of target objects to search for LLM mentions. Each object must contain either 'domain' or 'keyword'. Maximum number of targets: 1000"),
            location_name: z.string().optional().describe(`full name of the location, example: 'United Kingdom', 'United States'`),
            language_code: z.string().optional().describe("Search engine language code (e.g., 'en')"),
            platform: z.enum(['chat_gpt', 'google']).optional().describe("Platform to search for LLM mentions"),
            filters: this.getFilterExpression().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:
["ai_search_volume",">","1000"]
The full list of possible filters is available in 'ai_optimization_llm_mentions_filters' tool`),
            internal_list_limit: z.number().optional().describe("Internal parameter to limit the number of items processed. Not exposed to end-users."),
        };
    }
    async handle(params) {
        try {
            let payload = {};
            payload['target'] = params.target;
            payload['location_name'] = params.location_name;
            payload['language_code'] = params.language_code;
            if (params.platform) {
                payload['platform'] = params.platform;
            }
            if (params.filters) {
                payload['filters'] = params.filters;
            }
            if (params.internal_list_limit) {
                payload['internal_list_limit'] = params.internal_list_limit;
            }
            const response = await this.dataForSEOClient.makeRequest(`/v3/ai_optimization/llm_mentions/aggregated_metrics/live`, 'POST', [payload]);
            return this.validateAndFormatResponse(response);
        }
        catch (error) {
            return this.formatErrorResponse(error);
        }
    }
}
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