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google-trends-mcp

google-trends-mcp

by purahmanian

google-trends-mcp

Free Google Trends data inside any MCP-compatible AI client. No API key required.

CI npm


UNOFFICIAL ENDPOINT DISCLAIMER

This server communicates with the same internal endpoints that the trends.google.com frontend uses. These endpoints are undocumented and unofficial. Google can change, rate-limit, or remove them at any time without notice. This project is not affiliated with, endorsed by, or sponsored by Google LLC. "Google Trends" is a trademark of Google LLC.

If requests start failing, open an issue. The fix is usually a URL or parameter tweak.


What it does

Tool

Description

Example prompt

interest_over_time

Weekly interest scores (0-100) for up to 5 terms

"Show me interest in 'matcha latte' over the past year in the US"

compare_terms

Normalized comparison of 2-5 terms with winner callout

"Compare 'coffee', 'tea', and 'matcha' in Canada"

related_queries

Top and rising related search queries for a term

"What related queries are rising for 'cold plunge'?"

trending_now

Today's daily trending searches for a country

"What's trending on Google in the UK right now?"

interest_by_region

Regional breakdown of interest (country or sub-region)

"Which US states search for 'pickleball' most?"


Related MCP server: Trends MCP

Quick start

No API key is needed. Install and run via npx.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "google-trends": {
      "command": "npx",
      "args": ["-y", "google-trends-mcp"]
    }
  }
}

Claude Code

claude mcp add google-trends -- npx -y google-trends-mcp

OpenAI Codex CLI

Add to ~/.codex/config.toml:

[mcp_servers.google-trends]
command = "npx"
args = ["-y", "google-trends-mcp"]

Example conversations

Spotting seasonality:

"Use Google Trends to show me interest in 'pumpkin spice' over the past 5 years worldwide."

The model calls interest_over_time with terms=["pumpkin spice"], timeframe="today 5-y" and narrates the clear September-October spikes each year.

Keyword competition:

"Compare search interest in 'Notion', 'Obsidian', and 'Roam Research' in the US this year."

The model calls compare_terms, reads the averages, and identifies the winner with supporting time-series data.

Opportunity discovery:

"What are the fastest-rising related queries for 'sourdough bread' right now?"

The model calls related_queries and surfaces the rising queries, often revealing adjacent niches and trending subtopics.


Development

# Clone and install
git clone https://github.com/purahmanian/google-trends-mcp.git
cd google-trends-mcp
npm install

# Run tests (no network calls; all HTTP is mocked)
npm test

# Build TypeScript to dist/
npm run build

# Run the server locally (stdio mode)
node dist/index.js

Rate limits and blocking

Google does not publish a rate limit for these endpoints. In practice, a few requests per minute works reliably. If you hit HTTP 429 or get blocked, the server returns a descriptive error message. Waiting 2-5 minutes usually resolves it.


Built by

Built by Puya Ventures LLC. I build custom MCP servers and AI integrations for product teams and researchers. Get in touch: purahmanian@gmail.com | Portfolio: puyarahmanian.com

Part of the Product-Research MCP Suite: keepa-mcp · google-trends-mcp · junglescout-mcp


Privacy

This server runs entirely on your machine. It collects no telemetry and stores no data. The only network calls it makes are to Google Trends endpoints (trends.google.com), sending the search terms and region codes you ask about. No account or API key is involved. See Google's privacy policy: https://policies.google.com/privacy

License

MIT. See LICENSE.

Available Tools

5 tools
compare_termsA
Read-only

Compare 2-5 search terms against each other using Google Trends normalized interest scores. Returns the time series, averages per term, and identifies which term has the highest overall interest.

Inputs: terms (required), geo, timeframe.

interest_by_regionA
Read-only

Get Google Trends interest scores broken down by region (sub-country or country, depending on the geo parameter). Returns top regions with the highest relative interest for the given term.

Inputs: term (required), geo, timeframe.

interest_over_timeA
Read-only

Fetch Google Trends interest scores (0-100) for up to 5 search terms over a time range. Returns a time series with one value per term per data point. Useful for spotting seasonality, growth, or decline in search interest.

Inputs: terms (required), geo, timeframe.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

    TDQS

    A4.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: daily trending searches, time series for up to 5 terms, comparison of terms, related queries, and regional breakdown. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case (e.g., trending_now, interest_over_time, compare_terms). No deviation in style.

    Tool Count5/5

    With 5 tools, the set covers the essential Google Trends functionalities without being excessive. Each tool serves a core purpose, and the count is well-scoped for the domain.

    Completeness4/5

    The set covers key features: daily trending, interest over time, comparison, related queries, and regional interest. Minor gaps like real-time trends or category filtering are present but do not break core workflows.

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