Google Trends MCP Server
Provides access to Google Trends data, including trending topics, trending questions, and API status.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Google Trends MCP Serverwhat are the top trending topics right now?"
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 Server
⚠️ IMPORTANT SECURITY NOTICE: Never commit API keys to version control. This package requires an API key to be set via environment variable.
An MCP (Model Context Protocol) server that provides access to Google Trends data through the Google Trends Scraper API.
Features
Status: Check the API status and health
Questions: Get trending questions from Google Trends
Trending: Get currently trending topics from Google Trends
Related MCP server: bigquery-google-trends-mcp
Installation
Option 1: Using npx (Recommended)
# Set your API key first
export GOOGLE_TRENDS_API_KEY="your-api-key-here"
# Run directly with npx
npx @andrewlwn77/google-trends-mcpOption 2: Global Installation
npm install -g @andrewlwn77/google-trends-mcpOption 3: Local Development
git clone <repository-url>
cd google-trends-mcp
npm install
npm run buildConfiguration
Optional: You can set the GOOGLE_TRENDS_API_KEY environment variable. If not set, a default API key will be used.
Get an API key from RapidAPI Google Trends Scraper
Set the environment variable:
# Option 1: Export in your shell export GOOGLE_TRENDS_API_KEY="your-api-key-here" # Option 2: Create a .env file (for local development) echo "GOOGLE_TRENDS_API_KEY=your-api-key-here" > .env
⚠️ Security: Never commit your .env file or API key to version control!
Usage
Running the server
# If installed globally or using npx
google-trends-mcp
# For local development
npm start
# For development with auto-reload
npm run devAvailable Tools
1. google_trends_status
Check the status of the Google Trends API.
Parameters:
language(optional): Language code (default: "en")country(optional): Country code (default: "US")
2. google_trends_questions
Get trending questions from Google Trends.
Parameters:
language(optional): Language code (default: "en")country(optional): Country code (default: "US")
3. google_trends_trending
Get currently trending topics from Google Trends.
Parameters:
language(optional): Language code (default: "en")country(optional): Country code (default: "US")
Example Usage with MCP Client
// Check API status
const status = await client.callTool('google_trends_status', {
language: 'en',
country: 'US'
});
// Get trending questions
const questions = await client.callTool('google_trends_questions', {
language: 'en',
country: 'US'
});
// Get trending topics
const trending = await client.callTool('google_trends_trending', {
language: 'en',
country: 'US'
});Configuration
The server can be configured using environment variables:
GOOGLE_TRENDS_API_KEY: Your RapidAPI key for the Google Trends Scraper API (optional, defaults to example key)
Development
Project Structure
google-trends-mcp/
├── src/
│ ├── index.ts # Main MCP server implementation
│ └── types.ts # TypeScript type definitions
├── tests/
│ ├── integration/ # API integration tests
│ ├── unit/ # Unit tests
│ └── helpers/ # Test helper utilities
├── package.json
├── tsconfig.json
├── .env.example
└── README.mdType Safety
This server is written in TypeScript and provides full type safety for:
API parameters
API responses
Error handling
Google Trends data structures
License
MIT
Available Tools
3 toolsgoogle_trends_questionsC
Get trending questions from Google Trends
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | Country code (e.g., "US") | US |
| language | No | Language code (e.g., "en") | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic action. No information about rate limits, data freshness, authentication, or any potential side effects is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loading the core purpose. It is appropriately sized for a simple tool with few parameters, though it sacrifices some detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description should explain what the returned data looks like (e.g., list of trending questions). It fails to provide this context, leaving the agent uncertain about the response format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with clear descriptions for both parameters (country code and language code). The description does not add any extra meaning beyond the schema, meeting the baseline for well-described parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get trending questions from Google Trends', indicating a specific verb and resource. However, it does not fully distinguish from siblings like google_trends_trending, which might also return trending items. A slightly more precise definition would help.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like google_trends_trending or google_trends_status. There are no context clues for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
google_trends_statusC
Check the status of the Google Trends API
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | Country code (e.g., "US") | US |
| language | No | Language code (e.g., "en") | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Merely says 'Check the status', without disclosing what 'status' means (e.g., API availability, latency, error codes) or any side effects. Lacks behavioral details needed for an agent to understand implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (single sentence) but at the cost of missing critical information. It is front-loaded but too minimal to be effective. Every word earns its place, but the description is underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without output schema and with vague description, the agent has no idea what the tool returns. No explanation of return format, error handling, or relationship to sibling tools. Inadequate for informed tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds no meaning to parameters (country, language). It fails to explain why a status check needs location codes or how they affect results, leaving the agent guessing about their role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb ('Check') and resource ('Google Trends API status'), clearly indicating the tool's purpose. It distinguishes from sibling tools (google_trends_questions, google_trends_trending) which likely focus on querying data rather than status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. No mention of prerequisites, typical use cases, or situations where this status check is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
google_trends_trendingB
Get currently trending topics from Google Trends
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | Country code (e.g., "US") | US |
| language | No | Language code (e.g., "en") | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavioral traits, but it only states the action without details on return format, data volume, authentication needs, or rate limits. 'Get' implies a read operation, but lacks sufficient depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. While concise, it could incorporate slight additional context without becoming verbose, hence a slight deduction.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional params, 100% schema coverage, no output schema needed), the description adequately conveys the core function. However, it lacks any mention of return value characteristics (e.g., array of topics), leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both 'country' and 'language' parameters with examples. The description adds no extra semantics beyond what the schema provides, meeting the baseline but not exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' and clearly identifies the resource 'currently trending topics from Google Trends'. It effectively distinguishes from sibling tools 'google_trends_questions' and 'google_trends_status', which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its siblings, nor does it mention any prerequisites or context for usage. An explicit comparison with 'google_trends_questions' or 'google_trends_status' is missing.
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.
3 tool updates
v1.0.0- First observed
google_trends_questions - First observed
google_trends_status - First observed
google_trends_trending
TDQS
Each tool has a clearly distinct purpose: one for trending questions, one for API status, and one for currently trending topics. There is no overlap or ambiguity.
All tools follow a consistent `google_trends_<noun>` pattern, with clear, descriptive names. The verb (get) is implied, and the naming is uniform.
Three tools is minimal but reasonable for a focused server. The count covers the core functionalities—trending topics, related questions, and status—without being excessive.
The server covers basic features like trending topics and questions but lacks tools for specific search queries (e.g., interest over time, comparisons). The surface is functional but not comprehensive.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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