# X (twitter) Communities Search (`datamagnet/x-twitter-communities-search`) Actor Search X twitter communities by keyword and return matching community results. - **URL**: https://apify.com/datamagnet/x-twitter-communities-search.md - **Developed by:** [Datamagnet](https://apify.com/datamagnet) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## X Community Search Scraper Find X communities by keyword and quickly collect a clean list of matching communities in one place. X Community Search is built for marketers, researchers, creators, and growth teams who want to discover relevant communities without manually browsing for hours. Use it to search X communities by topic, review useful details like community name, description, member count, and direct links when available, and export the results for easy analysis. If you need a simple X community search extractor for lead discovery, audience research, or trend tracking, this actor gives you a fast and readable workflow. ### Key Features - Extract matching X communities from a keyword search in a clean, easy-to-review format. - Collect useful community details such as name, description, member count, and direct links when available. - Load additional results automatically when your search returns more communities than fit on one page. - Filter your research by topic, brand, niche, competitor, or audience interest. - Save time by turning a manual browsing task into a repeatable data collection workflow. - Export results for reporting, comparison, outreach planning, or internal sharing. - Keep your search focused on the exact keyword you care about, with no extra setup. ### Use Cases #### Market Research Researchers and analysts can search for communities around a product category, hobby, or industry term and review the names, descriptions, and member counts to understand where conversations are happening. This helps teams identify which topics have active communities and which niches may be underserved. #### Audience Discovery Creators, social media managers, and brand teams can look for communities related to their audience interests and see how those communities describe themselves. The community name and description make it easier to judge whether a group matches the people they want to reach. #### Competitor and Brand Monitoring Businesses can search for their own brand name, competitor names, or product terms to find communities that mention them. Member count and community descriptions help teams prioritize which communities may deserve closer attention or engagement. #### Partnership and Outreach Research Partnership managers can use the search results to find communities that align with a campaign, event, or collaboration idea. A direct link or identifier, when available, makes it easier to review the community and decide whether it is worth contacting or joining. #### Content Planning Writers, creators, and newsletter teams can search for topic-based communities to see what people are gathering around. The descriptions and names can inspire content ideas, help validate demand, and reveal language that resonates with the audience. #### Lead Qualification Sales and growth teams can search for communities tied to a niche, profession, or interest area and use the results to spot potential audience segments. The cleaned list makes it easier to compare communities and decide where outreach or community participation may be most relevant. ### Input | Field | Type | Required | Description | Example | |---|---|---:|---|---| | query | string | Yes | Enter the word or phrase you want to search for in communities. | superman | | max_results | integer | No | Set the maximum number of results to return. The actor will load more results automatically if needed. | 10 | ### Output | Field | Type | Description | |---|---|---| | search term | string | The keyword you searched for, so you can quickly remember what the results relate to. | ### Sample Output ```json { "search term": "superman" } ```` ### How It Works 1. You enter the keyword or phrase you want to search for. 2. You choose how many matching communities you want to see. 3. The actor searches X communities and gathers the best matching results. 4. If there are more results than fit at once, it continues loading them automatically until it reaches your limit. 5. You receive a cleaned list that is ready to review, share, or export. ### Getting Started Getting started is simple and does not require any coding knowledge. Click **Try for free**, enter your search keyword, choose the maximum number of results if needed, and click **Run**. In a short time, you will get a clean list of matching X communities that you can review right away. Your results are available in JSON, CSV, or Excel, making it easy to use them in reports, spreadsheets, or other business workflows. ### Frequently Asked Questions #### Do I need technical skills? No. This actor is designed for non-technical users who want a simple way to search X communities and collect results. You only need to enter a keyword and choose how many results you want. #### How fast does it run? It usually runs quickly, but the total time depends on how broad your search is and how many results you request. Smaller searches finish faster, while larger searches may take a bit longer because the actor automatically gathers more matches when available. #### What format is the output? You can work with the results in formats that are easy to use for business tasks, including JSON, CSV, and Excel. That makes it simple to review the data in a spreadsheet, share it with your team, or import it into your own workflow. #### Is this legal to use? This actor is intended for lawful research, analysis, and business use. You should always make sure your use follows applicable laws, platform rules, and your organizationโ€™s policies, especially if you plan to use the results for outreach or commercial decisions. #### Can I schedule it to run automatically? Yes, you can set it up to run on a schedule if you want regular updates. This is useful for tracking new communities over time, monitoring topic growth, or keeping an ongoing list of relevant groups up to date. # Actor input Schema ## `query` (type: `string`): Enter the word or phrase you want to search for in communities. ## `max_results` (type: `integer`): Set the maximum number of results to return. The actor will load more results automatically if needed. ## Actor input object example ```json { "query": "superman", "max_results": 10 } ``` # 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 = { "query": "superman" }; // Run the Actor and wait for it to finish const run = await client.actor("datamagnet/x-twitter-communities-search").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "query": "superman" } # Run the Actor and wait for it to finish run = client.actor("datamagnet/x-twitter-communities-search").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "superman" }' | apify call datamagnet/x-twitter-communities-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datamagnet/x-twitter-communities-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "X (twitter) Communities Search", "description": "Search X twitter communities by keyword and return matching community results.", "version": "0.0", "x-build-id": "WuiNXUp3e4WEb6eFq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datamagnet~x-twitter-communities-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datamagnet-x-twitter-communities-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datamagnet~x-twitter-communities-search/runs": { "post": { "operationId": "runs-sync-datamagnet-x-twitter-communities-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datamagnet~x-twitter-communities-search/run-sync": { "post": { "operationId": "run-sync-datamagnet-x-twitter-communities-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "query" ], "properties": { "query": { "title": "Search keyword", "type": "string", "description": "Enter the word or phrase you want to search for in communities." }, "max_results": { "title": "Max results", "type": "integer", "description": "Set the maximum number of results to return. The actor will load more results automatically if needed.", "default": 10 } } }, "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 } } } } } } } } } } ```