Neuron AI
Neuron AI · Productivity · Chatbot
Neuron AI is an open source PHP framework for building production-ready AI agents, with multi-provider LLM support, RAG pipelines, and event-driven workflows.
About Neuron AI
What Is Neuron AI
Neuron AI is a PHP framework for building agentic applications. Instead of translating a Python stack into your codebase, it lets PHP teams create AI agents that call tools, pull from vector stores, remember conversations, and run multi-step workflows in the language they already ship.
The framework handles the parts that usually eat development time: provider orchestration, memory, data loading, streaming, and debugging. You define the agent, and Neuron wires the rest together. It works with plain PHP, Laravel, Symfony, and WordPress, so you are not locked into one environment.
The catch is scope. Neuron AI targets developers, not end users, so there is nothing to click through without writing PHP. Teams that want a ready-made chatbot or a drag-and-drop builder should look at hosted platforms instead. If you already run PHP in production, it removes the usual reason to bolt on a second language.
Getting Started
- Install the package with
composer require neuron-core/neuron-aiin an existing PHP 8.1 or newer project. - Add the agent skills that ship with the package so your coding assistant follows the current API.
- Create an agent class that sets a provider, like Anthropic, OpenAI, or Gemini, and defines its instructions.
- Add toolkits such as database readers or an MCP connector, then run the agent with a user message and read the response.
- Push the same agent into a workflow when you need loops, state, or human approval steps.
Product Information
A quick look at Neuron AI's pricing, supported platforms, and performance.
Best for
The users, tasks, and scenarios where this tool fits best.
Users
- PHP developers who want to build AI agents without switching to Python.
- Backend teams at Laravel, Symfony, or WordPress shops that need agents to share the same database, cache, and middleware as the rest of the app.
- Software houses and product companies that want to standardize on one agentic architecture they can hire for.
Tasks
- Turning a text prompt into a tool-using agent
- Building a RAG pipeline
- Orchestrating multi-step or multi-agent flows
Scenarios
- A Laravel app that needs a customer service agent reading the same records the app already owns.
- A data team that wants retrieval-augmented answers over internal documents without a separate Python service.
- A CMS or WordPress plugin that adds an assistant while keeping a single deployment and a single team.
Key features
Multi-Provider Support
Neuron uses one interface for large language model providers, so switching between OpenAI, Anthropic, Gemini, Mistral, or a local Ollama model is a single line of code. The framework also covers Azure, AWS Bedrock, and OpenAI-compatible endpoints, which keeps you from rewriting your app when you change vendors.
Agents and Toolkits
An agent is a PHP class with a provider and a set of instructions. You extend its reach with composable toolkits, adding database readers, API connectors, or your own custom tools. The result is an assistant that can act on your application data and external services rather than just producing text.
RAG Pipelines
Neuron ships loaders and embeddings providers that pull data from CSV, JSON, PDFs, and SQL databases, then push it into vector stores like Pinecone, Elasticsearch, Weaviate, or Qdrant. A few lines connect an agent to a knowledge base, which is what makes answers accurate on topics the base model never saw.
Event-Driven Workflows
Workflows break a job into nodes that talk through events, with support for state, branches, loops, and human approval steps. The same workflow that runs a first agent also runs a production multi-agent system, so early code carries forward as the project grows.
MCP and Tool Integration
A secure MCP connector links agents to Model Context Protocol servers, giving them access to file systems, search, GitHub, and other external capabilities. You can mix MCP tools with built-in toolkits in the same agent, which cuts the amount of glue code you write by hand.
Built-in Observability
Neuron connects to Inspector.dev for monitoring agent execution, turning on with a single line of code. Tracing tool calls, tokens, and errors in a live environment is what separates a demo that works on your laptop from something you trust in production.
Frontend Streaming and UI Protocols
Stream adapters translate Neuron's internal streaming events into frontend formats like the Vercel AI SDK and AG-UI. That means the PHP backend feeds a modern chat interface without a custom bridge, which matters when the agent sits behind a real product UI.
Pros and cons
Pros
- Keeps agent code in PHP, so it runs in the same repo, deployment, and team as your existing application.
- One-line provider swaps across OpenAI, Anthropic, Gemini, Mistral, Ollama, and more cut vendor lock-in.
- Built-in RAG, workflows, memory, and MCP connectors cover most of the work a production agent needs.
- Fully typed code with 100 percent PHPStan coverage gives strong IDE support and fewer runtime surprises.
- Free and open source under the MIT license, so there is no licensing cost to start.
Cons
- It is a developer framework, so there is nothing usable without writing PHP code.
- The built-in monitoring depends on Inspector.dev, which adds a third-party service to your stack.
- As a newer framework, it has a smaller community and fewer ready-made plugins than Python alternatives like LangChain.
- Some integrations assume you already know PHP dependency management with Composer.
Frequently asked questions
Neuron AI is an open source PHP framework for building AI agents and other agentic applications. It provides a common layer for language model providers, tools, memory, retrieval, and workflows, so PHP developers can build AI features without moving to Python.
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