Which integrations are available for this server?

Enables querying Google Trends data for search interest, term comparison, related queries, trending searches, and regional interest.

How do I use google-trends-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@google-trends-mcp Compare 'coffee', 'tea', and 'matcha' in Canada" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

google-trends-mcp

by purahmanian

Overview Schema Source Related Servers Score Discussions Admin

TypeScript

Remote

google-trends-mcp

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

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: Google Trends MCP Server

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.

ParametersJSON Schema

Name	Required	Description	Default
`geo`	No	Two-letter country code or empty for worldwide.
`terms`	Yes	Search terms to compare (2-5).
`timeframe`	No	Trends timeframe string.	today 12-m

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and openWorldHint. The description adds that it returns time series, averages, and identifies the highest interest, expanding on the output behavior without contradicting annotations. This adds moderate value beyond the structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is concise yet informative. It front-loads the main action and deliverables, making it easy for an AI agent to quickly understand the tool's functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema, the description thoroughly explains what the tool returns (time series, averages, highest interest term). Given the low complexity and full schema coverage, the description provides sufficient context for correct use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already describes all parameters (geo, terms, timeframe) with defaults and constraints. The description does not add additional meanings beyond the schema, which is acceptable. A baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: compare 2-5 search terms using Google Trends normalized interest scores, and specifies the outputs (time series, averages, highest interest). It distinguishes from siblings like interest_over_time (single term) and related_queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies that 2-5 terms are required, which is a key constraint. While it doesn't explicitly state when to use this tool over siblings, the sibling names (e.g., interest_over_time, related_queries) imply the context. A clear usage guideline would improve this dimension.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.

ParametersJSON Schema

Name	Required	Description	Default
`geo`	No	Two-letter country code to drill into sub-regions (e.g. "US" gives US states), or empty for worldwide country-level breakdown.
`term`	Yes	The search term to get regional interest for.
`timeframe`	No	Trends timeframe string.	today 12-m

TDQS

A4.1/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds that it returns top regions with highest relative interest, which is useful but does not cover other behavioral traits like data freshness or pagination. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose, no extraneous information. Every part is necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the read-only nature, rich schema descriptions, and annotations, the description adequately covers input (geo, term, timeframe) and output (top regions with relative interest). No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions already present. The description adds slight nuance for geo (sub-country vs country) but largely restates schema info, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and resource 'Google Trends interest scores broken down by region'. It distinguishes from sibling tools like interest_over_time (time) and compare_terms (comparison) by focusing on regional breakdown.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the effect of the geo parameter (sub-country vs country), providing clear context. However, it does not explicitly state when to use this tool over alternatives or provide any exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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.

ParametersJSON Schema

Name	Required	Description	Default
`geo`	No	Two-letter country code (e.g. "US") or empty for worldwide.
`terms`	Yes	Search terms (1-5).
`timeframe`	No	Trends timeframe string, e.g. "today 12-m", "today 5-y", "now 7-d".	today 12-m

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint and openWorldHint, and the description adds that it returns a time series, which provides extra behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: the first states the purpose, the second gives a use case. No wasted words, front-loaded structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description explains the return format (time series with one value per term per data point). It covers core functionality and use case, though it omits edge cases or error conditions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for each parameter. The description mentions 'up to 5 terms' and 'time range' but adds no new detail about parameter formats or constraints beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches Google Trends interest scores (0-100) for up to 5 terms over a time range. The verb and resource are specific, but it does not explicitly differentiate from sibling tools like 'trending_now' or 'compare_terms'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context (spotting seasonality, growth, decline) but does not specify when not to use this tool or compare it to alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

related_queriesA

Read-only

Get rising and top related search queries for a given term from Google Trends. Rising queries have seen the largest recent growth; top queries have the most overall volume. Useful for discovering adjacent keywords and content ideas.

ParametersJSON Schema

Name	Required	Description	Default
`geo`	No	Two-letter country code or empty for worldwide.
`term`	Yes	The search term to get related queries for.
`timeframe`	No	Trends timeframe string.	today 12-m

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint and openWorldHint. The description adds behavioral context by defining rising and top queries and specifying the data source (Google Trends). It goes beyond annotations without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action, and every word adds value. No fluff or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains the purpose and result categories. It could be more complete by describing the output format, but for a simple tool with annotations, it is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for all three parameters. The tool description adds value by explaining the two types of results (rising and top), which is not in the schema, enhancing parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it gets rising and top related search queries for a given term from Google Trends, using specific verbs and indicating the resource. It distinguishes itself from siblings by focusing on related queries rather than trends over time or by region.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions the tool is useful for discovering adjacent keywords and content ideas, implying usage context, but lacks explicit guidance on when to use it versus sibling tools like interest_over_time or compare_terms.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

trending_nowA

Read-only

Get today's daily trending searches for a country from Google Trends. Returns the top trending queries with estimated traffic and linked news articles.

ParametersJSON Schema

Name	Required	Description	Default
`geo`	No	Two-letter country code (e.g. "US", "GB", "IN", "AU").	US

TDQS

A4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint and openWorldHint. The description adds context about the return format (top queries, traffic, news articles), which goes beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that immediately states the tool's purpose and output. No unnecessary words or clauses, making it efficient and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple tool (1 optional param, no output schema), the description covers the core functionality, output, and parameter sufficiently. However, it could mention that only one day's data is returned or clarify the 'estimated traffic' metric.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter (geo) with full schema description coverage (100%). The description does not add further meaning beyond the schema's description of a two-letter country code. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool gets daily trending searches from Google Trends for a country, and specifies it returns top trending queries with traffic estimates and news articles. This uniquely distinguishes it from siblings like interest_over_time and related_queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for fetching current trending searches but does not explicitly state when to use this tool versus alternatives (e.g., interest_over_time for historical trends). No when-not or direct comparisons are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

5 tool updatesv0.1.1Jul 30, 2026
- First observedcompare_terms
- First observedinterest_by_region
- First observedinterest_over_time
- First observedrelated_queries
- First observedtrending_now

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.2/5.0

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.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

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google-trends-mcp

What it does

Quick start

Claude Desktop

Claude Code

OpenAI Codex CLI

Example conversations

Development

Rate limits and blocking

Built by

Privacy

License

Available Tools

Tool Schema Changelog

Maintenance

Resources

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Related MCP Connectors

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Trends MCPofficial

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