dataforseo-mcp-server/build/main/core/modules/ai-optimization/tools/llms/llm-response.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 AiOptimizationLlmResponseTool extends BaseTool {
    constructor(dataForSEOClient) {
        super(dataForSEOClient);
    }
    getName() {
        return "ai_optimization_llm_response";
    }
    getDescription() {
        return "This endpoint allows you to retrieve structured responses from a specific AI model, based on the input parameters";
    }
    getParams() {
        return {
            llm_type: z.string().describe(`type of llm. Must be one of: 'claude', 'gemini', 'chat_gpt', 'perplexity'`),
            user_prompt: z.string().describe("Prompt for the AI model. The question or task you want to send to the AI model. You can specify up to 500 characters in the user_prompt field"),
            model_name: z.string().describe(`name of the AI model. consists of the actual model name and version name. if not sure which model to use, first call the ai_optimization_llm_models tool to get list of available models for the specified llm_type`),
            temperature: z.number().optional().describe("randomness of the AI response optional field higher values make output more diverse; lower values make output more focused;"),
            top_p: z.number().optional().describe("diversity of the AI response, optional field, controls diversity of the response by limiting token selection;"),
            web_search: z.boolean().optional().describe("enable web search for current information. When enabled, the AI model can access and cite current web information;"),
        };
    }
    async handle(params) {
        try {
            const payload = {
                user_prompt: params.user_prompt,
                model_name: params.model_name,
            };
            if (params.temperature) {
                payload.temperature = params.temperature;
            }
            if (params.top_p) {
                payload.top_p = params.top_p;
            }
            if (params.web_search) {
                payload.web_search = params.web_search;
            }
            const response = await this.dataForSEOClient.makeRequest(`/v3/ai_optimization/${params.llm_type}/llm_responses/live`, 'POST', [payload], true);
            return this.validateAndFormatResponse(response);
        }
        catch (error) {
            return this.formatErrorResponse(error);
        }
    }
}
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