We are partnering with InsForge to provide a seamless, autonomous DevOps pipeline for AI Agents using the Model Context Protocol (MCP).

We are thrilled to announce a strategic partnership with InsForge, the leading Backend-as-a-Service (BaaS) designed specifically for AI coding agents.
As next-generation AI tools like Cursor, Claude Code, and Windsurf redefine how code is written, the development bottleneck has shifted. The challenge is no longer generating code—it is configuring the scalable infrastructure it runs on. AI Agents often struggle with complex cloud setups, secure authentication flows, and database wiring.
By combining Zeabur’s "AI Agent for DevOps" capability with InsForge’s "Agent-Native Backend," we are unlocking the industry's first truly autonomous full-stack workflow.
As Zeabur continues to pioneer AI Agents for DevOps, we identified a recurring friction point: Backend Complexity.
While Zeabur solved the infrastructure problem—handling serverless deployments, networking, and containerization automatically—our users still faced hurdles when configuring traditional backend tools. Setting up Row Level Security (RLS) policies, complex JWT authentication, and PostgreSQL schemas often required human intervention, breaking the "autonomous" coding flow.
This made InsForge the obvious partner for the next generation of Zeabur.
InsForge shares the same DNA as Zeabur: it is built for the 'Agentic Era.’
Just as Zeabur agent handles your DevOps (so you don't have to), InsForge empowers the agent to architect the Backend.
Unlike traditional tools that require manual configuration, InsForge exposes backend primitives like Auth, Database, and Storage through the Model Context Protocol (MCP).
This creates a perfect symmetry for the Agentic Web:
The result? A backend your agent can actually 'understand,' manipulate, and scale without you ever touching a config file.
Here is exactly how to build an autonomous pipeline:
We list out the powerful features unlocked by the Zeabur + Insforge combination.
Zeabur eliminates the complexity of DevOps automation. While InsForge handles your backend logic and data, Zeabur allows you to deploy the connecting frontend—or even self-host instances—with a single click. No complex configuration files; just pure code running on the cloud.
InsForge provides modular building blocks—AI/Vector Databases, Authentication, File Storage, and Serverless Functions—while Zeabur provides the containerized environment to run them efficiently. This separation of concerns allows you to build extended architectures where the AI handles the logic and Zeabur handles the scale.
Zeabur’s robust Integration page is the perfect launchpad for InsForge projects. You can provision an entire stack (Frontend + InsForge connection) in under a minute and connect it to a GitHub repo for continuous integration; for instance, check out our guide on how to deploy a Lovable app to Zeabur with InsForge.
Zeabur deploys your services across global edge networks. This ensures that your application runs as close to your users—and your InsForge backend functions—as possible, reducing latency for real-time AI interactions.
Forget context switching. With InsForge handling backend complexity and Zeabur managing infrastructure, you get a unified, simplified workflow. Monitor deployments, manage environment variables, and scale your AI applications from a single, intuitive ecosystem.
Previously, you had to manually configure Supabase or write raw SQL (Already using Supabase? See why and how to migrate from Supabase to InsForge for better agentic control). Now, the workflow looks like this:
You focus on the product logic. The Agent handles the implementation. Zeabur handles the infrastructure.
Don't let backend complexity stop your flow. Follow these steps to enable the Code-to-Cloud pipeline:
Give your AI Agent the backend capabilities it has been missing.
We believe in transparent, infrastructure-based pricing. Because InsForge runs directly as a containerized service within your Zeabur project, you avoid the complex tiering and "per-seat" markups of traditional SaaS platforms.
You are charged only for the raw resources your backend consumes:
| Item | Rate |
|---|---|
| Compute Hour (Nano EC2 + EBS + Public IP) | $0.006 / hour |
| Database Size | $0.125 / GB / Month |
| Storage | $0.021 / GB / Month |
| Egress | $0.1 / GB |
| LLM AI Credits | Input / Output Token |