Agent-Native Apps Framework

Introduction

Agent-Native is an open-source application framework designed specifically for building agent-native applications. Unlike traditional AI applications, the core innovation of the Agent-Native framework lies in the fact that AI agents and the user interface (UI) share the same database and state. This means developers no longer need to handle complex data synchronization or state management between agent logic and frontend presentation. Whether you are building automated workflows, intelligent assistants, or data-driven interactive applications, Agent-Native allows AI agents to read and write application state directly, just like operating on local variables, delivering a true "what you see is what you get" and "what you do is what gets saved" experience.

Key Features

• Shared database and state: AI agents and the frontend UI connect directly to the same data source, eliminating the need for additional API bridges or state management libraries while ensuring real-time data consistency.
• Ready-to-fork templates: A collection of application templates covering common scenarios such as chat, forms, and dashboards, helping developers kick off projects quickly from scratch.
• Agent orchestration engine: Built-in lightweight orchestration capabilities that support combining multiple AI agents into complex workflows, with automatic handling of context passing and state changes.
• Open source and extensible: Fully open source with core code released under the MIT license. Developers are free to modify, extend, or integrate third-party tools and models.
• Real-time collaboration support: Based on shared state, the framework supports multiple users and multiple agents operating collaboratively within the same interface, making it suitable for team-level applications.

Highlights

• Eliminates state fragmentation: In traditional AI applications, agents and the UI often exist in "two separate worlds" that require frequent synchronization. Agent-Native breaks down this barrier directly, reducing over 80% of backend glue code.
• Multiplies development efficiency: Through template reuse and state sharing, the iteration cycle from prototype to production can be shortened to just a few hours, making it especially suitable for rapidly validating AI product ideas.
• Native AI experience: Every interaction between users and agents is instantly reflected in the UI, and agents can also perceive user actions and respond proactively, delivering a smooth and natural experience.
• Low barrier to entry: Even developers who are not proficient in frontend frameworks or AI model deployment can quickly build fully functional intelligent applications using the templates.

Who It's For

AI application developers who want to rapidly build SaaS products, tools, or internal systems with intelligent interaction capabilities while reducing backend development overhead. Product managers and entrepreneurs who need to quickly create interactive AI product prototypes to validate market assumptions and iterate on features. Open-source contributors and researchers interested in agent architecture, state management, or human-agent collaboration interfaces who want to experiment and innovate on a flexible open-source foundation. Educators and trainers who need to demonstrate how AI agents and frontend interfaces work together in real-world applications for teaching purposes.