Google Trends MCP Server

Search Trends Explorer

This project combines a Google Trends visualizer built with Next.js and a Model Context Protocol (MCP) server that exposes the same data as a tool you can connect to OpenAI or any MCP-compatible client. Both experiences call SearchAPI.io to retrieve the last 12 months of relative interest for a search term.

Prerequisites

• Node.js 18.18+ (recommended to avoid engine warnings)

• A SEARCH_API_KEY from SearchAPI.io

Create a .env file with:

SEARCH_API_KEY=your_key_here

Running the Next.js UI

npm install
npm run dev

Visit http://localhost:3000 to use the web interface.

Running the MCP Server

The MCP server exposes a single tool named fetch_google_trends over streamable HTTP.

npm install
npm run mcp:dev

The server listens on http://localhost:3000/mcp (honors the PORT env variable) and also serves GET /healthz for Render health checks.

Connecting from an MCP client

• MCP Inspector: npx @modelcontextprotocol/inspector --server http://localhost:3000/mcp

• OpenAI / other agents: add an HTTP MCP tool pointing to the same /mcp endpoint.

When invoked, fetch_google_trends expects a JSON payload:

{
  "term": "electric cars",
  "geo": "US",            // optional Google Trends geo code
  "category": "0"         // optional Google Trends category id
}

The tool responds with structured JSON containing the normalized timeline points.

Deploying the MCP server to Render.com

1. Create a new Web Service from this repository.

2. Set the start command to:

   npm run mcp:start

3. Add the environment variable SEARCH_API_KEY.

4. (Optional) Configure Render health checks to hit /healthz.

Render will inject PORT, which the server automatically respects.

Testing & Linting

npm run lint

Project Structure Highlights

• app/ – Next.js app router with UI and /api/trends endpoint.

• lib/trends.ts – Shared SearchAPI client used by both the API route and MCP tool.

• mcp/server.ts – Express + MCP server exposing the fetch_google_trends tool.