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Make Ordinary Developers Full-stack AI Engineers

Modular Framework for AI Agents

A composable AI agent framework that enables every developer to easily build, debug, and deploy complex AI applications

5 min
Quick Setup
100+
Built-in Agents
∞
Combinations

Why Choose MoFA

Making AI development simple, efficient, and enjoyable

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Composable Agent Architecture

Build complex AI applications by connecting agents via YAML-defined flows. Leverage a core kernel with modules for RAG (embedding, splitting, vector stores), planning, and tool integration. Easily orchestrate data flow between agents.

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Rapid Agent Development

MoFA offers a clear structure for agent development, significantly reducing boilerplate and letting you focus on core logic. The MoFA Stage visual IDE further accelerates the entire development cycle, from creation to debugging. Get started in just 5 minutes.

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Rich Agent Hub & Dev Tools

Access 100+ pre-built agents from our Agent Hub, covering data connectors, LLM integrations, and specialized tools. MoFA Stage further enhances development with visual agent management, an integrated terminal, and an advanced code editor.

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Highly Extensible Framework

Easily write custom Python agents. Integrate third-party tools, models, and data sources through well-defined interfaces. Extend core functionalities like memory (e.g., Mem0 integration) or RAG strategies by implementing custom components.

Real Examples: AI Workflows in Action

Explore different types of AI workflows - from simple hello world to complex research automation

Hello World

Simplest AI agent workflow for beginners

flowchart TB terminal-input[🖥️ Terminal Input<br/>User Query] agent[🤖 Agent<br/>Process & Respond] terminal-input --> agent agent --> terminal-input classDef inputNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px classDef agentNode fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px class terminal-input inputNode class agent agentNode

ArXiv Research

Automated research workflow with paper analysis and report generation

flowchart TB terminal[🖥️ Terminal Input<br/>Research Task] extractor[🔍 Keyword Extractor<br/>Extract Keywords] downloader[📥 Paper Downloader<br/>Download Papers] analyzer[🔬 Paper Analyzer<br/>Analyze Content] writer[✍️ Report Writer<br/>Generate Report] feedback[💬 Feedback Agent<br/>Review & Suggest] refinement[🔧 Refinement Agent<br/>Improve Report] terminal --> extractor extractor --> downloader downloader --> analyzer terminal --> analyzer analyzer --> writer terminal --> writer writer --> feedback terminal --> feedback feedback --> refinement terminal --> refinement classDef inputNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef processNode fill:#fff3e0,stroke:#f57c00,stroke-width:2px classDef analysisNode fill:#e3f2fd,stroke:#1976d2,stroke-width:2px classDef outputNode fill:#fce4ec,stroke:#c2185b,stroke-width:2px class terminal inputNode class extractor,downloader processNode class analyzer,feedback analysisNode class writer,refinement outputNode

RAG System

Retrieval-Augmented Generation for intelligent Q&A

flowchart TB terminal[🖥️ Terminal Input<br/>User Question] retrieval[🔍 RAG Retrieval<br/>Search Knowledge] reasoner[🧠 Reasoner Agent<br/>Generate Answer] terminal --> retrieval retrieval --> reasoner terminal --> reasoner retrieval --> terminal reasoner --> terminal classDef inputNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef retrievalNode fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef reasoningNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px class terminal inputNode class retrieval retrievalNode class reasoner reasoningNode

GoSim Pedia

Multi-agent system with web scraping and search capabilities

flowchart TB openai[🤖 OpenAI Server<br/>Chat Interface] gosim[🎮 GoSim Pedia Agent<br/>Main Controller] firecrawl[🕷️ Firecrawl Agent<br/>Web Scraping] rag[🧠 GoSim RAG Agent<br/>Knowledge Retrieval] serper[🔍 Serper Search Agent<br/>Web Search] openai <--> gosim gosim --> firecrawl firecrawl --> gosim gosim --> rag rag --> gosim gosim --> serper serper --> gosim classDef serverNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef mainNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px classDef toolNode fill:#fff3e0,stroke:#f57c00,stroke-width:2px class openai serverNode class gosim mainNode class firecrawl,rag,serper toolNode

Mem0 Memory System

Memory-enhanced AI workflow with retrieval and recording

flowchart TB terminal[🖥️ Terminal Input<br/>User Task] retrieval[🧠 Memory Retrieval<br/>Fetch Context] reasoner[🤔 Reasoner<br/>Process & Think] record[💾 Memory Record<br/>Store Results] terminal --> retrieval retrieval --> reasoner terminal --> reasoner reasoner --> record terminal --> record retrieval --> terminal reasoner --> terminal record --> terminal classDef inputNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef memoryNode fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef processNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px classDef storageNode fill:#fff3e0,stroke:#f57c00,stroke-width:2px class terminal inputNode class retrieval memoryNode class reasoner processNode class record storageNode

Agent Creation System

Intelligent system for generating AI agents automatically

flowchart TB openai[🤖 OpenAI Server<br/>API Interface] config[⚙️ Config Generator<br/>Generate Settings] code[👨‍💻 Code Generator<br/>Write Agent Code] dependency[📦 Dependency Generator<br/>Manage Dependencies] openai --> config openai --> code config --> code openai --> dependency code --> dependency config --> dependency dependency --> openai classDef serverNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef generatorNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px classDef codeNode fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef depNode fill:#fff3e0,stroke:#f57c00,stroke-width:2px class openai serverNode class config generatorNode class code codeNode class dependency depNode

XiaoWang Multi-Agent

Complex multi-agent workflow with reflection and generation

flowchart TB terminal[🖥️ XiaoWang Terminal<br/>Task Input] dlc[🎯 Agent DLC<br/>Task Processing] generate[🔧 Agent Generate<br/>Content Creation] reflection[🤔 Agent Reflection<br/>Self-Improvement] terminal --> dlc dlc --> generate generate --> reflection reflection --> generate generate --> dlc dlc --> terminal generate --> terminal reflection --> terminal classDef inputNode fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px classDef taskNode fill:#e1f5fe,stroke:#0277bd,stroke-width:2px classDef generateNode fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px classDef reflectNode fill:#fff3e0,stroke:#f57c00,stroke-width:2px class terminal inputNode class dlc taskNode class generate generateNode class reflection reflectNode

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See MoFA in Action

Watch how developers use MoFA to build sophisticated AI applications in minutes