Clado MCP Server

import { z } from "zod"; import { makeCladoRequest } from "../utils.js"; export const linkedinPostReactionsName = "linkedin_post_reactions"; export const linkedinPostReactionsDescription = "Retrieves reactions and engagement data for a specific LinkedIn post URL."; export const linkedinPostReactionsSchema = { post_url: z.string().describe("The LinkedIn post URL to analyze for reactions."), }; type LinkedinPostReactionsParams = { post_url: string; }; export const linkedinPostReactionsTool = async ({ post_url, }: LinkedinPostReactionsParams) => { const apiUrl = new URL("https://search.clado.ai/api/enrich/post-reactions"); apiUrl.searchParams.append("url", post_url); const response = await makeCladoRequest(apiUrl.toString(), {}); const responseData = await response.json(); if (responseData.error) { throw new Error( `Failed to get LinkedIn post reactions: ${JSON.stringify(responseData.error)}` ); } return { content: [ { type: "text" as const, text: `LinkedIn post reactions retrieved successfully: ${JSON.stringify(responseData, null, 2)}` } ] }; };