Tool-calling assistants need stable JSON, predictable quotas, and source strings that do not drift. Trends MCP exposes get_trends, get_growth, get_ranked_trends, and get_top_trends over HTTP MCP and REST so Claude, ChatGPT, Cursor, Windsurf, and custom services can pull live signals from Google, YouTube, TikTok, Reddit, Amazon, and more without maintaining scrapers.
Many prototypes bolt on a single scraper or an unofficial library. Those dependencies break on frontend changes, return relative indices only, or cover one platform. Production copilots need contracts that stay valid across releases. Trends MCP centralizes source maintenance and exposes a narrow tool surface the model can plan against.
Briefing workflows call get_trends to load history before summarization. Prioritization workflows call get_growth to score options. Open-ended ideation calls get_ranked_trends or get_top_trends when the user did not supply a keyword. Each tool returns structured JSON so follow-up logic can branch on growth percentages or feed labels without parsing prose.
MCP guidance from practitioners: treat the server as an information provider that returns rich structured context, keep tool descriptions explicit for the model, and prefer small, repeatable parameter sets as in agent-friendly server design notes.
Each keyword source has a dedicated page with copy tailored to that datatype, example calls, and keyword-format reminders: Google Search, Google Images, Google News, Google Shopping, YouTube, TikTok, Reddit, Amazon, Wikipedia, news volume, news sentiment, app downloads, npm, Steam.
MCP-compatible hosts load https://api.trendsmcp.ai/mcp with HTTP transport and an Authorization header. Pure services can mirror the examples on the Python trends API and JavaScript trends API pages using POST requests. The Model Context Protocol overview explains how those pieces fit for readers new to the standard. Source names and live feeds are listed under Data Sources in the docs.
Pass explicit source strings from the documentation, cap limit on ranked calls, and cache results when automation reruns the same keyword within minutes. Human-readable summaries belong after the tool output so factuality traces back to the API response.
Create a key on trendsmcp.ai, register the server in the client, and add the four tools to the system prompt with field-level descriptions copied from the API reference.
Tools for this workflow
get_trendsRetrieve full history for monitoring jobs that rerun on a schedule.
get_trends(keyword='react', source='npm', data_mode='weekly')
get_growthLet the assistant decide whether a topic warrants deeper research based on 1M to 12M change.
get_growth(keyword='react', source='npm, google search', percent_growth=['3M', '12M'])
get_ranked_trendsPopulate a ranked list for workflows that start without a user-supplied keyword.
get_ranked_trends(source='npm', sort='wow_pct_change', limit=20)
get_top_trendsAnswer what is trending now on a named feed for reactive briefs.
get_top_trends(type='Google Trends', limit=20)
FAQ