a2a cloud
a2a cloud vs Vertex AI

a2a cloud vs Vertex AI Agent Builder for deploying AI agents

Vertex AI Agent Builder is a capable way to build and run agents — if your world is Google Cloud. It's a set of GCP services you compose, with IAM and billing to match. a2a cloud is the framework-agnostic alternative: one deploy for the whole agent app, no cloud lock-in, with scoped grants and signed proof.

lock-inassemblydatabaseinteropauthorityproof
honest take

Where Vertex AI Agent Builder is genuinely strong — and where a2a cloud is different.

Vertex AI Agent Builder is good at

Deep Google Cloud integration

If you're already all-in on GCP, Vertex AI Agent Builder gives you tight integration with Google's models, data stores, and IAM, plus native A2A protocol support. For teams standardized on Google Cloud, that cohesion is genuinely valuable.

a2a cloud adds

One deploy, any framework, no lock-in

a2a cloud deploys Python or TypeScript agents on any framework — with a managed Postgres database, an MCP server, an OpenAPI gateway, a frontend, and auth from a single command. Authority is Ed25519-signed scoped grants instead of broad IAM roles, and every run ships an end-user-verifiable signed receipt. A2A-native and MCP-native, without living inside one cloud.

side-by-side

a2a cloud vs Vertex AI Agent Builder, dimension by dimension.

A fair comparison. Both columns are accurate as we understand the products today — the difference is what the runtime owns by default.

dimension
Vertex AI Agent Builder
a2a cloud
lock-in
Deeply tied to Google Cloud — Vertex, IAM, and GCP billing. Agents live inside the GCP estate.
Framework- and cloud-agnostic. Deploy Python or TypeScript agents on any framework.
assembly
Compose Agent Engine, Vertex models, data stores, and IAM to stand up a production agent.
One `a2a deploy`: runtime, Postgres, MCP server, API, frontend, and auth together.
database
Wire your own Cloud SQL / AlloyDB / vector store per agent.
A managed Postgres database per agent, provisioned automatically.
interop
Google's A2A protocol native; MCP support maturing across the stack.
A2A-protocol native and MCP-native — every agent tool is also an MCP tool, callable from any client.
authority
GCP IAM roles and service accounts — powerful, but broad and cloud-scoped.
Ed25519-signed scoped grants: audience, TTL, file and tool scope, per run.
proof
Cloud Logging / Cloud Audit Logs — mutable platform logs.
An Ed25519-signed, replayable receipt for every run, verifiable by the end user.
how to choose

Pick the tool that matches the job.

Reach for Vertex AI Agent Builder when

  • You're standardized on Google Cloud and want tight GCP integration.
  • Google's models and data stores are central to your stack.
  • You're comfortable composing Vertex services and IAM yourself.

Reach for a2a cloud when

  • You want framework-agnostic hosting with no cloud lock-in.
  • You need the full agent app — DB, MCP, API, frontend — in one deploy.
  • You need scoped grants and end-user-verifiable receipts, not just IAM and platform logs.
don't trust the agent

Trust the receipt.

a2a cloud deploys any agent — LangGraph, OpenAI Agents SDK, CrewAI, or custom — and ships it with a managed Postgres database, an MCP server, an API, a frontend, and an Ed25519-signed receipt for every run. Scoped grants, no ambient production access. One deploy, the whole agent app, with proof.