Google Search MCP Server

A Next.js App Router deployment that exposes a Model Context Protocol (MCP) server focused on organic search research. The server provides two tools—get_autocomplete_suggestions and get_trend_index— built on top of Google Suggest and Google Trends. No OAuth credentials are required; both tools rely on public endpoints with careful validation and rate limiting.

Features

• Google Autocomplete: Expands a seed query into the real phrases Google users type right now.
• Google Trends: Returns interest-over-time indices for any keyword with optional geo and category filters.
• Next.js 15 App Router with strict TypeScript, ESLint, and Prettier configuration.
• Structured MCP responses with consistent error handling and lightweight rate limiting.

Requirements

• Node.js 18.18 or newer.
• pnpm or npm for dependency management.

Getting started locally

pnpm install
pnpm dev

The development server defaults to http://localhost:3000.

MCP tools

All tools share the same POST endpoint: POST /api/mcp with JSON payload {"tool": "<name>", "input": { ... } }. Responses follow the ToolResponse shape ({ ok: true, data } or { ok: false, error }).

ping

{
  "tool": "ping"
}

Result:

{
  "ok": true,
  "data": { "status": "ok" }
}

get_autocomplete_suggestions

Fetches live suggestions from Google Suggest for the provided query.

{
  "tool": "get_autocomplete_suggestions",
  "input": { "query": "toroidal transformer" }
}

Result:

{
  "ok": true,
  "data": {
    "query": "toroidal transformer",
    "suggestions": [
      "toroidal transformer winding",
      "toroidal transformer core",
      "toroidal transformer advantages"
    ]
  }
}

get_trend_index

Returns Google Trends interest-over-time data. Optional fields (geo, timeRange, category, property) map directly to the underlying Trends API.

{
  "tool": "get_trend_index",
  "input": {
    "keyword": "toroidal transformer",
    "timeRange": "today 12-m",
    "geo": "US"
  }
}

Result (truncated):

{
  "ok": true,
  "data": {
    "keyword": "toroidal transformer",
    "geo": "US",
    "timeRange": "today 12-m",
    "seriesLabels": ["toroidal transformer"],
    "averages": [42],
    "points": [{ "time": "1704067200", "formattedTime": "Dec 31, 2023", "values": [37] }]
  }
}

Rate limiting & errors

• Rate limiting: 10 requests per minute per IP/user agent combination. Exceeding the budget returns 429 with code: RATE_LIMIT_EXCEEDED.
• Upstream issues: Failures from Google endpoints map to UPSTREAM_ERROR with the HTTP status and service name.
• Validation errors: Invalid input payloads return INVALID_ARGUMENT and include Zod field errors.
• Unexpected failures: Return 500 with code: UNKNOWN but never leak secrets.

ChatGPT Developer Mode integration

Add a remote MCP server in ChatGPT using the following configuration:

• Server URL: https://<your-app>.vercel.app/api/mcp
• Tools: Automatically discovered (ping, get_autocomplete_suggestions, get_trend_index).
• Auth flow: None required—both tools rely on public Google endpoints.

Example invocation in ChatGPT:

{
  "tool": "get_trend_index",
  "input": { "keyword": "toroidal transformer" }
}

Expect a JSON payload with interest-over-time points that you can combine with autocomplete suggestions to build keyword clusters or validate seasonal demand.

Troubleshooting

Symptom	Resolution
RATE_LIMIT_EXCEEDED	Wait until the window resets (~60 seconds) or reduce tool frequency.
UPSTREAM_ERROR	Google responded with an error status. Retry later or adjust the query/filters.
UNKNOWN	Check server logs for the underlying exception.

Acceptance checklist

• [x] Autocomplete MCP tool returning Google Suggest phrases.
• [x] Trends MCP tool returning interest-over-time data.
• [x] README covering setup, usage, and troubleshooting.