# Lemmy Keyword Monitor (`kempt_sprinkles/lemmy-keyword-monitor`) Actor Track Lemmy posts mentioning any keyword, brand, or competitor. The open Reddit alternative — structured data, scheduled daily. - **URL**: https://apify.com/kempt\_sprinkles/lemmy-keyword-monitor.md - **Developed by:** [Nikolas Gevorkyan](https://apify.com/kempt_sprinkles) (community) - **Categories:** Social media, Lead generation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.00 / 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. 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 ## Lemmy Keyword Monitor — Track Mentions on the Open Reddit Alternative **Know when Lemmy talks about your product, your competitor, or the problem you solve.** Lemmy Keyword Monitor is a no-code **lemmy keyword monitor** and **mention tracker** for Lemmy — the open-source, federated Reddit alternative where many communities migrated. It watches any keyword across Lemmy and delivers fresh posts as clean, structured data. Powered by the open Lemmy API — no key, no auth. Great for **lead generation**, **brand monitoring**, and **community research** on a fast-growing, developer- and privacy-friendly network. ### What you get | keyword | title | author | community | score | comments | createdAt | url | |---|---|---|---|---|---|---|---| | self hosted | Best self-hosted alternative to X? | alice | selfhosted | 42 | 18 | 2026-06-12 | https://lemmy.world/post/123 | ```json { "keyword": "self hosted", "source": "lemmy", "type": "post", "id": "https://lemmy.world/post/123", "title": "Best self-hosted alternative to X?", "snippet": "I've been looking for a lightweight, privacy-friendly option …", "author": "alice", "community": "selfhosted", "score": 42, "numComments": 18, "createdAt": "2026-06-12T08:14:03Z", "url": "https://example.com/tool", "lemmyUrl": "https://lemmy.world/post/123", "matchedIn": "title" } ```` Download as JSON, CSV, Excel, or via the Apify API. ### Use cases - **Lead generation** — catch people on Lemmy asking for a tool like yours. - **Brand monitoring** — track mentions of your product across federated communities. - **Competitor tracking** — follow what users say about rivals. - **Community research** — discover the questions and pain points of a niche audience. ### How to use 1. **Enter your keywords**. 2. **(Optional) Pick a Lemmy instance** — `lemmy.world` by default; it federates content network-wide. 3. **Run it — or schedule it daily**. 4. **Export or automate** — CSV/Sheets, or Slack/webhook/Make/Zapier via Apify integrations. ### Input parameters | Field | Type | Default | Description | |---|---|---|---| | `keywords` | array | **required** | Words or phrases to monitor. | | `instance` | string | `lemmy.world` | Lemmy instance to query. | | `timeRange` | enum | `day` | `hour` … `all`. | | `sort` | enum | `new` | `new`, `relevance`, `top`. | | `includeNsfw` | boolean | `false` | Include NSFW posts. | | `maxResultsPerKeyword` | integer | `50` | Max posts per keyword. | | `proxyConfiguration` | proxy | off | Optional. | ### Scheduling & integrations Built to run daily on autopilot via **Apify Schedules**, with **Google Sheets, Slack, email, webhooks, Make, and Zapier** integrations. ### Pricing Simple **pay-per-event**: a small fee per run start + a small fee per post found. A typical daily run costs a few cents; empty runs are near-free. ### FAQ **Do I need an API key?** No. Lemmy's API is fully open. **Which instance should I use?** `lemmy.world` is the largest and federates content from across the network, so it's a good default. You can point it at any instance. **How fresh is the data?** Real-time. `sort = new` returns the newest posts first. **What if a run finds nothing?** It writes one informational item per keyword, at near-zero cost. *** *Keywords: lemmy keyword monitor, lemmy mention tracker, reddit alternative monitor, lemmy scraper, lead generation lemmy, brand monitoring lemmy, fediverse monitoring.* # Actor input Schema ## `keywords` (type: `array`): Words or phrases to monitor on Lemmy (e.g. your product, a competitor, a topic). ## `instance` (type: `string`): Which Lemmy instance to search (it federates content from across the network). Default: lemmy.world. ## `timeRange` (type: `string`): How far back to search. For daily monitoring keep at "Past 24 hours". ## `sort` (type: `string`): "New" = newest first (best for monitoring); "Top" = highest score. ## `includeNsfw` (type: `boolean`): If enabled, posts marked NSFW are included. Off by default. ## `maxResultsPerKeyword` (type: `integer`): Maximum posts collected per keyword. ## `proxyConfiguration` (type: `object`): Optional. The Lemmy API is open; a proxy is only useful at very high volume. ## Actor input object example ```json { "keywords": [ "self hosted", "open source" ], "instance": "lemmy.world", "timeRange": "day", "sort": "new", "includeNsfw": false, "maxResultsPerKeyword": 50, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): No description # 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": [ "self hosted", "open source" ], "instance": "lemmy.world" }; // Run the Actor and wait for it to finish const run = await client.actor("kempt_sprinkles/lemmy-keyword-monitor").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": [ "self hosted", "open source", ], "instance": "lemmy.world", } # Run the Actor and wait for it to finish run = client.actor("kempt_sprinkles/lemmy-keyword-monitor").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": [ "self hosted", "open source" ], "instance": "lemmy.world" }' | apify call kempt_sprinkles/lemmy-keyword-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kempt_sprinkles/lemmy-keyword-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Lemmy Keyword Monitor", "description": "Track Lemmy posts mentioning any keyword, brand, or competitor. The open Reddit alternative — structured data, scheduled daily.", "version": "1.0", "x-build-id": "pWS13xZufHCd1IBTl" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kempt_sprinkles~lemmy-keyword-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kempt_sprinkles-lemmy-keyword-monitor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kempt_sprinkles~lemmy-keyword-monitor/runs": { "post": { "operationId": "runs-sync-kempt_sprinkles-lemmy-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kempt_sprinkles~lemmy-keyword-monitor/run-sync": { "post": { "operationId": "run-sync-kempt_sprinkles-lemmy-keyword-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "minItems": 1, "type": "array", "description": "Words or phrases to monitor on Lemmy (e.g. your product, a competitor, a topic).", "items": { "type": "string" } }, "instance": { "title": "Lemmy instance", "type": "string", "description": "Which Lemmy instance to search (it federates content from across the network). Default: lemmy.world.", "default": "lemmy.world" }, "timeRange": { "title": "Time range", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "How far back to search. For daily monitoring keep at \"Past 24 hours\".", "default": "day" }, "sort": { "title": "Sort by", "enum": [ "new", "relevance", "top" ], "type": "string", "description": "\"New\" = newest first (best for monitoring); \"Top\" = highest score.", "default": "new" }, "includeNsfw": { "title": "Include NSFW posts", "type": "boolean", "description": "If enabled, posts marked NSFW are included. Off by default.", "default": false }, "maxResultsPerKeyword": { "title": "Max results per keyword", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum posts collected per keyword.", "default": 50 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. The Lemmy API is open; a proxy is only useful at very high volume.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```