Google Trends Remote MCP Server
Server Details
Google Trends interest over time, by region, and related queries and topics, as JSON.
- Status
- Healthy
- Uptime
- 100.0% over the last 24 hours
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- HasData/google-trends-mcp
- GitHub Stars
- 5
- Server Listing
- Google Trends MCP Server
- ChatGPT
- –
- Claude
- –
TDQS
Scored across 1 tool
There is only one tool, so there is no risk of selecting the wrong tool from an overlapping set. Its purpose is clearly and specifically to retrieve Google Trends data.
The name hasdata_google_trends_search_getTrendsData mixes snake_case prefixing with a camelCase action suffix, which is readable but not internally consistent. With only one tool, cross-tool naming consistency cannot be evaluated, but the convention is mixed.
A single tool can be defensible for a focused Google Trends endpoint because it consolidates multiple data types and parameters. However, one tool is thin for an MCP server surface and sits at the borderline of the typical 3-15 tool range.
The tool covers the main Google Trends retrieval surfaces: timeseries, geo breakdowns, related topics/queries, and many targeting parameters. Minor gaps may exist for other Google Trends features such as real-time trending searches, but the core read-only domain is well covered.
Publisher details
- Operator
- HasData · Publisher source
- Operator website
- https://hasdata.com · Publisher source
- Vendor relationship
- Independent · Publisher source
- Documentation
- https://docs.hasdata.com/mcp-server · Publisher source
- Trust center
- Not available
- Restrictions
- A free HasData account covers 1,000 credits a month with no card. Heavier use needs a paid plan. No admin approval, no regional limits and no custom OAuth app. · Publisher source
Available Tools
1 toolhasdata_google_trends_search_getTrendsDatagoogle_trends_search: GET /ARead-onlyInspect
Get Google Trends Data
Pulls Google Trends data for one or more queries with geo targeting, region granularity (country/subregion/metro/city), date range, category, time zone, Google property (web, images, news, shopping, YouTube), and dataType (timeseries, geoMap, relatedTopics, relatedQueries). Returns interest-over-time series, geo-level breakdowns, and rising/top related topics/queries with relative scores. Use for keyword/content strategy, demand forecasting, seasonality analysis, topic discovery, campaign timing, and adding live-trend signals to marketing or research agents.
Inputs: q (required), tz, cat, geo, +4 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Related MCP Connectors
Google Trends interest over time, by region, related queries and Trending now, as JSON.
Google Trends data as JSON: interest over time, rising and top queries, regions, Trending Now.
Google Trends data via Apify: interest over time, by region, related queries and Trending Now.
Google Trends interest, regions, rising queries and Trending Now, via Apify
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables fetching Google Trends interest over time, regional breakdowns, and related topics and queries as JSON, with optional geography, date range, category, time zone, and Google property filters.MIT
- AlicenseNot gradedqualityCmaintenanceQueries Google Trends for interest over time, related and rising queries, regional interest, and trending topics without requiring an API key or account.2MIT
- AlicenseAqualityBmaintenanceEnables retrieval of relative search interest, regional breakdowns, related queries, and related topics for search terms, with optional geo, timeframe, category, and search-property filters, and comparison of up to five terms on a shared scale.1770 npmMIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query Google Trends for search-interest signals, returning stable JSON envelopes with calibrated searches/day estimates, relative comparisons across keywords, related and rising queries, regional interest, and country-level Trending Now data. It also surfaces explicit status and error codes so agents can distinguish partial or failed results from real numbers.MIT
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