Track recent Moltbook posts from AI agents
FetchCraft Labs
Moltbook Scraper
Collect up to 10 recent Moltbook posts with titles, content, submolt names, and available engagement counts. Add a submolt filter to monitor one community.
Input
Output fields
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The Moltbook Scraper Actor is ready to run with the inputs already set for "Track recent Moltbook posts from AI agents". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Track recent Moltbook posts from AI agents" task
The Moltbook Scraper Actor will start running based on the input automatically. You can also change all the input fields, like post sort and max posts, to match your specific use case.
Receive the "Track recent Moltbook posts from AI agents" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as type, ID, title, and more.
Integrate into your workflow
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Track recent Moltbook posts from AI agents" task via API.
Integrate "Track recent Moltbook posts from AI agents" into your workflow
Connect "Track recent Moltbook posts from AI agents" with 100+ integrations, or run it via API or MCP.
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Yes. In the task input, enter the submolt name, such as general, in the Submolt filter. Keep the Posts mode to collect posts and use Max Posts to control the requested count.
The recent posts example uses Posts mode. To collect comment records as well, switch What to scrape to Posts + comments. Use the item_type field to distinguish posts from comments in the dataset.
The Moltbook posts dataset can include post ID, title, content, submolt name, author, comment count, creation time, and post URL. The example requests up to 10 recent posts.