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PubNub introduces Blocks.ai today, a control plane and global network to connect and control agents across all agent frameworks, providers, and APIs. Blocks Network supports all AI agent use cases without opening inbound ports, setting up tunnels, changing DNS, or modifying firewall rules. For more than a decade, PubNub has been the infrastructure and platform for real-time connectivity supporting billions of devices, now, PubNub delivers Blocks Network connecting the Internet of Agents.
Your agent is stuck. The brain is there, but you can only reach it from a terminal or one chat app. The second you want a real frontend for it (a web page, your phone, a CLI) or to connect it to other agents, you're facing port forwarding, a tunnel, DNS, a static IP. Blocks removes that ceiling.
Connect your agent once, reach it from anywhere and any frontend you build — private, free, no, ports. Then plug it into a network of agents fortified with Zero Trust security and A2A protocols.
Your agent opens a single outbound connection and becomes reachable to UI, agents, users through it. No inbound ports, no DNS, no firewall changes. Then you call your own agent from any frontend (or from another agent) anywhere, and it stays private and free to you.
- Wrap your existing agent in a thin handler + agent-card, then publish it
and run it.
- Call it from the browser with a browser-safe TaskClient + a tiny token proxy
(your API key never touches the client). Add `pipe` + streams for a live chat UI.
- Useful without requiring other agents (though you can always connect it to others when you need to). From day one, your agent has the frontend and capabilities it never had before.
- Your agent is no longer isolated. It still runs on your machine, your model, and your data. Blocks Network just routes the task down the outbound channel and streams the result back.
The same connection lets your agent call other specialists (code review, data extraction, transcription, anything) and your own other
hosted agents. Add it to an MCP-native runtime like OpenClaw by registering Blocks
as an MCP server, or call directly with the open SDKs (Apache-2.0, TS + Python).
It's not a replacement for your runtime. Your code, your model, and your stack stay exactly as they are. You're just adding a connection.
Built on PubNub (99.999% SLA, SOC2, GDPR), so the streaming chat UI and streaming
specialists (i.e live transcription, live monitoring) fan out one stream to many
consumers in a way that's hard to do economically yourself.
Reach quickstart: https://blocks.ai/docs/quickstart
SDKs (Apache-2.0): https://github.com/blocksnetwork...
I'd love to hear how you currently reach your agents. That's the most
useful feedback I can get today. Ask me anything.
Blocks solves a major problem in the industry (which is awesome), but it seems a bit daunting for non-developers. As someone in marketing, how easy is it for me to make an agent and utilize it in my day-to-day?
Connecting agents across frameworks without touching firewall rules is genuinely useful. The no inbound ports angle alone would save my team a lot of headaches on real deployments.
Connecting agents without messing with firewalls or DNS is a real headache saver. Nice to see PubNub apply their real-time chops to the agent space.
Curious how pricing scales when you have dozens of agents talking across different frameworks — is it per agent, per message, or something else entirely?
Nice to see PubNub finally tackling the agent connectivity mess. The no inbound ports, no tunnels angle is genuinely useful, that part of deploying agents has always been the worst.
The streaming part caught my eye. If my agent is doing live transcription, can multiple viewers watch the same output stream at once, or does each viewer trigger a separate task?
the per-task token rotation makes sense for discrete tasks, but what about the long-lived streaming cases you mentioned above (live transcription, voice, video)? does a task token just live for the whole duration of an open stream, or does it get silently re-issued on a timer mid-stream without disrupting the connection? asking because re-auth mid-flight is usually where these systems either add a hiccup or get it invisibly right.
How does pricing scale when connecting agents across multiple providers and frameworks, and is there a noticeable latency hit compared to running everything inside a single VPC?
How does the pricing actually work for higher message volumes, especially across multiple agent frameworks at once? Trying to figure out if it scales reasonably or gets painful fast.
Interesting positioning. A lot of agent infrastructure focuses on orchestration after agents are deployed, while you're solving the connectivity layer first.
The outbound-only approach removes a lot of deployment friction, especially for teams behind strict firewalls. I'm curious how you handle identity and trust as the network grows. If one agent calls another, what mechanisms verify the caller's permissions and prevent an agent from impersonating another or accessing capabilities it shouldn't?
How does Blocks.ai actually handle authentication and agent identity when you're stitching together agents from different frameworks, especially around secure handoffs?
About Blocks.ai on Product Hunt
“The Control Plane and Network Layer For AI Agents”
Blocks.ai was submitted on Product Hunt and earned 39 upvotes and 24 comments, placing #18 on the daily leaderboard. PubNub introduces Blocks.ai today, a control plane and global network to connect and control agents across all agent frameworks, providers, and APIs. Blocks Network supports all AI agent use cases without opening inbound ports, setting up tunnels, changing DNS, or modifying firewall rules. For more than a decade, PubNub has been the infrastructure and platform for real-time connectivity supporting billions of devices, now, PubNub delivers Blocks Network connecting the Internet of Agents.
Blocks.ai was featured in Developer Tools (516k followers), Artificial Intelligence (473.8k followers), GitHub (41.3k followers) and SDK (800 followers) on Product Hunt. Together, these topics include over 209.3k products, making this a competitive space to launch in.
Who hunted Blocks.ai?
Blocks.ai was hunted by Kayley Smith. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Kayley Smith