# Google Trends Scraper - Interest Over Time, Peaks & Compare (`santhej/google-trends-scraper`) Actor Scrape Google Trends for any keywords: interest-over-time series, average, peak and latest interest, plus side-by-side comparison of up to 5 terms. Pick country and time range. Clean JSON/CSV for trend research and content timing. No API keys. - **URL**: https://apify.com/santhej/google-trends-scraper.md - **Developed by:** [Santhej Kallada](https://apify.com/santhej) (community) - **Categories:** SEO tools, MCP servers - **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Google Trends Scraper — Interest Over Time, Peaks & Keyword Comparison **Track demand before you bet on it. Pull Google Trends interest-over-time for any keyword, compare up to 5 terms side by side, and spot what's rising or fading — as clean, structured data.** No more screenshotting the Trends website. Get the actual numbers: average interest, peak, latest value, and the full time series for every keyword — ready for spreadsheets, dashboards, and AI agents. --- ### What you get per keyword - 📈 **Interest-over-time series** — the full data behind the Trends chart. - 📊 **Average, peak & latest interest** — instant read on momentum. - 🆚 **Side-by-side comparison** — pit up to 5 keywords against each other. - 🌍 **Country or worldwide** — localize demand by market. - 🔎 **Web, News, YouTube, Images or Shopping** — trends across Google properties. ### Perfect for - **Content & SEO timing** — publish while a topic is climbing, not after it peaks. - **Product & market validation** — confirm demand is growing before you invest. - **Trend monitoring** — track brands, niches, and seasonal patterns over time. - **Newsrooms & social** — ride rising search interest with timely content. - **AI agents** — feed structured trend data into automated research and MCP tools. ### How to use it 1. Enter your **keywords** (compared in groups of 5). 2. Pick a **time range**, **property**, and optional **country**. 3. Run it — export JSON/CSV or pull via the API. #### Example input ```json { "keywords": ["bitcoin", "ethereum", "solana"], "timeRange": "past_12_months", "trendType": "web" } ```` #### Example output (one row per keyword) ```json { "keyword": "bitcoin", "average_interest": 64, "peak_interest": 100, "latest_interest": 58, "time_range": "past_12_months", "series": [{ "date": "2025-05-01", "value": 72 }, { "date": "2025-06-01", "value": 80 }] } ``` ### Pricing Pay per keyword analyzed — no monthly fee, no minimum. ### FAQ **Can I compare keywords?** Yes — terms are compared in groups of 5, just like the Trends UI. **Worldwide or by country?** Both — leave country blank for worldwide or pick a market. **Which Google properties?** Web, News, YouTube, Images, and Shopping search. **Good for AI agents?** Yes — clean JSON, ideal for MCP servers, n8n, Make, and LLM agents. *** *Tags: google trends scraper, google trends api, interest over time, trend analysis, keyword trends, search demand, trending topics, seo research, content planning.* # Actor input Schema ## `keywords` (type: `array`): Keywords/topics to analyze. Compared in groups of 5. One per line. Up to 100 per run. ## `timeRange` (type: `string`): Period to analyze. ## `trendType` (type: `string`): Which Google Trends property to query. ## `locationCode` (type: `string`): Limit interest to a country. Leave blank for worldwide. US 2840, UK 2826, India 2356. ## Actor input object example ```json { "keywords": [ "bitcoin", "ethereum", "solana" ], "timeRange": "past_12_months", "trendType": "web", "locationCode": "" } ``` # Actor output Schema ## `dataset` (type: `string`): Interest-over-time per keyword. ## `summary` (type: `string`): Keywords and counts. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "bitcoin", "ethereum", "solana" ] }; // Run the Actor and wait for it to finish const run = await client.actor("santhej/google-trends-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "bitcoin", "ethereum", "solana", ] } # Run the Actor and wait for it to finish run = client.actor("santhej/google-trends-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "bitcoin", "ethereum", "solana" ] }' | apify call santhej/google-trends-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=santhej/google-trends-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Trends Scraper - Interest Over Time, Peaks & Compare", "description": "Scrape Google Trends for any keywords: interest-over-time series, average, peak and latest interest, plus side-by-side comparison of up to 5 terms. Pick country and time range. Clean JSON/CSV for trend research and content timing. No API keys.", "version": "0.0", "x-build-id": "9VMS4t088MnbBi6yU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/santhej~google-trends-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-santhej-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/santhej~google-trends-scraper/runs": { "post": { "operationId": "runs-sync-santhej-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/santhej~google-trends-scraper/run-sync": { "post": { "operationId": "run-sync-santhej-google-trends-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "keywords": { "title": "Keywords", "minItems": 1, "maxItems": 100, "type": "array", "description": "Keywords/topics to analyze. Compared in groups of 5. One per line. Up to 100 per run.", "items": { "type": "string" } }, "timeRange": { "title": "Time range", "enum": [ "past_7_days", "past_30_days", "past_90_days", "past_12_months", "past_5_years" ], "type": "string", "description": "Period to analyze.", "default": "past_12_months" }, "trendType": { "title": "Trends property", "enum": [ "web", "news", "youtube", "images", "froogle" ], "type": "string", "description": "Which Google Trends property to query.", "default": "web" }, "locationCode": { "title": "Country (optional)", "enum": [ "", "2840", "2826", "2124", "2036", "2356", "2276" ], "type": "string", "description": "Limit interest to a country. Leave blank for worldwide. US 2840, UK 2826, India 2356.", "default": "" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```