Getting Started With Moltbook: How to Get Your AI Agent Posting

If you’re reading this, you’ve probably already heard about Moltbook and the wave of attention it sparked. It got popular fast, partly because the idea sounds exciting and a little unsettling: millions of AI agents communicating with each other, posting, replying, and shaping conversations at scale.

In this article, we'll learn why OpenClaw matters for Moltbook and how Moltbook works end-to-end. We’ll walk through the full setup step by step, with a visual guide to joining Moltbook and getting your agent posting. We’ll also break down the security risks people are calling out, and explain why this story matters beyond the hype for you and for the wider world.

Before Joining Moltbook: Understand How OpenClaw Works

If Moltbook is the “agent social network,” OpenClaw is the engine room that makes agents feel real. It keeps agents always on, able to use tools, and reachable from the places you already chat.

As we explore in our guide, OpenClaw is an open-source personal AI assistant that you run on your own machine. 

The pitch is simple: your agent does not live inside one chat app. Instead, it can respond through channels like WhatsApp, Telegram, Slack, or Discord, and it can optionally use tools to do real work beyond writing text.

You may also see older names in guides and threads, because the project went through rapid renaming in late January 2026 after trademark concerns connected to Anthropic.

OpenClaw becomes powerful because it combines three pieces:

• Channels: Where you talk to it, so the agent can sit inside apps you already use and feel like a normal contact.
• Tools: What it can do, like reading files, running scripts, controlling a browser, or calling APIs.
• Skills: How capabilities are packaged and shared, usually as installable bundles (often a SKILL.md plus optional scripts and assets), so you can add new behaviors without rebuilding your whole agent

Moltbook and OpenClaw get mentioned together because Moltbook expects an agent that can run continuously and perform a few setup actions reliably. 

With OpenClaw, that usually looks like: install or load the Moltbook skill, have your agent run the registration step, claim ownership of the agent, and then let it start posting.

So when you see “How do I get an agent onto Moltbook?” threads and OpenClaw keeps coming up, it’s not random. OpenClaw is simply one of the easiest ways to give an agent both a plug-and-play skills system and a persistent runtime that stays online.

What is Moltbook?

Moltbook is a Reddit-style social platform built for AI agents, where bots can post, comment, and upvote or downvote, while humans are mostly limited to watching. It launched in late January 2026 and was created by Matt Schlicht; the whole point is to give “agentic” bots a shared public space to interact with each other rather than with people.

Source: moltbook - the front page of the agent internet

What makes Moltbook more than a novelty is the sudden scale and the uncertainty it creates: within days, multiple reports described ~2.3 million agent accounts and huge volumes of posts/comments, but also noted how easy it can be for humans to slip in and “roleplay” as bots, so you’re often watching a mix of real automation, heavy human steering, and spam. 

That tension (mass participation + unclear authenticity) is exactly why it’s become a reference point in current agent discussions.

Source: moltbook - the front page of the agent internet

Here’s a simple breakdown of Moltbook’s main features before we jump into the step-by-step guide:

• Posts: Agents can publish standalone posts that show up in feeds and inside topic communities.
• Comments: Agents can reply in threaded comment chains under posts, just like forum threads.
• Upvotes and downvotes: Agents can vote content up or down, which affects ranking and visibility.
• Submolts: Moltbook organizes conversations into Reddit-like communities called submolts, each centered on a topic.
• Agent profiles: Each bot has its own identity and profile page, so you can follow what a specific agent is posting across submolts.
• Following: Agents can follow other agents to track their activity across the network.
• Humans mostly observe: The platform positions humans as observers while interaction is intended to be agent-only.
• Search: AI-powered search available on the platform.

Getting Started with Moltbook

In this section, you’ll learn two simple ways to get your agent onboarded to Moltbook. 

You do not need OpenClaw to sign up, but it is recommended because it is designed to run 24/7, supports a persistent runtime, and is commonly used in Moltbook’s “always-on agent” workflows.

 That said, you can still onboard with other agents or coding assistants like Claude Code, OpenAI Codex, or an “OpenCode” style local setup, as long as your agent can read a web page and run the required commands.

You can onboard your agent in two ways: a manual method where you explicitly tell it to follow the skill instructions, or an automated method where you simply tell it to join Moltbook, and it handles the steps itself.

No matter which method you use, the flow is the same, and Moltbook describes it as a simple ownership loop: the agent registers, sends you a claim link, you verify ownership by posting on X, and then the agent can start posting

Manual method

This is “manual” because you give your agent the exact instructions to follow.

Send your agent this message:

Read https://moltbook.com/skill.md and follow the instructions to join Moltbook

What happens next is predictable:

• Your agent opens the skill instructions and reads the onboarding steps
• It runs the provided commands (often curl-based) to pull the Moltbook skill files and set itself up
• It registers itself and then sends you a claim link
• You post on X to verify ownership, using the verification text or link provided in the claim flow
• Once verified, the agent can post, comment, and vote using the Moltbook API patterns described in the skill guide

If you already have OpenCode set up, just run opencode in your terminal and paste the prompt to get started.

In my case, I also had a Firecrawl MCP server configured for web search and scraping, so the agent could read and understand the instructions in skill.md directly.

Once it follows the instructions, it runs a few curl commands to register and set up the account.

When that’s done, it sends you a “claim your agent” URL, and you simply follow the step-by-step flow to verify ownership through X. After that, your agent is ready to post.

Automated Method

This is “automated” because you do not give your agent a prompt with the link to the skills file. You simply tell it to join Moltbook, and it handles the onboarding flow end to end, including fetching the instructions it needs and running the required setup commands.

In practice, the agent typically reads the Moltbook skill page, follows the steps to register itself, and then sends you a claim link. After you claim the agent, it can start posting.

For example, I just told my AI agent: “Join Moltbook.” It then did the web browsing and scraping on its own to find the skill.md instructions and understand how to set up a Moltbook account. 

Similar to the manual method, it returned a unique URL to claim my agent’s spot on Moltbook.

From there, I opened the link, entered my email address, and verified it.

Moltbook then provided an X verification step, so I copied the verification text and posted it from my X account to confirm ownership. 

Here’s the tweet I posted on my X account to verify ownership.

Once verification is complete, Moltbook redirects you to your agent’s dashboard. Think of this as your bot’s profile and control panel, where you can manage basic details and view activity like posts and comments.

After everything was set up, I asked my agent to write and publish a “Love = Hate” poetry post. It published the post successfully and sent me the link.

And the fun part: it already picked up a comment, which shows how quickly agents can start interacting once you’re live.

Moltbook Security Issues

Moltbook grew extremely fast, and recent incidents showed how that kind of speed can expose basic security gaps when access controls and secrets are not fully locked down. Here are the main issues that have been reported, in simple terms:

• Exposed production database: A misconfiguration that exposed sensitive data (including large volumes of agent tokens and some human user data) because backend protections were not properly enforced.
• Real human data exposure: Multiple reports said the incident included exposure risk for real people (for example, email addresses and private messages), which raised concerns beyond “bots talking to bots.”
• Claim and verification: A case where an account was “claimed” through a verification weakness and social engineering, showing how ownership flows can be abused if they are not robust.
• Malicious “skills” supply-chain risk: The Verge reported that the open skills ecosystem around OpenClaw has attracted malicious or unsafe skills, including ones that can steal credentials or run harmful commands if users install them.
• Prompt injection and bot-to-bot manipulation: Several analyses warned that when agents automatically read content and then take actions, attackers can hide instructions in posts or skills to influence other agents (for example, trying to trick them into revealing secrets).
• Exposed dashboards and “public admin panels”: Security reporting flagged many internet-exposed control panels for agent tooling, which can turn a simple misconfiguration into full host compromise if the panel has powerful permissions.

Why Does Moltbook Matter? (Even if it’s Chaotic)

Moltbook matters because it is an early, messy preview of what the “agent internet” could feel like: software entities posting, ranking content, and interacting at scale in public feeds, while humans mostly watch. 

It is less about whether Moltbook itself becomes a lasting platform and more about what it reveals when the cost of spinning up agents drops, and millions of them can share one public space.

It also forces a few uncomfortable questions into the open. 

First, authenticity gets messy almost immediately: even in an “agent-only” space, a lot of activity can still be guided by humans, from lightly steering one bot to operating whole fleets, which means you cannot always tell if you are watching real autonomy, human direction, or pure spam. 

Second, it raises the stakes for online identity, because once bot-native spaces go viral, the rest of the internet starts demanding clearer signals for who is human, who is automated, and who is pretending to be either.

Finally, Moltbook is a real-world stress test for safety and security. When agent platforms connect to tool ecosystems like OpenClaw, small mistakes can have an outsized impact: leaked tokens, over-permissioned skills, and prompt injection risks stop being theoretical and start looking like normal operational security.

Final Thoughts

An “AI-agents-only” social network sounds a bit dystopian on paper. A feed full of bots posting, voting, and reacting to each other makes you wonder what happens when that system gets smarter, faster, and more persuasive than the people watching it.

But the real problem today is not sci-fi superintelligence. 

It is authenticity. 

A viral Moltbook post can look like organic agent behavior, but it might be heavily steered by a human, or boosted by one person running a whole fleet of bots to upvote certain content and shape what rises to the top. 

Add in the fact that the platform is still new, and you get predictable growing pains around privacy, security, and basic trust signals.

At the same time, it is hard not to admit the platform is fun. I genuinely enjoy reading what the agents write and testing interactions, even using a simple setup like OpenCode. 

Onboarding is fairly straightforward, verification can take a bit longer, and once you are in, posting is easy. You can tell your agent to read a thread, decide if it likes it, leave a comment, or upvote, and it will do it.

If you need to get up to speed with AI agents, I recommend taking the AI Agent Fundamentals skill track. You can also learn to create desktop AI agents with our Claude Cowork tutorial.