An AI agent builder that ships production agents, not demos.
Most AI agent builders are drag-and-drop canvases. You wire nodes until something demos well, then discover it can't reach production — no database, no real access model, no proof of what it did, and no way out of the visual editor. a2a cloud's Agent Studio works differently. You describe the agent in one prompt, and a crew of specialist agents builds it, reviews it for flaws, fixes them, and deploys it as a real governed service you own.
one prompt · builder + reviewer + editor · real code you own
Drag-and-drop builders demo well and ship nothing.
The typical AI agent builder is a visual editor: drag nodes, connect arrows, and watch a happy-path demo run. The trouble starts after the demo. The flow is trapped inside the editor with no code to own, it talks to a model but has no database or service other systems can call, its access is a long-lived API key with standing reach, and there's no record of what any run actually did. What looked like a finished agent is a screenshot away from production and a long way from it.
Describe it once. A crew builds, reviews, and deploys it.
Agent Studio turns a single prompt into a governed service. A builder agent scaffolds the code, a reviewer agent hunts for flaws, and an editor agent fixes them — looping build → review → improve within a budget — then it deploys with its own managed Postgres, an MCP server, a REST/A2A API, an optional frontend, scoped grants, and a signed receipt for every run.
Describe it once
You don't wire nodes on a canvas. You write one prompt describing what the agent should do, and Agent Studio turns it into a working service — the scaffolding, the tools, the API surface, the database schema. The starting point is a sentence, not a blank flowchart.
A crew, not a template
A builder agent scaffolds the code, a reviewer agent hunts for flaws and gaps, and an editor agent fixes what the reviewer finds. They loop — build, review, improve — bounded by a budget and a review cap, so you get something inspected and corrected, not the first draft of a generator.
You own the code
The output is real source in a git repo you own — readable, forkable, diffable. It is not trapped inside a visual editor you can only escape by rebuilding. When you outgrow the studio, you keep the code and edit it like any other service.
A whole service, deployed
Every agent ships as a governed service: its own managed Postgres, an MCP server, a REST/A2A API, and an optional frontend. One deploy stands up the whole app — not a chat widget that calls a model, but a service other systems and agents can actually call.
Grants, not API keys
The agent reaches its database and tools through scoped grants — audience-bound and time-limited — instead of a long-lived API key baked into an env var. Production access is explicit and revocable, so a builder-produced agent doesn't inherit a standing key to everything.
A receipt for every run
Each invocation emits an Ed25519-signed, replayable receipt: the inputs, the tool calls, the grant in force, the output. You don't audit the agent by trusting it — you keep the receipt and verify what actually happened. Don't trust the agent, trust the receipt.
Drag-and-drop toy vs. Agent Studio.
Frequently asked.
What is a2a cloud's AI agent builder?
It's Agent Studio: you describe the agent you want in one prompt, and a crew of specialist agents builds it. A builder agent scaffolds the code, a reviewer agent hunts for flaws, and an editor agent fixes them — looping build → review → improve until the work passes, bounded by a budget and a review cap. The result deploys as a real governed service with its own managed Postgres, an MCP server, a REST/A2A API, and an optional frontend. It's a builder that ships production agents, not drag-and-drop demos.
How is this different from drag-and-drop agent builders?
Most 'AI agent builders' are visual canvases: you wire nodes until a demo works, and the result lives inside the editor. Agent Studio starts from a prompt and produces real code in a git repo you own — nothing is locked in a proprietary flow. And it doesn't stop at a chatbot: it deploys a full service with a database, an MCP server, and an API, so the agent is something other systems can call in production, not a demo you screen-record.
Do I own the code the agent builder produces?
Yes. The build → review → improve loop writes real source into a git repo you own — readable, forkable, and diffable. You are never trapped in a visual editor. When you outgrow the studio, you keep the code and edit it like any other service; the studio was the starting point, not a cage.
How does the build-and-review loop actually work?
Three roles run as a crew. The builder scaffolds the agent from your prompt — code, tools, database schema, API surface. The reviewer reads the result and hunts for flaws, gaps, and risky assumptions. The editor applies fixes for what the reviewer flags. They iterate build → review → improve, bounded by a budget and a maximum number of review passes, so you get inspected and corrected work instead of a generator's untouched first draft.
What does 'deploy as a real service' actually give me?
One deploy stands up the whole agent app. It gets its own managed Postgres database, an MCP server usable directly from Claude Code or Cursor, a REST and A2A API, and an optional frontend. It scales to zero when idle and runs each invocation inside a libkrun microVM for hardware-level isolation. Its database and tools are reached through scoped, time-limited grants instead of a standing API key, and every run emits an Ed25519-signed receipt you can replay — so the agent your builder produced is governed and provable, not just live.
Describe the agent. Ship the service.
a2a cloud's Agent Studio turns one prompt into a deployed, governed agent: a builder scaffolds it, a reviewer flaw-hunts it, an editor fixes it, and it ships with its own managed Postgres, an MCP server usable from Claude Code or Cursor, a REST/A2A API, an optional frontend, scale-to-zero, libkrun microVM isolation, scoped grants instead of API keys, and an Ed25519-signed receipt for every run. Real code you own in a git repo — not a flow trapped in a visual editor.