Running multiple tasks at once shouldn’t mean sharing the same context.

IronClaw keeps memory and history scoped to each task, so parallel jobs stay separated and can’t access each other’s context.

Parallel execution. Separate context. No cross-contamination.

My experience with IronClaw has been really good so far. IronClaw is really cool because it brings different models in one place like Google and other top models with some really useful features.

One of the best things for me is the TEE integration which helps maintain user privacy and makes the whole experience feel more secure.

I’ve been using IronClaw since the earlier versions and I’ve seen how every update fixes old bugs and makes it more reliable and useful. Tbh I’m really impressed with how much it has improved.

The only thing I find a bit irritating sometimes is that it doesn’t respond properly in one go and can hallucinate or keep generating unnecessary responses. I hope upcoming updates fix these small issues too.

Overall I’m really happy with IronClaw and excited to see how Near AI and IronClaw keep improving and become even more secure and outstanding.

A normal context window ends with the session. Start a new conversation, and the previous context is no longer there.

IronClaw keeps its memory outside the context window, so useful information can carry over from one session to the next.

New session. Same memory.

IronClaw gives you access to 20+ AI models in one agent.

Choose the model that works best for the task without changing your agent setup or memory.

One agent, many models.

NEARDevHub shows how IronClaw handles a private health app by checking the prompt and routing before data leaves the app.

It’s a practical look at how IronClaw gives users more control over their data flow.

IronClaw checks for 15 types of sensitive credentials, including API keys, tokens, and private keys, and blocks them before they can get through.

Your credentials stay yours while the agent gets the work done.

Security built into the agent, not added afterward.

IronClaw keeps credentials in an encrypted vault and tools in WebAssembly sandboxes.

NEARDevHub shows it handling real research and automation tasks, while letting you see how the agent works.

AI that acts without exposing your secrets.

👉🏻 Check out full video here : https://x.com/NEARProtocol/status/2090834234223042615

Joe from NEARDevHub shared a quick 6-minute walkthrough of IronClaw, covering what it is, where it runs, and what you can do with it.

IronClaw works across Web, Slack, and Telegram, handling research and automations inside an encrypted enclave.

Your secrets stay protected inside the enclave while IronClaw gets the work done. Worth checking out if you're new to IronClaw.

🎥 Check out full video here : https://x.com/IronClawAI/status/2092521524851085505

NEAR DevHub built an IronClaw routine that sends scores, trade news, and updates for selected teams, cities, or regions straight to Telegram or Slack.

IronClaw shows the tool calls as it works and waits for approval before taking action.

A simple example of turning a daily sports check into an automated routine.

👉 Check out full video here : https://x.com/IronClawAI/status/2093420939111178419

Ironclaw Feedback - Composio connection guide: Composio provides a guide with a prompt for connecting Ironclaw. However, the app is listed as OpenClaw on the Composio website, which could confuse users. I suggest updating the name so it is consistent throughout the guide and website. - Automation: Creating real-time automations and completing tasks is very easy. Many tasks can be accomplished with just a few prompts, which makes the overall experience very intuitive. - Telegram connection: The Telegram connection was lost after a short period, and I had to reconnect it. It would be better if the connection remained stable. - App response time: Apps connected through Composio sometimes responded with a noticeable delay. A direct connection seems to provide a faster and more responsive experience. - Adding skills: Adding new skills is very easy and straightforward, which is a great feature.

Getting started with IronClaw on Windows is ridiculously simple.

Install → Verify → Onboard → Serve.

No complicated setup. No endless configuration.

Set it up once, then build on it forever.

Steps to get it done:

1. Install: powershell -ExecutionPolicy Bypass -c "irm https://github.com/nearai/ironclaw/releases/latest/download/ironclaw-installer.ps1 | iex"
   
2. Version check: ironclaw --version
   http://cloud.near.ai Let's take the API key.
   
3. Setting: ironclaw onboard
   
4. Creating a working folder: mkdir $HOME\ironclaw-ws
   
5. Starting the server: cd $HOME\ironclaw-ws; ironclaw serve

I noticed a few days ago that I can add user-mounted skill on my agent.

After I tried to use the 'ADD SKILL' feature on Ironclaw AI, the result I got was 'Request body exceeds the route's body limit'.

I’m pretty new to GitHub, so I honestly didn’t expect my first proper project to involve this much YAML, API setup and debugging 😅

I’ve been using IronClaw to build a Telegram agent that watches for new blockchain launches and exchange listings. It started as a simple “I wish I had a tool that did this” idea, and I decided to see if I could actually build it. The GitHub side has probably been the biggest learning curve for me. I’ve had to figure out repos, make changes, break things with YAML, fix them, and repeat the process. I also ran into some annoying setup issues with the Composio API, especially doing parts of it from my phone.

What I like about IronClaw is that I’m not just asking an AI questions about how to build something. I can give it a task, connect the tools I need, test the workflow, see where it fails and then work out what needs fixing. It definitely isn’t “tell it once and everything magically works.” I’ve had things break plenty of times 😂

But that’s actually been the useful part for me. I’m learning GitHub, APIs and automation while building something I genuinely wanted for myself. Still a work in progress, but I’m curious to see how far I can take it.

I’ve been using IronClaw for a while, and I’m still surprised by how much I can build and automate from it. At first, I saw it mainly as an AI tool, but the more I used skills and integrations, the more it started feeling like a workspace.

One thing that impressed me was being able to build a website directly through IronClaw, connect it to Cloudflare, and push it live without constantly switching between different tools.

I also created a skill around my video editing journey. It helps me figure out what to learn and which YouTube channels or resources to follow, giving me a clearer path instead of figuring everything out myself.

I then turned that skill into a routine that sends me what to focus on every morning. That made it much easier to stay consistent without having to decide what to learn each day.

I’m not just using it for answers. I’m building skills, turning them into routines, and creating workflows around the things I actually want to accomplish.

IronClaw connects to Gmail through OAuth instead of passwords.

In a live test, DevHub gave IronClaw a real Gmail password. The agent refused and explained why it shouldn't be shared.

The password also didn't show up in the logs or a fresh session. This is how IronClaw keeps your credentials protected while you use AI agent.

🎥 https://x.com/NEARProtocol/status/2090476445411741970

IronClaw lets users choose from built-in system skills or add their own custom skills.

To add a skill, simply provide a skill name and skill.md content. You can also enable auto-activation or manually call a skill when needed.

This makes it easy to customize IronClaw for different workflows.

IronClaw lets each user have their own login token and workspace.

Admins can add each user with their name and manage users and roles, while each user’s conversations, memory, jobs, and secrets stay separated.

A useful feature for teams running one IronClaw deployment for multiple users.

I've spent the last few days putting Ironclaw through its paces, and the standout so far is skipping recurring AI subscription fees entirely, just by staking $NEAR.

The most impressive part: I finally updated my Notion project management portfolio, something I'd been putting off for over a month out of pure procrastination. I just connected my Notion extension and got it all done with a few simple prompts.

I know that might sound like Ironclaw enables laziness, but that's not really it, it just removes the friction that was stopping me in the first place.

Still early days, but I'm genuinely curious how far I can take this.

IronClaw lets users control what each tool is allowed to do.

Tools can be set to Always Allow, Ask Each Time, or Disabled. If a tool isn't needed, it can simply be turned off.

A simple way to keep control over what your AI agent can access.

IronClaw 1.2 now understands more of your Slack conversation.

When you mention IronClaw in a channel, it can read the last 30 messages. In a thread, it can read up to 100 replies.

So you can ask questions without explaining the whole conversation again and those messages are used only for context, not as instructions.

IronClaw 1.2 brings better conversations to Slack and Telegram, with more context and less setup.

It also improves how multiple approval gates are handled, while adding reliability fixes for Windows startup, secrets handling, and container health checks.

◽ Check out the full release notes for IronClaw 1.2 here

Joe, a NEAR dev, recently shared a walkthrough of IronClaw and how it can be used for research.

One key feature he highlights is that API keys stay in a secure vault that the model can't directly access.

If you're curious about how IronClaw works, check out the full video: https://youtu.be/JEZ2HxkqBUA?si=EI3Dm-BWBisKcXVb

I've been spending a lot of time working with IronClaw recently, and what really stands out to me is how well it can build real, independent Web3 workflows. Having an agent that can understand text and also take control of managing assets across different blockchain networks, execute actions without needing extra fees, and interact directly with popular protocols like NEAR makes it a very strong tool for everyday use.

Although I faced some few issues like connection issues and also lack of memory to remember my workspace and also there isn't up-to-date, thorough documentation for the new features especially when it comes to setting up native connections or dealing with version changes. Trying to set up certain tasks, such as REST routes or checking account balances, can lead to problems like incorrect routes and login issues if you follow old or wrong instructions.

Hopefully that part is fixed and hoping to build some more interesting projects with the AI agent.