# Mastodon Scraper (`opendata-labs/mastodon-scraper`) Actor Scrape posts, hashtags, public timelines, and profiles from any Mastodon instance via the official public ActivityPub API. No login needed. Clean, flat output for JSON, CSV, or Excel, with auto pagination and media/reply filters. Works on any fediverse server. - **URL**: https://apify.com/opendata-labs/mastodon-scraper.md - **Developed by:** [Joao Paulo](https://apify.com/opendata-labs) (community) - **Categories:** Social media, AI, News - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Mastodon Scraper **Scrape posts, hashtags, public timelines, and account profiles from any Mastodon instance — fast, structured, and auth-free.** Built on the official public **Mastodon API v1** (ActivityPub / fediverse), so it works on `mastodon.social` or any other decentralized server. ### What it does Mastodon Scraper turns the public Mastodon REST API into clean, flat dataset rows you can export to JSON, CSV, or Excel. Point it at any instance, pick a mode, and collect data from the fediverse without logging in. Four modes: - **Hashtag posts** — every public post tagged with a given hashtag. - **Public timeline** — the instance's live public feed, local-only or full federated. - **Account posts** — all posts from a specific user's profile. - **Account info** — metadata for a single profile (followers, post count, bio). ### Features - Works on **any Mastodon instance** — just change the `instance` input. - No authentication, no cookies, no tokens — pure public API reads. - **Flattened output** — clean columns, not raw nested JSON blobs. - Automatic `max_id` pagination with a `maxItems` cap. - Optional filters: media-only posts and reply exclusion. - Polite request pacing plus automatic retries on transient HTTP errors. - Pay-per-result pricing friendly (PPE `item-scraped` events). ### Input | Field | Type | Description | |---|---|---| | `mode` | enum | `hashtag_posts`, `public_timeline`, `account_posts`, or `account_info`. | | `instance` | string | Mastodon host, e.g. `mastodon.social` (default). | | `hashtag` | string | Hashtag to scrape (with or without `#`). Required for `hashtag_posts`. | | `account` | string | Handle `username` or `username@instance.tld`. Required for account modes. | | `local` | boolean | Public timeline only: local instance (`true`) or federated (`false`). | | `onlyMedia` | boolean | Collect only posts that contain an image or video. | | `excludeReplies` | boolean | Account posts: skip replies to other users. | | `maxItems` | integer | Max rows to collect (default `1000`). | #### Example input ```json { "mode": "hashtag_posts", "instance": "mastodon.social", "hashtag": "technology", "onlyMedia": false, "maxItems": 500 } ```` ### Output example Each post becomes one flat row: ```json { "id": "112233445566778899", "url": "https://mastodon.social/@dev_user/112233445566778899", "createdAt": "2026-06-20T14:03:11.000Z", "language": "en", "content": "Open-source project just hit 1.0 🎉", "authorUsername": "dev_user", "authorDisplayName": "Dev User", "authorUrl": "https://mastodon.social/@dev_user", "authorFollowers": 5120, "repliesCount": 12, "reblogsCount": 87, "favouritesCount": 214, "mediaUrls": ["https://files.mastodon.social/media_attachments/.../original.png"], "hashtags": ["technology", "opensource"], "isReblog": false, "rebloggedBy": null, "inReplyToId": null } ``` The `account_info` mode produces its own flat schema (followers, following, statuses count, bio, created date, etc.). ### Use cases - **Brand monitoring** — track mentions of your product or company across the fediverse via hashtag mode. - **OSINT & research** — monitor public discussion and sentiment on decentralized platforms. - **Journalism** — follow emerging stories and trending hashtags on Mastodon. - **AI / ML training data** — collect open social text at scale from a permissive, open protocol. ### Why this actor Mastodon exposes a **stable, official public REST API** backed by ActivityPub. This scraper talks to that API directly instead of fragile HTML parsing, so it keeps working through UI changes and runs against **any Mastodon server** in the fediverse. No login, no rate-limit gymnastics, no brittle selectors — just structured decentralized social data. *** *Keywords: Mastodon scraper, Mastodon API, scrape Mastodon, ActivityPub, fediverse data, decentralized social, Mastodon posts, hashtag scraper, federated Twitter alternative, brand monitoring.* # Actor input Schema ## `mode` (type: `string`): What to scrape. 'hashtag\_posts' collects posts for a hashtag, 'public\_timeline' reads the instance's public/federated feed, 'account\_posts' lists a user's posts, 'account\_info' fetches a single profile's metadata. ## `instance` (type: `string`): Hostname of the Mastodon instance to target (without https://). Works with any Mastodon server in the fediverse. ## `hashtag` (type: `string`): Hashtag to scrape, with or without the leading '#'. Required for 'hashtag\_posts' mode. ## `account` (type: `string`): Account handle to scrape. Use 'username' for a local account or 'username@instance.tld' for a remote one, with or without the leading '@'. Required for 'account\_posts' and 'account\_info' modes. ## `local` (type: `boolean`): For 'public\_timeline' mode: if true, only posts from this instance; if false, the full federated timeline. ## `onlyMedia` (type: `boolean`): If true, only collect posts that contain an image or video attachment. ## `excludeReplies` (type: `boolean`): For 'account\_posts' mode: if true, skip posts that are replies to other users. ## `maxItems` (type: `integer`): Maximum number of rows to push to the dataset. Scraping stops once this is reached. ## Actor input object example ```json { "mode": "hashtag_posts", "instance": "mastodon.social", "hashtag": "technology", "account": "Gargron", "local": false, "onlyMedia": false, "excludeReplies": false, "maxItems": 1000 } ``` # 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 = { "instance": "mastodon.social", "hashtag": "technology", "account": "Gargron" }; // Run the Actor and wait for it to finish const run = await client.actor("opendata-labs/mastodon-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 = { "instance": "mastodon.social", "hashtag": "technology", "account": "Gargron", } # Run the Actor and wait for it to finish run = client.actor("opendata-labs/mastodon-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 '{ "instance": "mastodon.social", "hashtag": "technology", "account": "Gargron" }' | apify call opendata-labs/mastodon-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=opendata-labs/mastodon-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Mastodon Scraper", "description": "Scrape posts, hashtags, public timelines, and profiles from any Mastodon instance via the official public ActivityPub\nAPI. No login needed. Clean, flat output for JSON, CSV, or Excel, with auto pagination and media/reply filters. Works\non any fediverse server.", "version": "0.1", "x-build-id": "Zj0MAHWEAzIYtvc9k" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/opendata-labs~mastodon-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-opendata-labs-mastodon-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/opendata-labs~mastodon-scraper/runs": { "post": { "operationId": "runs-sync-opendata-labs-mastodon-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/opendata-labs~mastodon-scraper/run-sync": { "post": { "operationId": "run-sync-opendata-labs-mastodon-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", "required": [ "mode", "instance" ], "properties": { "mode": { "title": "Scrape mode", "enum": [ "hashtag_posts", "public_timeline", "account_posts", "account_info" ], "type": "string", "description": "What to scrape. 'hashtag_posts' collects posts for a hashtag, 'public_timeline' reads the instance's public/federated feed, 'account_posts' lists a user's posts, 'account_info' fetches a single profile's metadata.", "default": "hashtag_posts" }, "instance": { "title": "Mastodon instance", "type": "string", "description": "Hostname of the Mastodon instance to target (without https://). Works with any Mastodon server in the fediverse.", "default": "mastodon.social" }, "hashtag": { "title": "Hashtag", "type": "string", "description": "Hashtag to scrape, with or without the leading '#'. Required for 'hashtag_posts' mode." }, "account": { "title": "Account", "type": "string", "description": "Account handle to scrape. Use 'username' for a local account or 'username@instance.tld' for a remote one, with or without the leading '@'. Required for 'account_posts' and 'account_info' modes." }, "local": { "title": "Local only (public timeline)", "type": "boolean", "description": "For 'public_timeline' mode: if true, only posts from this instance; if false, the full federated timeline.", "default": false }, "onlyMedia": { "title": "Only posts with media", "type": "boolean", "description": "If true, only collect posts that contain an image or video attachment.", "default": false }, "excludeReplies": { "title": "Exclude replies (account posts)", "type": "boolean", "description": "For 'account_posts' mode: if true, skip posts that are replies to other users.", "default": false }, "maxItems": { "title": "Max items", "minimum": 1, "type": "integer", "description": "Maximum number of rows to push to the dataset. Scraping stops once this is reached.", "default": 1000 } } }, "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 } } } } } } } } } } ```