Building an MCP server so Claude can query my SaaS analytics directly

Last week I shipped a Model Context Protocol (MCP) server for my analytics SaaS. Now Claude Desktop, Cursor, and any MCP compatible client can query traffic, revenue, and funnel data directly. This is a walkthrough of how I built it, what worked, and a couple of patterns that surprised me. What MCP is, briefly MCP is a protocol that lets AI clients invoke tools and read resources from external servers. Think of it as REST for LLM tool calling, with a stable schema and discovery. Server skeleton import { Server } from '@modelcontextprotocol/sdk/server/index.js' import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js' const server = new Server({ name: 'zenovay', version: '1.0.0', }, { capabilities: { tools: {}, resources: {} } }) Defining tools server.setRequestHandler('tools/list', async () => ({ tools: [ { name: 'get_traffic', description: 'Get pageview and visitor counts for a