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Agent-Native is an open-source TypeScript framework from Builder.io for building apps in which an AI agent and a human-facing interface use the same application actions, data, and relevant context. Developers define a capability once with defineAction(); the agent can invoke it as a tool, while a React UI and other documented surfaces can call the same action layer.
What is Agent-Native?
Builder.io describes Agent-Native as “an open-source TypeScript framework for building agents that pair autonomous work with a purpose-built UI.” Rather than treating an agent as a separate chatbot bolted onto an app, the framework’s design puts agent operations and human interface operations on shared application capabilities.
The central idea is a single action definition. A developer describes what an operation accepts and does, then exposes that implementation to the agent and to user-facing or integration surfaces. The project’s overview says: “Define a capability once with defineAction(). Your agent, React UI, HTTP clients, and integrations all call the same code.” Agent-Native’s official site and its GitHub repository document this model.
How does Builder.io Agent-Native work?
Define an action once
An action represents an application capability, such as an operation on a record. The repository’s example uses defineAction(), a Zod input schema, an HTTP method, and a run function. This puts the operation’s input validation and implementation in an action layer that different callers can use.
Expose the same action to agents and interfaces
The agent invokes actions as tools; a UI invokes them from application code. The README describes the action layer as serving the UI, agents, HTTP, MCP, A2A, and CLI surfaces. Its concise distinction is: “The agent does not click through the UI. It works through the same action layer as the UI.”
The intended advantage is avoiding two separately maintained versions of an operation—one for a button or form and another for an agent tool. The project says both paths use the same validation, permissions, and implementation. That is an architectural design claim, not independent evidence that every deployment will behave reliably or securely.
How do AI agents and a web app share actions and state?
Agent-Native documents shared application data and context alongside shared actions. Agent work can appear in the UI, and work performed in the UI can be available to the agent. The project also describes passing relevant interface context to the agent, such as the current page, selected record, or active view. Its website says users and agents read and update the same PostgreSQL data source of truth.
In practical terms, a user might select a record in an app and ask an agent to work on it. The design is for the agent to receive that relevant context and call an application action, while the user can inspect or edit the resulting work in the interface. Whether this is appropriate for a particular task depends on how the app defines permissions, actions, and context; shared access does not by itself guarantee correct outcomes.
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What capabilities and examples does the project document?
The repository lists these built-in areas:
- Agent chat
- Authentication and permissions
- Skills and memory
- Automations
- Agent teams
- PostgreSQL for production and PGlite for local development
The project also provides example apps in its gallery, including Clips for meeting, screen, and voice-note capture; Design; Slides; Analytics; Calendar; Mail; Assets; Content; and Plans. These are project examples, not independent verification of their production use or a certification of the framework.
Can an AI agent use the same actions as my React UI?
Yes—that is the framework’s core documented pattern. A capability defined with defineAction() can be called by the agent and by a React UI, rather than requiring a separate agent-specific implementation. The documentation also names HTTP and integration surfaces. The amount of context and authority each caller receives remains a matter of application design and configuration.
What stack, setup, and license does Agent-Native use?
Agent-Native is written in TypeScript and is MIT-licensed. The project says developers choose their model, database, and host, and keep application code in their repository. Its documentation identifies PostgreSQL for production and PGlite for local development on a Nitro-compatible host.
The repository’s documented chat-template quick start is:
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npx --yes @agent-native/core@latest create my-agent --standalone --template chatThe command uses the project’s npm CLI to create a standalone app from the chat template. Hosting, database, and model costs depend on the services a developer chooses; an open-source framework does not make those deployment costs disappear.
What should developers evaluate before choosing it?
The shared action layer is most relevant when an app needs agents to perform the same domain operations available through its human interface. Before adopting the framework, assess how its documented pattern fits the app’s requirements:
- Action design: Which operations should be callable by an agent, and what validation and permissions should each enforce?
- Context boundaries: Which page, record, or view details should the agent receive for a task?
- Infrastructure: Which model, database, and host will the app use, and what will those services cost?
- Deployment assurance: Test the specific application’s behavior, security, performance, and operational needs rather than inferring them from a feature list.
The official materials explain the intended architecture and list included areas, but do not establish a performance benchmark, security certification, or independent production-readiness assessment. They also do not provide a verified price comparison.
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