by neuron-core · Agent Tool · ★ 2.0k
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Create Full-Featured Agentic Applications in PHP [!IMPORTANT] Get early access to new features, exclusive tutorials, and expert tips for building AI agents in PHP. Join a community of PHP developers pioneering the future of AI development. Subscribe to the newsletter Before moving on, support the Neuron AI community giving a GitHub star ⭐️. Thank you! What is Neuron? Neuron is a PHP framework for creating and orchestrating AI Agents. It allows you to integrate AI entities into your PHP applications with a powerful and flexible architecture. We provide tools for the entire agentic application development lifecycle, from LLM interfaces, data loading, multi-agent orchestration, to monitoring and debugging. In addition, we provide tutorials and other educational content to help you get started using AI Agents in your projects. Video Tutorial Requirements PHP: ^8.1 Official documentation Go to the official documentation Guides & Tutorials Check out the technical guides and tutoria
| Stars | 1,995 |
| Forks | 223 |
| Language | PHP |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.8664558394894/100 |
| Open Issues | 10 |
| Last Updated | 2026-07-02 |
| Created | 2025-03-02 |
| Est. Tokens | ~19k |
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neuron-ai is The Agentic Framework of the PHP ecosystem to build production-ready AI driven applications. Connect components (LLMs, Tools, vector DBs, memory) to agents that can interact with your data.. It is categorized as a Agent Tool with 2.0k GitHub stars.
neuron-ai is primarily written in PHP. It covers topics such as agent, agentic-ai, agentic-framework.
You can find installation instructions and usage details in the neuron-ai GitHub repository at github.com/neuron-core/neuron-ai. The project has 2.0k stars and 223 forks, indicating an active community.
neuron-ai is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to neuron-ai on Agent Skills Hub include cursor-talk-to-figma-mcp, nexent, mcp-agent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.