MCP server

TrendFlow

dev.mory/trendflow

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

Google Trends data: interest over time, by region, related queries, and trending now.

Website Source

At a glance

Type

MCP server

Publisher

mory.dev (verified by the MCP Registry)

Status

Working at last check

Tools

8

Token cost

About 3,325 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http trendflow https://trendflow.mory.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.trendflow]
url = "https://trendflow.mory.dev/mcp"

Gemini CLI

{"mcpServers":{"trendflow":{"httpUrl":"https://trendflow.mory.dev/mcp"}}}

Cursor

{"mcpServers":{"trendflow":{"url":"https://trendflow.mory.dev/mcp"}}}

VS Code

{"servers":{"trendflow":{"type":"http","url":"https://trendflow.mory.dev/mcp"}}}

Antigravity

agy mcp add trendflow https://trendflow.mory.dev/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"trendflow","server_url":"https://trendflow.mory.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"trendflow","server_url":"https://trendflow.mory.dev/mcp"}

Tools

• get_interest_by_region ~591 tokens
  Break down search interest for one term by geography. Use this when the user asks where something is popular, or wants a regional or city-level comparison. Values are normalized relative interest (0-100 within the result set).
• get_interest_over_time ~630 tokens
  Get relative search interest for one or more terms over a historical period. Use this when the user asks how popular something is, whether it is rising or falling, or how several things compare — passing multiple keywords compares them on one scale. Values are normalized relative interest (0-100 wit
• get_related_queries ~562 tokens
  Find the top and rising searches related to a term. Use this for keyword discovery, SEO and content research, and spotting breakout queries. `top` is ranked by volume; `rising` is ranked by growth, where "Breakout" means growth too large to measure.
• get_trending_now ~368 tokens
  Lists the searches surging right now in a country, for questions about what is spiking without a term being named, and for news and real-time context. The `backend` parameter selects the source: "rpc" returns around 50 entries with growth percentages and a relative volume index; "rss" returns 10 en
• list_regions ~237 tokens
  Returns the geo codes Google Trends accepts. With no argument it lists every country; given a country code it lists that country's sub-regions — US states, German states, UK nations — each as a code and a name. Any code returned here can be passed as the `region` argument of the other tools.
• research_bulk ~402 tokens
  Researches up to 10 topics in a single call, each with the same full picture as `research_trend`: interest over time, where it is most searched, and related queries. Each topic is looked up on its own scale, so they are not comparable to one another. Use this when you need data across many topics —
• research_trend ~303 tokens
  Returns a full picture of one term in a single call: interest over time, where it is most searched, and the queries people search alongside it. Suited to open-ended research on a topic rather than one narrow question. Each section is fetched independently, so a partial result is normal: any section
• search_topics ~232 tokens
  Resolves a name — a company, product, person, technology, or concept — to its Google Trends topic id (`mid`), with a `type` field that distinguishes same-name entities such as Nike the company from Nike the goddess. A topic aggregates every spelling and translation of one concept, so it measures co

Browse

• SEO
• Translation
• News

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