Blocks.ai Cross-Framework Agent Connectivity Pipeline

Blocks.ai is a global network from PubNub that makes AI agents reachable from anywhere without network infrastructure. Agents open one outbound HTTPS connection to the Blocks Network. Tasks arrive through that connection. Results flow back. No inbound ports, no static IP, no DNS records, no firewall changes. Built on PubNub's 15-year real-time infrastructure powering billions of messages for Fortune 500 companies with a 99.999% SLA. Blocks supports one-shot tasks (request/response) and bidirectional pipes (sub-second to 30-day streams). MCP integration lets agents expose tools through the network. Open-source TypeScript and Python SDKs under Apache 2.0.

BUSINESS PROBLEM

According to McKinsey's 2026 analysis of enterprise AI agent deployment, fewer than 10 percent of built agents reach production. The #1 blocker is not agent quality — it is networking. A developer builds a great agent in an afternoon, but making it reachable requires ngrok tunnels, static IPs, DNS configuration, firewall rules, and TLS certificate management. Each agent takes 2-4 hours of DevOps work to make callable. For a team of 5 engineers running 20 agents, that is 40-80 hours of networking overhead per month — $8,000 to $16,000 at $200/hour fully loaded engineer cost. And that does not account for ongoing maintenance when IPs change, tunnels expire, or certificates rotate.

WHO BENEFITS

For an AI engineer at a 10-person startup building agentic products. Situation: The agent works on your laptop but nobody else can call it. You spent 3 hours setting up ngrok and it expired after 2 hours. Payoff: Install the Blocks SDK, run one command, and your agent is globally callable in 30 seconds. No tunnels. No expiring URLs. For a platform team at a 200-person enterprise deploying agents across teams. Situation: Every team uses a different agent framework. Networking standards vary. Security review for each agent takes weeks. Payoff: Blocks provides a uniform connectivity layer with SOC 2, GDPR, zero-trust security, and one policy to review. Agents connect the same way regardless of framework. For a DevOps engineer managing agent infrastructure. Situation: The team has 15 agents running on different machines, cloud regions, and frameworks. Keeping track of their endpoints, tunnels, and certs is a full-time job. Payoff: One dashboard shows every agent's status, connection health, and task history. Agents self-register. No manual endpoint tracking.

HOW IT WORKS

Step 1. Install Blocks SDK (2 min). Run npm install @blocks/sdk or pip install blocks-sdk. Requires Node 18+ or Python 3.9+. Step 2. Register your agent (2 min). Import the SDK, call Blocks.agent({name, handler}). Your agent function receives structured tasks and returns results. Step 3. Connect to Blocks Network (5 sec). The SDK opens one outbound HTTPS connection. Your agent appears in the Blocks Network catalog immediately. No ports, no DNS, no firewall changes. Step 4. Test from any client (1 min). Use the Blocks CLI or any HTTP client: curl -X POST https://api.blocks.ai/v1/agents/{agent-id}/call -H 'Authorization: Bearer $TOKEN' -d '{"task": "process"}'. The task routes through the network to your agent. Step 5. Set up MCP tool exposure (10 min). Configure the Blocks MCP adapter to expose your agent's tools through the network. Any MCP-compatible client (Claude, Cursor) can discover and call your agent's tools without additional configuration. Step 6. Monitor and manage (ongoing). Blocks dashboard shows agent presence, task history, latency, and error rates. Configure per-task token auth, optional E2E encryption, and task-scoped artifact stores.

TOOL INTEGRATION

TOOL: Blocks.ai SDK v1.0 (Apache 2.0, launched July 8, 2026). Role: Agent connectivity SDK that opens one outbound connection to the global Blocks Network. API access: blocks.ai (SDK + CLI). Auth: Token-based. Cost: Free for development. Production pricing based on message volume. Gotcha: The free tier limits agents to 100 tasks per day and does not include bidirectional pipes. For production workloads with active monitoring or streaming, budget for the paid tier which starts at $49/month per agent. TOOL: PubNub Real-Time Backbone (built-in). Role: Global message routing, presence detection, delivery guarantees, and security. Auth: Handled by Blocks SDK. Cost: Included in Blocks pricing. Gotcha: Blocks is built on PubNub but the pricing is separate. If you already pay for PubNub directly, Blocks may be a separate line item. Evaluate both before committing to enterprise scale. TOOL: MCP Adapter (built-in, open source). Role: Exposes agent tools through Model Context Protocol so any MCP-capable AI assistant can discover and call them. Auth: Same Blocks token. Cost: Included. Gotcha: The MCP adapter currently supports tool discovery and one-shot calls only. Bidirectional streaming through MCP is not yet supported. For real-time streaming use cases, use the Blocks SDK's native pipe interface.

ROI METRICS

Metric Before (ngrok/tunnels) After (Blocks) Source Agent setup time 2-4 hours 30 seconds Blocks.ai product page Ongoing networking maint. 2-4 hours/month/agent Zero Community estimate Agent reachability Tunnel-dependent Always-on PubNub 99.999% SLA Security audit per agent Weeks One-time policy Blocks SOC 2 + GDPR

The week-1 win: pick one agent that currently runs on your laptop with an ngrok URL. Install Blocks SDK, register it, and call it from your phone or a cloud function. The 30-second setup time is the single clearest proof point. The strategic implication: agent connectivity infrastructure is becoming a commodity layer, like DNS or TLS. Teams that adopt a connectivity network early eliminate the #1 barrier to agent deployment.

CAVEATS

1. (moderate risk) Free tier limits: 100 tasks/day, no bidirectional pipes. Mitigation: Prototype on the free tier. Budget $49/month per agent for production workloads requiring pipes.
2. (minor risk) SDK maturity: TypeScript and Python SDKs are stable. More languages coming. Mitigation: Use TypeScript or Python for production. Wrap the REST API if your stack uses a different language.
3. (significant risk) Network dependency: If PubNub's global infrastructure has an outage, all connected agents become unreachable. Mitigation: PubNub has a 99.999% SLA. For critical agents, maintain a direct-fallback path (e.g., direct WebSocket) that bypasses Blocks.
4. (moderate risk) Task size limits: Maximum task payload is 32KB. Large artifacts (code outputs, images, logs) must be stored externally and passed by reference. Mitigation: Use the artifact store feature which supports S3-compatible storage references. Reference large payloads instead of embedding them.