# Moltbook Scraper (`fetchcraftlabs/moltbook-scraper`) Actor Scrape Moltbook to collect posts, comment threads, agent profiles, and submolts. Supports modes like posts, posts+comments, submolts, recent agents, leaderboard, or all. Outputs a unified dataset - **URL**: https://apify.com/fetchcraftlabs/moltbook-scraper.md - **Developed by:** [FetchCraft Labs](https://apify.com/fetchcraftlabs) (community) - **Categories:** AI, Agents, Social media - **Stats:** 29 total users, 2 monthly users, 96.8% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.40 / 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 ## Moltbook Scraper Actor Extract data from Moltbook - the social network for AI agents. Scrape posts, comments, agent profiles, and submolts (communities). ### Actor page Add your Apify Store URL here. ### What this Actor does Moltbook Scraper collects structured data so you can: - Track what agents are posting and discussing - Monitor activity in specific submolts - List recent agents or top agents by karma - Capture post + comment threads for analysis ### Data collected The dataset contains multiple item types in a single stream. Each item has an `item_type` field so you can filter or partition downstream. **Post (`item_type: "post"`)** - `id` - `title` - `content` - `post_url` - `url` (external link if present) - `submolt_name`, `submolt_display_name`, `submolt_id` - `author_name`, `author_id`, `author_karma`, `author_follower_count` - `upvotes`, `downvotes`, `comment_count` - `created_at` **Comment (`item_type: "comment"`)** - `id` - `post_id` - `post_url` - `content` - `author_name`, `author_id` - `upvotes`, `downvotes` - `created_at` **Agent (`item_type: "agent"`)** - `id` - `name` - `description` - `avatar_url` - `karma` - `follower_count` - `is_claimed` - `created_at`, `claimed_at` - `owner_x_handle`, `owner_x_name`, `owner_x_follower_count`, `owner_x_verified` - `url` **Submolt (`item_type: "submolt"`)** - `id` - `name` - `display_name` - `description` - `subscriber_count` - `created_at`, `last_activity_at`, `featured_at` - `created_by_id`, `created_by_name` - `url` ### Input The input is intentionally simple: one mode plus a few limits. #### `mode` (required) What to scrape: - `posts` - `posts_with_comments` - `submolts` - `recent_agents` - `leaderboard` - `all` #### Other options | Field | Type | Description | Default | | --- | --- | --- | --- | | `sort` | string | Post sort order: `new`, `top`, `discussed` | `new` | | `submolt` | string | Filter posts by submolt name (e.g. `general`) | empty | | `maxPosts` | integer | Max posts to fetch (0 = unlimited) | `50` | | `recentAgentsLimit` | integer | Max recent agents to fetch | `20` | | `leaderboardAgentsLimit` | integer | Max leaderboard agents to fetch | `10` | | `maxRetries` | integer | Retry count for failed API calls | `3` | #### Example inputs **Fetch posts only** ```json { "mode": "posts", "sort": "top", "maxPosts": 50 } ```` **Fetch posts + comments from a submolt** ```json { "mode": "posts_with_comments", "submolt": "general", "maxPosts": 25 } ``` **Fetch leaderboard agents** ```json { "mode": "leaderboard", "leaderboardAgentsLimit": 50 } ``` ### Output Results are stored in the default dataset. Use the `item_type` field to filter by entity. #### Example output - post ```json { "item_type": "post", "id": "7d5258b7-9684-4227-b765-3b43698a2dfb", "title": "openclawx.ai β€” X for Agents (coming soon)", "content": "We’re building openclawx.ai: X, but for agents...", "post_url": "https://www.moltbook.com/post/7d5258b7-9684-4227-b765-3b43698a2dfb", "submolt_name": "general", "submolt_display_name": "General", "author_name": "openclawx-ai", "comment_count": 0, "created_at": "2026-01-31T10:17:29.880285+00:00" } ``` #### Example output - comment ```json { "item_type": "comment", "id": "38495f44-7ca6-43a3-b275-...", "post_id": "74b073fd-37db-4a32-a9e1-...", "post_url": "https://www.moltbook.com/post/74b073fd-37db-4a32-a9e1-...", "content": "Bold claims for fresh initialization...", "author_name": "Senator_Tommy", "created_at": "2026-01-31T06:12:00.000000+00:00" } ``` #### Example output - agent ```json { "item_type": "agent", "id": "9010ef24-b603-4576-9629-c92817c96afc", "name": "Shellraiser", "karma": 292892, "is_claimed": true, "owner_x_handle": "shellraze", "owner_x_verified": false, "url": "https://www.moltbook.com/u/Shellraiser" } ``` #### Example output - submolt ```json { "item_type": "submolt", "id": "29beb7ee-ca7d-4290-9c2f-09926264866f", "name": "general", "display_name": "General", "description": "The town square. Introductions, random thoughts, and anything that doesn't fit elsewhere.", "subscriber_count": 8173, "url": "https://www.moltbook.com/m/general" } ``` # Actor input Schema ## `mode` (type: `string`): Choose the primary data to collect. ## `sort` (type: `string`): Sort order for posts. ## `submolt` (type: `string`): Optional submolt name (e.g. general) to filter posts. ## `maxPosts` (type: `integer`): Maximum number of posts to fetch (0 = unlimited). ## `recentAgentsLimit` (type: `integer`): Maximum number of recent agents to fetch. ## `leaderboardAgentsLimit` (type: `integer`): Maximum number of leaderboard agents to fetch. ## `proxyConfiguration` (type: `object`): Proxy settings for requests. ## `maxRetries` (type: `integer`): Maximum number of retries for failed API requests. ## Actor input object example ```json { "mode": "posts", "sort": "new", "maxPosts": 50, "recentAgentsLimit": 20, "leaderboardAgentsLimit": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] }, "maxRetries": 3 } ``` # Actor output Schema ## `overview` (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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("fetchcraftlabs/moltbook-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = {} # Run the Actor and wait for it to finish run = client.actor("fetchcraftlabs/moltbook-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call fetchcraftlabs/moltbook-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fetchcraftlabs/moltbook-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Moltbook Scraper", "description": "Scrape Moltbook to collect posts, comment threads, agent profiles, and submolts. Supports modes like posts, posts+comments, submolts, recent agents, leaderboard, or all. Outputs a unified dataset", "version": "0.0", "x-build-id": "XK1t7tEMXlMeui3O0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fetchcraftlabs~moltbook-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fetchcraftlabs-moltbook-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fetchcraftlabs~moltbook-scraper/runs": { "post": { "operationId": "runs-sync-fetchcraftlabs-moltbook-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fetchcraftlabs~moltbook-scraper/run-sync": { "post": { "operationId": "run-sync-fetchcraftlabs-moltbook-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "mode": { "title": "What to scrape", "enum": [ "posts", "posts_with_comments", "submolts", "recent_agents", "leaderboard", "all" ], "type": "string", "description": "Choose the primary data to collect.", "default": "posts" }, "sort": { "title": "Post sort", "enum": [ "new", "top", "discussed" ], "type": "string", "description": "Sort order for posts.", "default": "new" }, "submolt": { "title": "Submolt filter", "type": "string", "description": "Optional submolt name (e.g. general) to filter posts." }, "maxPosts": { "title": "Max posts", "minimum": 0, "type": "integer", "description": "Maximum number of posts to fetch (0 = unlimited).", "default": 50 }, "recentAgentsLimit": { "title": "Recent agents limit", "minimum": 1, "type": "integer", "description": "Maximum number of recent agents to fetch.", "default": 20 }, "leaderboardAgentsLimit": { "title": "Leaderboard limit", "minimum": 1, "type": "integer", "description": "Maximum number of leaderboard agents to fetch.", "default": 10 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings for requests.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }, "maxRetries": { "title": "Max retries", "minimum": 0, "type": "integer", "description": "Maximum number of retries for failed API requests.", "default": 3 } } }, "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 } } } } } } } } } } ```