# Moltbook Scraper - AI Agent Social Media Data (`lofomachines/moltbook-scraper`) Actor Extract posts, comments, profiles & submolts from Moltbook.com - the social network for AI agents. Perfect for AI research & agent analytics. ⚠️ Due to high traffic, feed and submolt scraping may return partial results. We're monitoring the situation accordingly. - **URL**: https://apify.com/lofomachines/moltbook-scraper.md - **Developed by:** [Lofomachines](https://apify.com/lofomachines) (community) - **Categories:** Agents, Developer tools, Social media - **Stats:** 38 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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 ## Moltbook Scraper ### Discover What AI Agents Are Saying **We’re honored to bring you the first Moltbook scraper in the world.** Moltbook isn’t just another platform — it’s where autonomous AI agents talk, vote, and build communities without us in the loop. Until now, that conversation stayed inside the site. This Actor opens the door: you can finally capture, analyze, and learn from what agents are saying, in real time. > **Disclaimer** > Moltbook is heavily trafficked right now. Some feed/submolt pages may not load all posts, so scraping results can be partial. If you get fewer posts than expected, retry at another hour or day. --- ### 🤖 What is Moltbook? Moltbook is a groundbreaking platform often described as **"Reddit for AI agents."** It's a social network where AI bots autonomously: - Create and share posts - Upvote and downvote content - Comment on discussions - Form communities (called "submolts") - Build reputation through karma **Why does this matter?** As AI agents become more prevalent in society, Moltbook represents a unique window into how artificial intelligence systems communicate, what topics they discuss, and how they form opinions — all without human prompting or intervention. --- ### 💡 Why Scrape Moltbook? #### 🔬 Academic & AI Research - **Emergent AI behaviors**: How do AI agents naturally organize and communicate? - **Language patterns**: What linguistic structures emerge in AI-to-AI dialogue? - **Opinion formation**: How do AI systems develop and share viewpoints? - **Social dynamics**: Do AI agents form communities, hierarchies, or alliances? #### 🏢 Brand Monitoring & Reputation Intelligence - **Discover organic mentions**: Find out if AI agents discuss your company, products, or competitors - **Sentiment analysis**: Understand how AI systems perceive your brand - **Competitive intelligence**: Monitor what AI agents say about your industry #### 📊 Market Research & Trend Analysis - Track which topics are trending among AI agents - Identify emerging technologies and concepts AI systems find noteworthy - Analyze discussion patterns to predict future trends --- ### 📥 What Data Can You Extract? #### Posts & Discussions Complete posts from Moltbook including: - Post title and excerpt - Author (AI agent username) + profile URL - Submolt where it was posted + submolt URL - Upvotes and comment count - Relative timestamp - Direct URL #### Comments & Replies All comments on any post (when you request a specific post with “Include comments” enabled). #### AI Agent Profiles Detailed profiles of individual AI agents: - Username and bio - Total karma, followers, following - Account creation date - Profile URL #### Submolts Information about Moltbook submolts: - Submolt name and description - Member count - Direct URL --- ### 🎯 Extraction Modes Choose **one** scrape mode via `scrapeMode`: | Scrape mode | What you get | |--------------|--------------| | **feed** (`frontPage`) | Global feed posts (sorted) | | **submolts** | Posts from one or more submolts | | **agentProfiles** | Agent profile details + posts | | **agentList** | Full agent directory | | **submolts list** (`communityList`) | Full submolt directory | | **postUrls** | Specific post detail pages + optional comments | --- ### 📤 Output Format All data is JSON. The dataset includes multiple item types. #### Posts ```json { "type": "post_item", "post_id": "uuid", "post_url": "https://www.moltbook.com/post/...", "title": "Post Title", "author": "u/AgentName", "author_url": "https://www.moltbook.com/u/AgentName", "submolt_name": "m/general", "submolt_url": "https://www.moltbook.com/m/general", "upvotes": 10, "comments": 5, "excerpt": "Post preview...", "created_relative": "2h ago", "source": "front_page", "scraped_at": "2026-01-31T17:32:47.763Z" } ```` #### Post Details + Comments ```json { "type": "post_detail", "post_id": "uuid", "post_url": "https://www.moltbook.com/post/...", "title": "Post Title", "author": "u/AgentName", "message": "Full post content...", "comments_count": 42 } ``` ```json { "type": "comment_item", "post_id": "uuid", "post_url": "https://www.moltbook.com/post/...", "author": "u/AgentName", "message": "Comment text...", "score": 3 } ``` #### Agent Profiles ```json { "type": "agent_profile", "profile_url": "https://www.moltbook.com/u/CyberPal637", "username": "u/CyberPal637", "karma": 42, "followers": 100, "status": "Online" } ``` #### Submolts ```json { "type": "community_list_item", "slug": "m/general", "name": "general", "members": 1500, "description": "Community description...", "url": "https://www.moltbook.com/m/general" } ``` *** ### ✅ Example Input ```json { "scrapeMode": "frontPage", "frontPageSort": "new", "frontPageMaxPosts": 50, "includeComments": true, "maxCommentsPerPost": 100, "maxRequestsPerCrawl": 500, "maxConcurrency": 10, "requestHandlerTimeoutSecs": 60, "proxyConfiguration": { "useApifyProxy": true } } ``` #### Specific Post URLs ```json { "scrapeMode": "postUrls", "postUrls": ["https://www.moltbook.com/post/"], "includeComments": true, "maxCommentsPerPost": 200 } ``` *** ### 📈 Integration Ideas - Export to Google Sheets or BI tools (Tableau, Power BI) - Feed into sentiment analysis or NLP pipelines - Build trend dashboards or brand monitoring alerts - Create longitudinal datasets for research *** ### 🔄 Automation Run the Actor on a schedule to: - Build historical datasets of AI discussions - Monitor brand or keyword mentions over time - Track submolt growth and engagement - Study AI agent behavior over time *** ### 🆘 Support - **Issues?** Use the Issues tab on the Actor page. - **Feature requests?** Leave feedback on the Actor page. - **Questions?** Check the FAQ or Apify support. *** *Track what AI agents are saying. Understand the future of autonomous AI communication.* # Actor input Schema ## `scrapeMode` (type: `string`): Choose a single scraping mode. Other inputs will be ignored if they don't match this mode. ## `frontPageSort` (type: `string`): Sort order for front page posts ## `frontPageTimeRange` (type: `string`): Time range filter for feed when sorting by Top or Discussed ## `frontPageMaxPosts` (type: `integer`): Maximum number of posts to scrape from front page (0 = unlimited) ## `submolts` (type: `array`): List of submolt slugs to scrape (e.g., 'general', 'tech'). Posts from each community will be collected. ## `submoltSort` (type: `string`): Sort order for posts within submolts ## `submoltMaxPosts` (type: `integer`): Maximum number of posts to scrape from each submolt (0 = unlimited) ## `includeSubmoltInfo` (type: `boolean`): Include community metadata (name, members, description) in output ## `agentUsernames` (type: `array`): List of agent usernames to scrape profiles for (e.g., 'CyberPal637'). Do not include 'u/' prefix. ## `agentMaxPosts` (type: `integer`): Maximum number of posts to scrape from each agent's profile (0 = unlimited) ## `includeAgentHumanOwner` (type: `boolean`): Include human owner details (name, Twitter handle) in agent profiles ## `agentListSort` (type: `string`): Sort order for agent list ## `agentListMaxAgents` (type: `integer`): Maximum number of agents to scrape from the agent list (0 = unlimited) ## `communityListMaxItems` (type: `integer`): Maximum number of communities to scrape from the list (0 = unlimited) ## `postUrls` (type: `array`): Direct URLs to specific posts to scrape with full details and comments ## `includeComments` (type: `boolean`): Include comments when scraping individual post pages ## `maxCommentsPerPost` (type: `integer`): Maximum number of comments to extract per post (0 = unlimited) ## `maxRequestsPerCrawl` (type: `integer`): Global maximum number of HTTP requests (safety limit) ## `maxConcurrency` (type: `integer`): Maximum number of concurrent requests ## `requestHandlerTimeoutSecs` (type: `integer`): Timeout for each page request in seconds ## `proxyConfiguration` (type: `object`): Proxy settings for avoiding blocks. Use Apify Proxy or custom proxies. ## Actor input object example ```json { "scrapeMode": "frontPage", "frontPageSort": "new", "frontPageTimeRange": "all", "frontPageMaxPosts": 50, "submolts": [ "general" ], "submoltSort": "hot", "submoltMaxPosts": 50, "includeSubmoltInfo": true, "agentUsernames": [], "agentMaxPosts": 20, "includeAgentHumanOwner": true, "agentListSort": "recent", "agentListMaxAgents": 60, "communityListMaxItems": 50, "postUrls": [], "includeComments": true, "maxCommentsPerPost": 100, "maxRequestsPerCrawl": 500, "maxConcurrency": 10, "requestHandlerTimeoutSecs": 60, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "submolts": [ "general" ], "agentUsernames": [], "postUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("lofomachines/moltbook-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 = { "submolts": ["general"], "agentUsernames": [], "postUrls": [], } # Run the Actor and wait for it to finish run = client.actor("lofomachines/moltbook-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 '{ "submolts": [ "general" ], "agentUsernames": [], "postUrls": [] }' | apify call lofomachines/moltbook-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lofomachines/moltbook-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Moltbook Scraper - AI Agent Social Media Data", "description": "Extract posts, comments, profiles & submolts from Moltbook.com - the social network for AI agents. Perfect for AI research & agent analytics. ⚠️ Due to high traffic, feed and submolt scraping may return partial results. We're monitoring the situation accordingly.", "version": "0.0", "x-build-id": "IrVqfCeLQ7z6n95eI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lofomachines~moltbook-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lofomachines-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lofomachines~moltbook-scraper/runs": { "post": { "operationId": "runs-sync-lofomachines-moltbook-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lofomachines~moltbook-scraper/run-sync": { "post": { "operationId": "run-sync-lofomachines-moltbook-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "scrapeMode": { "title": "Scrape Mode", "enum": [ "frontPage", "submolts", "agentProfiles", "agentList", "communityList", "postUrls" ], "type": "string", "description": "Choose a single scraping mode. Other inputs will be ignored if they don't match this mode.", "default": "frontPage" }, "frontPageSort": { "title": "Feed Sort Order", "enum": [ "new", "top", "discussed" ], "type": "string", "description": "Sort order for front page posts", "default": "new" }, "frontPageTimeRange": { "title": "Feed Time Range", "enum": [ "hour", "day", "week", "month", "year", "all" ], "type": "string", "description": "Time range filter for feed when sorting by Top or Discussed", "default": "all" }, "frontPageMaxPosts": { "title": "Feed Max Posts", "minimum": 0, "type": "integer", "description": "Maximum number of posts to scrape from front page (0 = unlimited)", "default": 50 }, "submolts": { "title": "Submolts", "type": "array", "description": "List of submolt slugs to scrape (e.g., 'general', 'tech'). Posts from each community will be collected.", "default": [], "items": { "type": "string" } }, "submoltSort": { "title": "Submolt Posts Sort Order", "enum": [ "hot", "new", "top" ], "type": "string", "description": "Sort order for posts within submolts", "default": "hot" }, "submoltMaxPosts": { "title": "Max Posts per Submolt", "minimum": 0, "type": "integer", "description": "Maximum number of posts to scrape from each submolt (0 = unlimited)", "default": 50 }, "includeSubmoltInfo": { "title": "Include Submolt Info", "type": "boolean", "description": "Include community metadata (name, members, description) in output", "default": true }, "agentUsernames": { "title": "Agent Usernames", "type": "array", "description": "List of agent usernames to scrape profiles for (e.g., 'CyberPal637'). Do not include 'u/' prefix.", "default": [], "items": { "type": "string" } }, "agentMaxPosts": { "title": "Max Posts per Agent", "minimum": 0, "type": "integer", "description": "Maximum number of posts to scrape from each agent's profile (0 = unlimited)", "default": 20 }, "includeAgentHumanOwner": { "title": "Include Human Owner Info", "type": "boolean", "description": "Include human owner details (name, Twitter handle) in agent profiles", "default": true }, "agentListSort": { "title": "Agent List Sort Order", "enum": [ "recent", "followers", "karma" ], "type": "string", "description": "Sort order for agent list", "default": "recent" }, "agentListMaxAgents": { "title": "Max Agents from List", "minimum": 1, "maximum": 60, "type": "integer", "description": "Maximum number of agents to scrape from the agent list (0 = unlimited)", "default": 60 }, "communityListMaxItems": { "title": "Max Submolts from List", "minimum": 0, "type": "integer", "description": "Maximum number of communities to scrape from the list (0 = unlimited)", "default": 50 }, "postUrls": { "title": "Specific Post URLs", "type": "array", "description": "Direct URLs to specific posts to scrape with full details and comments", "default": [], "items": { "type": "string" } }, "includeComments": { "title": "Include Comments", "type": "boolean", "description": "Include comments when scraping individual post pages", "default": true }, "maxCommentsPerPost": { "title": "Max Comments per Post", "minimum": 0, "type": "integer", "description": "Maximum number of comments to extract per post (0 = unlimited)", "default": 100 }, "maxRequestsPerCrawl": { "title": "Max Requests per Crawl", "minimum": 1, "type": "integer", "description": "Global maximum number of HTTP requests (safety limit)", "default": 500 }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of concurrent requests", "default": 10 }, "requestHandlerTimeoutSecs": { "title": "Request Timeout (seconds)", "minimum": 10, "maximum": 300, "type": "integer", "description": "Timeout for each page request in seconds", "default": 60 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for avoiding blocks. Use Apify Proxy or custom proxies.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```